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pandas-dev/pandas
|
pandas/core/dtypes/cast.py
|
maybe_infer_dtype_type
|
def maybe_infer_dtype_type(element):
"""Try to infer an object's dtype, for use in arithmetic ops
Uses `element.dtype` if that's available.
Objects implementing the iterator protocol are cast to a NumPy array,
and from there the array's type is used.
Parameters
----------
element : object
Possibly has a `.dtype` attribute, and possibly the iterator
protocol.
Returns
-------
tipo : type
Examples
--------
>>> from collections import namedtuple
>>> Foo = namedtuple("Foo", "dtype")
>>> maybe_infer_dtype_type(Foo(np.dtype("i8")))
numpy.int64
"""
tipo = None
if hasattr(element, 'dtype'):
tipo = element.dtype
elif is_list_like(element):
element = np.asarray(element)
tipo = element.dtype
return tipo
|
python
|
def maybe_infer_dtype_type(element):
"""Try to infer an object's dtype, for use in arithmetic ops
Uses `element.dtype` if that's available.
Objects implementing the iterator protocol are cast to a NumPy array,
and from there the array's type is used.
Parameters
----------
element : object
Possibly has a `.dtype` attribute, and possibly the iterator
protocol.
Returns
-------
tipo : type
Examples
--------
>>> from collections import namedtuple
>>> Foo = namedtuple("Foo", "dtype")
>>> maybe_infer_dtype_type(Foo(np.dtype("i8")))
numpy.int64
"""
tipo = None
if hasattr(element, 'dtype'):
tipo = element.dtype
elif is_list_like(element):
element = np.asarray(element)
tipo = element.dtype
return tipo
|
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Try to infer an object's dtype, for use in arithmetic ops
Uses `element.dtype` if that's available.
Objects implementing the iterator protocol are cast to a NumPy array,
and from there the array's type is used.
Parameters
----------
element : object
Possibly has a `.dtype` attribute, and possibly the iterator
protocol.
Returns
-------
tipo : type
Examples
--------
>>> from collections import namedtuple
>>> Foo = namedtuple("Foo", "dtype")
>>> maybe_infer_dtype_type(Foo(np.dtype("i8")))
numpy.int64
|
[
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] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/dtypes/cast.py#L486-L516
|
train
|
Try to infer the dtype of an object.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(1935 - 1887) + chr(111) + chr(0b110010) + chr(1133 - 1078) + chr(1202 - 1147), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1011000 + 0o27) + chr(51) + chr(1143 - 1093) + chr(194 - 142), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110001) + '\x31' + '\062', 44309 - 44301), ehT0Px3KOsy9('\x30' + '\157' + '\x36', 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + '\x32' + '\064' + chr(717 - 663), 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(49) + '\061' + chr(48), ord("\x08")), ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(8293 - 8182) + chr(0b110010) + '\x37' + chr(0b1110 + 0o42), 0o10), ehT0Px3KOsy9('\x30' + chr(5237 - 5126) + chr(507 - 457) + '\x34' + chr(0b101001 + 0o7), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(50) + chr(0b110010) + '\x33', 0b1000), ehT0Px3KOsy9('\060' + chr(7946 - 7835) + chr(0b11101 + 0o25), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + '\061' + chr(0b101100 + 0o13) + chr(55), 13542 - 13534), ehT0Px3KOsy9(chr(48) + chr(0b1101100 + 0o3) + chr(0b110001) + chr(0b10111 + 0o34) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(0b110011) + '\x37' + '\060', 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b11 + 0o60) + '\063', 7194 - 7186), ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(0b11100 + 0o123) + chr(51) + '\066' + chr(0b1011 + 0o50), ord("\x08")), ehT0Px3KOsy9(chr(0b10 + 0o56) + chr(10314 - 10203) + chr(0b110001) + '\066' + chr(0b110011), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b101011 + 0o10) + chr(556 - 507) + chr(49), ord("\x08")), ehT0Px3KOsy9(chr(0b1000 + 0o50) + chr(111) + '\063' + chr(932 - 881) + chr(55), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(95 - 44) + chr(55) + '\062', 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(284 - 234) + '\x34' + chr(2502 - 2447), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(50) + chr(1453 - 1402) + chr(0b110011), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(50) + chr(49) + chr(0b110110), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110011) + chr(1992 - 1942) + chr(54), 0b1000), ehT0Px3KOsy9(chr(2178 - 2130) + '\x6f' + '\x32' + chr(1662 - 1614) + chr(699 - 647), 0b1000), ehT0Px3KOsy9(chr(606 - 558) + chr(0b1101111) + '\066' + chr(0b100100 + 0o20), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(49) + chr(596 - 541) + chr(50), 44833 - 44825), ehT0Px3KOsy9(chr(911 - 863) + chr(0b1001001 + 0o46) + chr(0b110011) + chr(51) + '\063', 0o10), ehT0Px3KOsy9(chr(48) + chr(4157 - 4046) + chr(0b110001) + chr(0b110011) + chr(52), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(899 - 849) + '\x36' + '\067', ord("\x08")), ehT0Px3KOsy9(chr(0b1110 + 0o42) + '\157' + chr(0b11010 + 0o27) + chr(0b110011) + '\060', 62479 - 62471), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b100101 + 0o15) + '\x35' + chr(2365 - 2314), 0b1000), ehT0Px3KOsy9(chr(48) + chr(7444 - 7333) + chr(50) + chr(2031 - 1982) + chr(0b100001 + 0o17), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(833 - 783) + '\067' + '\066', ord("\x08")), ehT0Px3KOsy9(chr(0b11000 + 0o30) + chr(111) + '\x32', 8), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110010) + chr(0b110111) + chr(53), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b101 + 0o57) + chr(50), 0b1000), ehT0Px3KOsy9(chr(873 - 825) + '\157' + chr(0b10110 + 0o34) + chr(0b110101) + '\x30', 0o10), ehT0Px3KOsy9(chr(0b100011 + 0o15) + '\157' + chr(50) + chr(48) + chr(51), 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(50) + '\060' + chr(49), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + '\064' + chr(898 - 845), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(267 - 219) + chr(0b1011111 + 0o20) + chr(0b111 + 0o56) + chr(0b101001 + 0o7), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x91'), chr(0b1011100 + 0o10) + chr(0b1010 + 0o133) + chr(655 - 556) + chr(7502 - 7391) + '\144' + '\x65')('\x75' + chr(116) + chr(0b110000 + 0o66) + '\x2d' + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def YadG0MtpawrR(_CF03Rifpmdh):
tCXizGVUk0M_ = None
if lot1PSoAwYhj(_CF03Rifpmdh, xafqLlk3kkUe(SXOLrMavuUCe(b'\xdb\xa03v\xc3'), '\144' + chr(101) + '\143' + chr(111) + chr(100) + chr(0b1001001 + 0o34))('\165' + chr(116) + chr(0b1100110) + '\x2d' + chr(0b1100 + 0o54))):
tCXizGVUk0M_ = _CF03Rifpmdh.dtype
elif bAgBF7jXI53B(_CF03Rifpmdh):
_CF03Rifpmdh = WqUC3KWvYVup.asarray(_CF03Rifpmdh)
tCXizGVUk0M_ = _CF03Rifpmdh.dtype
return tCXizGVUk0M_
|
pandas-dev/pandas
|
pandas/core/dtypes/cast.py
|
maybe_upcast
|
def maybe_upcast(values, fill_value=np.nan, dtype=None, copy=False):
""" provide explicit type promotion and coercion
Parameters
----------
values : the ndarray that we want to maybe upcast
fill_value : what we want to fill with
dtype : if None, then use the dtype of the values, else coerce to this type
copy : if True always make a copy even if no upcast is required
"""
if is_extension_type(values):
if copy:
values = values.copy()
else:
if dtype is None:
dtype = values.dtype
new_dtype, fill_value = maybe_promote(dtype, fill_value)
if new_dtype != values.dtype:
values = values.astype(new_dtype)
elif copy:
values = values.copy()
return values, fill_value
|
python
|
def maybe_upcast(values, fill_value=np.nan, dtype=None, copy=False):
""" provide explicit type promotion and coercion
Parameters
----------
values : the ndarray that we want to maybe upcast
fill_value : what we want to fill with
dtype : if None, then use the dtype of the values, else coerce to this type
copy : if True always make a copy even if no upcast is required
"""
if is_extension_type(values):
if copy:
values = values.copy()
else:
if dtype is None:
dtype = values.dtype
new_dtype, fill_value = maybe_promote(dtype, fill_value)
if new_dtype != values.dtype:
values = values.astype(new_dtype)
elif copy:
values = values.copy()
return values, fill_value
|
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provide explicit type promotion and coercion
Parameters
----------
values : the ndarray that we want to maybe upcast
fill_value : what we want to fill with
dtype : if None, then use the dtype of the values, else coerce to this type
copy : if True always make a copy even if no upcast is required
|
[
"provide",
"explicit",
"type",
"promotion",
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"coercion"
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/dtypes/cast.py#L519-L542
|
train
|
provide explicit type promotion and coercion of the values to the type of the object.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(0b1101111) + '\x32' + '\063' + chr(71 - 18), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(49) + chr(49) + chr(2508 - 2457), 0o10), ehT0Px3KOsy9(chr(619 - 571) + chr(0b1101111) + '\062' + '\x30' + chr(51), 21182 - 21174), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x31' + chr(0b110110), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\061' + chr(0b110110) + '\x32', ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(50) + chr(0b110000) + chr(299 - 244), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(2360 - 2311) + '\064' + chr(1742 - 1692), 39505 - 39497), ehT0Px3KOsy9(chr(48) + '\157' + '\063' + chr(657 - 605) + chr(52), ord("\x08")), ehT0Px3KOsy9(chr(587 - 539) + chr(111) + '\x33' + '\x33' + '\065', ord("\x08")), ehT0Px3KOsy9(chr(1402 - 1354) + chr(0b1101111) + chr(0b111 + 0o54) + chr(766 - 713) + chr(766 - 711), 0b1000), ehT0Px3KOsy9(chr(0b11000 + 0o30) + chr(111) + chr(0b100101 + 0o15) + '\060' + chr(0b101000 + 0o16), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b11011 + 0o124) + chr(51) + chr(410 - 360) + chr(0b100100 + 0o21), 63582 - 63574), ehT0Px3KOsy9('\x30' + chr(0b1100000 + 0o17) + chr(50) + '\x36' + '\063', 0o10), ehT0Px3KOsy9(chr(1458 - 1410) + chr(111) + chr(0b110011) + '\x32' + chr(328 - 275), 8), ehT0Px3KOsy9('\x30' + chr(111) + '\061' + chr(55) + chr(2181 - 2132), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110100) + chr(0b11000 + 0o32), 38019 - 38011), ehT0Px3KOsy9(chr(981 - 933) + chr(194 - 83) + chr(1894 - 1845) + chr(0b110110) + chr(353 - 302), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(0b11010 + 0o35) + '\061', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1111 + 0o140) + chr(597 - 547) + chr(0b10101 + 0o33) + chr(0b1110 + 0o42), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1001001 + 0o46) + chr(49) + '\x34' + '\066', 14597 - 14589), ehT0Px3KOsy9('\x30' + chr(111) + '\062' + chr(0b100111 + 0o20) + '\x36', ord("\x08")), ehT0Px3KOsy9(chr(0b1111 + 0o41) + chr(0b1101111) + '\061' + chr(0b110011) + chr(0b1101 + 0o43), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(2455 - 2404) + chr(1150 - 1100) + chr(55), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110011) + '\x32' + '\060', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110001) + '\x30' + '\x34', 0o10), ehT0Px3KOsy9('\x30' + chr(8379 - 8268) + chr(0b110011) + '\065' + chr(0b110001), 0b1000), ehT0Px3KOsy9('\x30' + '\157' + '\067' + chr(53), ord("\x08")), ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(0b10111 + 0o130) + chr(1683 - 1634) + '\060' + '\x36', 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x31' + chr(0b1111 + 0o47) + chr(54), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x37' + '\065', 8), ehT0Px3KOsy9(chr(0b0 + 0o60) + chr(111) + chr(1526 - 1476) + chr(0b110011) + chr(0b100111 + 0o11), 0o10), ehT0Px3KOsy9(chr(0b10011 + 0o35) + chr(0b1101111) + '\x31' + '\066', 8), ehT0Px3KOsy9(chr(0b110000) + chr(5663 - 5552) + chr(51) + chr(1835 - 1785) + chr(49), ord("\x08")), ehT0Px3KOsy9(chr(0b100100 + 0o14) + chr(144 - 33) + '\061' + chr(0b101100 + 0o6) + chr(48), 0o10), ehT0Px3KOsy9('\x30' + chr(7739 - 7628) + '\063' + chr(1318 - 1264) + '\x31', 0o10), ehT0Px3KOsy9(chr(1837 - 1789) + '\x6f' + chr(50) + chr(0b110100) + chr(0b100101 + 0o16), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x33' + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(0b101111 + 0o1) + '\157' + chr(0b1100 + 0o47) + '\065' + chr(116 - 67), 8), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110010) + chr(0b110101), 0b1000), ehT0Px3KOsy9(chr(387 - 339) + chr(111) + '\x33' + chr(49) + chr(0b10010 + 0o40), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + chr(112 - 1) + chr(0b110101) + chr(0b10 + 0o56), 63409 - 63401)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xb3'), chr(0b10111 + 0o115) + chr(0b111100 + 0o51) + '\143' + chr(111) + chr(5886 - 5786) + '\145')(chr(0b1110101) + chr(0b11100 + 0o130) + chr(0b1100110) + chr(1385 - 1340) + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def Pt7jFRXjbP7u(SPnCNu54H1db, RlLNSsrUm3zD=xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf3*\xed'), '\144' + chr(101) + chr(0b1011001 + 0o12) + chr(0b1101111) + chr(100) + '\x65')(chr(117) + '\x74' + '\x66' + '\055' + chr(2276 - 2220))), jSV9IKnemH7K=None, igThHS4jwVsa=ehT0Px3KOsy9('\060' + '\x6f' + chr(1932 - 1884), 0b1000)):
if oW69L6z1WahW(SPnCNu54H1db):
if igThHS4jwVsa:
SPnCNu54H1db = SPnCNu54H1db.igThHS4jwVsa()
else:
if jSV9IKnemH7K is None:
jSV9IKnemH7K = SPnCNu54H1db.dtype
(H6Aqpf9qhdEs, RlLNSsrUm3zD) = ikHVdLFrBU6G(jSV9IKnemH7K, RlLNSsrUm3zD)
if H6Aqpf9qhdEs != xafqLlk3kkUe(SPnCNu54H1db, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf9?\xfa~\x17'), '\144' + chr(0b10000 + 0o125) + '\x63' + '\157' + '\x64' + '\145')(chr(0b1110101) + chr(9931 - 9815) + chr(102) + chr(0b101101) + '\x38')):
SPnCNu54H1db = SPnCNu54H1db.astype(H6Aqpf9qhdEs)
elif igThHS4jwVsa:
SPnCNu54H1db = SPnCNu54H1db.igThHS4jwVsa()
return (SPnCNu54H1db, RlLNSsrUm3zD)
|
pandas-dev/pandas
|
pandas/core/dtypes/cast.py
|
invalidate_string_dtypes
|
def invalidate_string_dtypes(dtype_set):
"""Change string like dtypes to object for
``DataFrame.select_dtypes()``.
"""
non_string_dtypes = dtype_set - {np.dtype('S').type, np.dtype('<U').type}
if non_string_dtypes != dtype_set:
raise TypeError("string dtypes are not allowed, use 'object' instead")
|
python
|
def invalidate_string_dtypes(dtype_set):
"""Change string like dtypes to object for
``DataFrame.select_dtypes()``.
"""
non_string_dtypes = dtype_set - {np.dtype('S').type, np.dtype('<U').type}
if non_string_dtypes != dtype_set:
raise TypeError("string dtypes are not allowed, use 'object' instead")
|
[
"def",
"invalidate_string_dtypes",
"(",
"dtype_set",
")",
":",
"non_string_dtypes",
"=",
"dtype_set",
"-",
"{",
"np",
".",
"dtype",
"(",
"'S'",
")",
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"type",
",",
"np",
".",
"dtype",
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"'<U'",
")",
".",
"type",
"}",
"if",
"non_string_dtypes",
"!=",
"dtype_set",
":",
"raise",
"TypeError",
"(",
"\"string dtypes are not allowed, use 'object' instead\"",
")"
] |
Change string like dtypes to object for
``DataFrame.select_dtypes()``.
|
[
"Change",
"string",
"like",
"dtypes",
"to",
"object",
"for",
"DataFrame",
".",
"select_dtypes",
"()",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/dtypes/cast.py#L556-L562
|
train
|
Change string like dtypes to object for
.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(120 - 72) + '\x6f' + chr(0b11000 + 0o32) + chr(50) + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(1423 - 1373) + chr(902 - 849) + chr(0b110100), 0o10), ehT0Px3KOsy9(chr(646 - 598) + '\157' + chr(593 - 543) + chr(2294 - 2240) + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(48) + chr(5702 - 5591) + chr(49) + chr(970 - 922) + chr(0b10010 + 0o36), 10188 - 10180), ehT0Px3KOsy9('\060' + chr(0b11 + 0o154) + chr(1077 - 1027) + '\067', 0b1000), ehT0Px3KOsy9(chr(0b10000 + 0o40) + chr(0b1000100 + 0o53) + chr(50) + chr(79 - 27) + chr(55), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(50) + '\066' + chr(226 - 174), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x33' + chr(0b101100 + 0o7) + chr(48), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b11 + 0o56) + chr(53) + '\x31', 0o10), ehT0Px3KOsy9(chr(1424 - 1376) + chr(0b1000011 + 0o54) + chr(0b10 + 0o60) + chr(0b110110) + '\062', 8), ehT0Px3KOsy9('\060' + chr(7342 - 7231) + '\063' + '\x35' + '\x34', 0o10), ehT0Px3KOsy9(chr(978 - 930) + '\157' + chr(0b110001) + chr(0b11110 + 0o24) + '\x32', 0b1000), ehT0Px3KOsy9(chr(0b100 + 0o54) + chr(9559 - 9448) + '\061' + chr(0b110111) + chr(1614 - 1562), 38165 - 38157), ehT0Px3KOsy9(chr(1258 - 1210) + chr(1097 - 986) + chr(0b110010) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + '\x32' + '\x31' + '\064', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x31' + '\x33' + chr(51), ord("\x08")), ehT0Px3KOsy9(chr(786 - 738) + chr(0b1101111) + '\063' + chr(0b110001) + chr(0b10100 + 0o34), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b100001 + 0o20) + '\065' + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1000 + 0o147) + chr(0b110110) + chr(0b11100 + 0o27), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(10497 - 10386) + chr(683 - 628) + chr(0b10101 + 0o34), 32810 - 32802), ehT0Px3KOsy9(chr(0b101101 + 0o3) + chr(6100 - 5989) + chr(137 - 86) + chr(0b100111 + 0o14) + chr(50), ord("\x08")), ehT0Px3KOsy9(chr(0b1110 + 0o42) + chr(0b111 + 0o150) + chr(1205 - 1154) + chr(769 - 716) + chr(486 - 436), 21122 - 21114), ehT0Px3KOsy9('\x30' + chr(111) + chr(51) + chr(0b100 + 0o56), 15188 - 15180), ehT0Px3KOsy9('\x30' + chr(111) + '\x32' + chr(0b110101) + chr(214 - 165), ord("\x08")), ehT0Px3KOsy9(chr(2275 - 2227) + chr(0b100101 + 0o112) + '\x33' + '\x35' + chr(0b10111 + 0o34), 0o10), ehT0Px3KOsy9(chr(0b100011 + 0o15) + chr(0b11110 + 0o121) + chr(1865 - 1812) + chr(55), 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110011) + chr(1140 - 1087) + chr(343 - 291), 8), ehT0Px3KOsy9('\x30' + chr(1109 - 998) + chr(0b100100 + 0o17) + chr(54) + chr(0b110000), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b100001 + 0o116) + chr(1612 - 1561) + chr(0b110101) + chr(48), 0o10), ehT0Px3KOsy9(chr(0b11 + 0o55) + '\157' + chr(0b1010 + 0o55), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1011111 + 0o20) + chr(0b110011) + '\x31' + chr(54), 0b1000), ehT0Px3KOsy9(chr(0b101001 + 0o7) + '\x6f' + '\x32' + chr(0b101110 + 0o7) + '\065', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(5607 - 5496) + '\062' + chr(0b110000) + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b110110 + 0o71) + '\061' + '\x30' + '\067', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(51) + chr(0b110010) + '\067', 26061 - 26053), ehT0Px3KOsy9(chr(48) + chr(2881 - 2770) + '\061' + chr(0b110011) + chr(2431 - 2377), 55722 - 55714), ehT0Px3KOsy9('\060' + '\x6f' + '\x34' + chr(342 - 290), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110100) + '\065', 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x33' + chr(0b10010 + 0o37) + chr(0b101100 + 0o4), 8), ehT0Px3KOsy9('\060' + chr(0b1101111 + 0o0) + chr(50) + chr(200 - 147), 25725 - 25717)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(1141 - 1093) + chr(0b101100 + 0o103) + chr(0b110101) + '\x30', ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xbe'), chr(0b1100100) + '\145' + '\x63' + chr(0b111001 + 0o66) + chr(0b10011 + 0o121) + chr(7610 - 7509))(chr(117) + chr(0b1010100 + 0o40) + chr(0b1100110) + chr(0b101101) + chr(0b11111 + 0o31)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def S0ouKFlIlp1k(nU32U6T1LFmT):
WMafKQmwI86c = nU32U6T1LFmT - {WqUC3KWvYVup.dtype(xafqLlk3kkUe(SXOLrMavuUCe(b'\xc3'), '\144' + chr(0b1100101) + chr(0b11010 + 0o111) + chr(0b111100 + 0o63) + chr(100) + chr(0b1100101))(chr(7365 - 7248) + chr(0b1110100) + '\x66' + chr(45) + chr(0b10011 + 0o45))).type, WqUC3KWvYVup.dtype(xafqLlk3kkUe(SXOLrMavuUCe(b'\xac\xf9'), '\x64' + chr(0b1100101) + chr(99) + '\x6f' + chr(100) + chr(101))(chr(0b1110101) + chr(9457 - 9341) + chr(0b1100110) + chr(45) + chr(0b111000))).type}
if WMafKQmwI86c != nU32U6T1LFmT:
raise sznFqDbNBHlx(xafqLlk3kkUe(SXOLrMavuUCe(b'\xe3\xd8\xc0)y\xc0\x94\xbc\x1d\xcb\x9c7\x0f2\xed)\xadK]V\xae\xca{\xc5\x87@\x9b\x95\x8c+\xee\xd8\xf0"\xf7yKG\xa2p\xf3\xd8\x95`~\xc9\xc7\xac\x0c\xd3\x88'), chr(0b1100100) + chr(101) + '\143' + '\x6f' + '\144' + chr(101))('\165' + chr(0b1 + 0o163) + '\x66' + chr(0b101101) + chr(0b11 + 0o65)))
|
pandas-dev/pandas
|
pandas/core/dtypes/cast.py
|
coerce_indexer_dtype
|
def coerce_indexer_dtype(indexer, categories):
""" coerce the indexer input array to the smallest dtype possible """
length = len(categories)
if length < _int8_max:
return ensure_int8(indexer)
elif length < _int16_max:
return ensure_int16(indexer)
elif length < _int32_max:
return ensure_int32(indexer)
return ensure_int64(indexer)
|
python
|
def coerce_indexer_dtype(indexer, categories):
""" coerce the indexer input array to the smallest dtype possible """
length = len(categories)
if length < _int8_max:
return ensure_int8(indexer)
elif length < _int16_max:
return ensure_int16(indexer)
elif length < _int32_max:
return ensure_int32(indexer)
return ensure_int64(indexer)
|
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] |
coerce the indexer input array to the smallest dtype possible
|
[
"coerce",
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"indexer",
"input",
"array",
"to",
"the",
"smallest",
"dtype",
"possible"
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/dtypes/cast.py#L565-L574
|
train
|
coerce the indexer input array to the smallest dtype possible
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b100011 + 0o15) + chr(0b1101111) + chr(0b110010) + chr(0b110100), 63013 - 63005), ehT0Px3KOsy9(chr(1618 - 1570) + chr(7556 - 7445) + chr(1876 - 1823) + chr(0b1011 + 0o47), 46150 - 46142), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(470 - 421) + chr(0b10011 + 0o36), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x31' + chr(1197 - 1144) + chr(49), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(51) + chr(0b110000) + '\063', 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(52) + '\067', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110010) + chr(1026 - 977) + chr(0b110111), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(8454 - 8343) + chr(0b110001) + '\060' + '\x32', ord("\x08")), ehT0Px3KOsy9(chr(0b101110 + 0o2) + chr(0b1101111) + chr(792 - 742) + '\x36' + chr(53), 42138 - 42130), ehT0Px3KOsy9('\060' + '\x6f' + chr(49) + chr(895 - 844) + chr(52), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + '\061' + '\066' + '\064', ord("\x08")), ehT0Px3KOsy9(chr(336 - 288) + '\157' + chr(49) + chr(1621 - 1572) + chr(0b110001), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110010) + chr(0b100110 + 0o20) + '\x35', 8), ehT0Px3KOsy9(chr(48) + chr(0b11000 + 0o127) + chr(0b110110) + chr(0b100 + 0o56), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + '\x31', ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(73 - 18) + chr(2122 - 2072), 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110011) + chr(0b110111) + chr(0b110110), 48797 - 48789), ehT0Px3KOsy9(chr(1251 - 1203) + '\157' + chr(0b111 + 0o52) + '\x35' + chr(0b10110 + 0o40), 26002 - 25994), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(51) + chr(1371 - 1322) + chr(2634 - 2579), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b101101 + 0o102) + chr(0b100001 + 0o25) + chr(582 - 528), ord("\x08")), ehT0Px3KOsy9(chr(829 - 781) + chr(111) + '\063' + '\064' + chr(0b110000), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b10 + 0o57) + chr(0b110110) + '\x33', 0b1000), ehT0Px3KOsy9(chr(0b100100 + 0o14) + chr(0b1101111) + '\066' + '\065', 47422 - 47414), ehT0Px3KOsy9('\x30' + chr(6048 - 5937) + chr(0b110001) + chr(0b101011 + 0o11) + chr(55), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110011) + chr(54) + '\x34', 0o10), ehT0Px3KOsy9(chr(0b101000 + 0o10) + chr(2673 - 2562) + '\062' + '\063' + chr(0b101101 + 0o4), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110010) + '\060' + chr(55), 54423 - 54415), ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(0b1001101 + 0o42) + '\064' + chr(0b11001 + 0o27), 8242 - 8234), ehT0Px3KOsy9(chr(0b101000 + 0o10) + '\x6f' + chr(0b100111 + 0o20) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + '\x33' + '\062' + chr(48), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b111001 + 0o66) + chr(0b11010 + 0o30) + chr(0b11011 + 0o32) + '\x35', 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(50) + chr(52), 8), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110110) + '\x34', 0o10), ehT0Px3KOsy9(chr(441 - 393) + '\x6f' + '\x32' + chr(1455 - 1406) + chr(0b110010), 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(49) + chr(54) + chr(1429 - 1380), 38943 - 38935), ehT0Px3KOsy9(chr(48) + chr(0b11 + 0o154) + chr(0b101011 + 0o6) + chr(50), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + '\x31' + chr(2421 - 2371) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(51) + chr(2420 - 2365), 2549 - 2541), ehT0Px3KOsy9(chr(1689 - 1641) + '\157' + '\x32' + '\065' + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(0b101101 + 0o3) + chr(111) + chr(51) + chr(1549 - 1500) + '\x34', 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + chr(0b111011 + 0o64) + chr(0b110011 + 0o2) + chr(0b11111 + 0o21), 13775 - 13767)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b':'), '\144' + chr(101) + '\x63' + chr(0b1101111) + '\x64' + '\x65')(chr(117) + chr(0b1100111 + 0o15) + chr(0b1100110) + chr(1700 - 1655) + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def IhoUBFeIAvnv(BvJfssszZMhp, mZZDAT49UzAb):
CHAOgk5VCHH_ = c2A0yzQpDQB3(mZZDAT49UzAb)
if CHAOgk5VCHH_ < QpPu2DLO1hgY:
return GbUdSRd1aN9u(BvJfssszZMhp)
elif CHAOgk5VCHH_ < ms5WZ2Hu3FO7:
return LLtIFxoEAXeb(BvJfssszZMhp)
elif CHAOgk5VCHH_ < zWd8ApOTJGRH:
return IkYWtcjOGBEn(BvJfssszZMhp)
return AZPeOKsfRpRQ(BvJfssszZMhp)
|
pandas-dev/pandas
|
pandas/core/dtypes/cast.py
|
coerce_to_dtypes
|
def coerce_to_dtypes(result, dtypes):
"""
given a dtypes and a result set, coerce the result elements to the
dtypes
"""
if len(result) != len(dtypes):
raise AssertionError("_coerce_to_dtypes requires equal len arrays")
def conv(r, dtype):
try:
if isna(r):
pass
elif dtype == _NS_DTYPE:
r = tslibs.Timestamp(r)
elif dtype == _TD_DTYPE:
r = tslibs.Timedelta(r)
elif dtype == np.bool_:
# messy. non 0/1 integers do not get converted.
if is_integer(r) and r not in [0, 1]:
return int(r)
r = bool(r)
elif dtype.kind == 'f':
r = float(r)
elif dtype.kind == 'i':
r = int(r)
except Exception:
pass
return r
return [conv(r, dtype) for r, dtype in zip(result, dtypes)]
|
python
|
def coerce_to_dtypes(result, dtypes):
"""
given a dtypes and a result set, coerce the result elements to the
dtypes
"""
if len(result) != len(dtypes):
raise AssertionError("_coerce_to_dtypes requires equal len arrays")
def conv(r, dtype):
try:
if isna(r):
pass
elif dtype == _NS_DTYPE:
r = tslibs.Timestamp(r)
elif dtype == _TD_DTYPE:
r = tslibs.Timedelta(r)
elif dtype == np.bool_:
# messy. non 0/1 integers do not get converted.
if is_integer(r) and r not in [0, 1]:
return int(r)
r = bool(r)
elif dtype.kind == 'f':
r = float(r)
elif dtype.kind == 'i':
r = int(r)
except Exception:
pass
return r
return [conv(r, dtype) for r, dtype in zip(result, dtypes)]
|
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] |
given a dtypes and a result set, coerce the result elements to the
dtypes
|
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] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/dtypes/cast.py#L577-L607
|
train
|
Coerce the result elements to the dtypes and a result set.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\x30' + chr(111) + chr(0b11001 + 0o30) + '\065' + chr(0b100000 + 0o21), ord("\x08")), ehT0Px3KOsy9(chr(0b101000 + 0o10) + chr(111) + chr(464 - 415) + chr(610 - 561), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110010) + '\062' + chr(2236 - 2185), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(1000 - 951) + chr(51) + chr(0b101010 + 0o7), 39346 - 39338), ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(8728 - 8617) + '\061' + chr(51) + '\061', 8), ehT0Px3KOsy9(chr(190 - 142) + chr(3702 - 3591) + chr(0b110001) + chr(0b110011) + '\060', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(49) + chr(817 - 767) + '\x32', 0o10), ehT0Px3KOsy9(chr(992 - 944) + '\x6f' + chr(641 - 591) + chr(0b100010 + 0o16) + chr(107 - 53), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(10497 - 10386) + '\063' + '\064', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101101 + 0o2) + '\061' + '\065' + chr(0b11111 + 0o24), 60662 - 60654), ehT0Px3KOsy9('\x30' + chr(7547 - 7436) + chr(55) + '\x36', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(50) + chr(55), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\062' + chr(53) + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(10124 - 10013) + chr(293 - 239) + '\x34', 0o10), ehT0Px3KOsy9(chr(2242 - 2194) + chr(111) + chr(1773 - 1724) + chr(0b10101 + 0o34) + chr(0b101010 + 0o12), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(0b0 + 0o61) + chr(0b110101) + chr(0b110101), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1 + 0o156) + chr(51) + chr(2706 - 2652), 0b1000), ehT0Px3KOsy9(chr(832 - 784) + '\157' + chr(0b101111 + 0o10) + chr(0b0 + 0o61), 44386 - 44378), ehT0Px3KOsy9(chr(390 - 342) + chr(0b1011100 + 0o23) + chr(316 - 267) + chr(747 - 696) + '\x35', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1 + 0o156) + chr(1970 - 1919) + '\060' + chr(0b100111 + 0o20), 49495 - 49487), ehT0Px3KOsy9(chr(0b110000) + chr(4279 - 4168) + chr(2231 - 2180) + '\x33' + chr(0b100011 + 0o23), ord("\x08")), ehT0Px3KOsy9(chr(0b111 + 0o51) + chr(111) + '\063' + '\x30' + chr(0b110101), 0o10), ehT0Px3KOsy9(chr(0b100010 + 0o16) + chr(0b1100101 + 0o12) + '\x31' + chr(2093 - 2042) + '\062', 730 - 722), ehT0Px3KOsy9(chr(399 - 351) + chr(0b1101111) + '\x31' + chr(48) + '\067', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b111010 + 0o65) + '\x31' + chr(0b110100 + 0o1) + chr(54), 18228 - 18220), ehT0Px3KOsy9('\060' + '\157' + chr(0b1 + 0o61) + chr(55) + chr(0b11001 + 0o30), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110001) + '\063' + '\x32', 8), ehT0Px3KOsy9('\060' + chr(111) + chr(49) + '\x31' + chr(54), 5047 - 5039), ehT0Px3KOsy9(chr(0b1010 + 0o46) + chr(111) + chr(1331 - 1281) + '\x36' + chr(52), ord("\x08")), ehT0Px3KOsy9(chr(1913 - 1865) + '\157' + chr(450 - 399) + chr(52) + '\x37', 27313 - 27305), ehT0Px3KOsy9('\060' + chr(0b10000 + 0o137) + chr(0b10101 + 0o34) + chr(0b110000) + '\x32', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(50) + chr(0b100001 + 0o25) + chr(55), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\063' + '\064' + chr(55), 8), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b11111 + 0o23) + '\x32', 0b1000), ehT0Px3KOsy9(chr(0b110 + 0o52) + chr(0b1000111 + 0o50) + '\062' + chr(55) + chr(51), ord("\x08")), ehT0Px3KOsy9(chr(0b10011 + 0o35) + chr(12295 - 12184) + '\x31' + chr(0b1110 + 0o46) + chr(52), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + '\x32' + '\x32' + '\x34', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x33' + chr(0b101111 + 0o1) + chr(0b101010 + 0o11), 4396 - 4388), ehT0Px3KOsy9(chr(0b110000) + chr(5363 - 5252) + '\063' + '\x32' + chr(219 - 167), 0o10), ehT0Px3KOsy9(chr(1065 - 1017) + chr(111) + chr(926 - 877) + '\x34' + chr(749 - 694), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(9320 - 9209) + chr(0b110101) + '\x30', 40013 - 40005)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'G'), '\144' + chr(6572 - 6471) + '\143' + '\157' + '\x64' + chr(0b1100101))('\165' + chr(0b1110100) + '\146' + chr(0b10110 + 0o27) + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def cBAjaDRXl5EL(ShZmEKfTkAOZ, povqwBfbr44M):
if c2A0yzQpDQB3(ShZmEKfTkAOZ) != c2A0yzQpDQB3(povqwBfbr44M):
raise vcEHXBQXuDuh(xafqLlk3kkUe(SXOLrMavuUCe(b'6j\xfc<+;7\xd9h\x04as\xdaM<\x08m\x19/\xa2\xaf\xb035\x0b\xcaz+\xc5\x92#\xdb\xc7~\xde\n\xb4\xa2\xa6\x15\x08p\xe0'), chr(2318 - 2218) + chr(0b1100101) + chr(0b1100011) + chr(111) + chr(0b100011 + 0o101) + chr(0b1100101))(chr(0b1110101) + chr(4504 - 4388) + chr(0b1100110) + '\055' + '\070'))
def m1sWr00SVpVY(JWG5qApaeJkp, jSV9IKnemH7K):
try:
if yBUx5qcFiTz6(JWG5qApaeJkp):
pass
elif jSV9IKnemH7K == NTDhEo0ZZwai:
JWG5qApaeJkp = oBknBeXuTNVm.Timestamp(JWG5qApaeJkp)
elif jSV9IKnemH7K == AMHqSK4wRc2k:
JWG5qApaeJkp = oBknBeXuTNVm.Timedelta(JWG5qApaeJkp)
elif jSV9IKnemH7K == xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\x0bf\xfc5\x06'), chr(0b1100100) + '\x65' + chr(99) + chr(0b10001 + 0o136) + '\144' + chr(0b11000 + 0o115))(chr(10405 - 10288) + chr(116) + chr(4325 - 4223) + chr(0b101101) + chr(0b111000))):
if _Et3xS6KnOuP(JWG5qApaeJkp) and JWG5qApaeJkp not in [ehT0Px3KOsy9('\x30' + '\157' + '\x30', ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110001 + 0o0), 51086 - 51078)]:
return ehT0Px3KOsy9(JWG5qApaeJkp)
JWG5qApaeJkp = WbBjf8Y7v9VN(JWG5qApaeJkp)
elif xafqLlk3kkUe(jSV9IKnemH7K, xafqLlk3kkUe(SXOLrMavuUCe(b'\x02`\xfd='), chr(7296 - 7196) + chr(2918 - 2817) + chr(99) + '\x6f' + chr(0b111111 + 0o45) + '\145')(chr(7287 - 7170) + chr(11677 - 11561) + '\146' + '\055' + chr(1694 - 1638))) == xafqLlk3kkUe(SXOLrMavuUCe(b'\x0f'), chr(100) + chr(8668 - 8567) + '\x63' + chr(0b111 + 0o150) + chr(0b1100100) + chr(0b1100101))(chr(0b1110101) + chr(0b1001101 + 0o47) + chr(0b111000 + 0o56) + chr(45) + '\070'):
JWG5qApaeJkp = kkSX4ccExqw4(JWG5qApaeJkp)
elif xafqLlk3kkUe(jSV9IKnemH7K, xafqLlk3kkUe(SXOLrMavuUCe(b'\x02`\xfd='), '\144' + chr(0b1100101) + '\143' + chr(0b1101111) + chr(0b1100100) + chr(8227 - 8126))(chr(117) + chr(116) + '\x66' + '\x2d' + chr(2098 - 2042))) == xafqLlk3kkUe(SXOLrMavuUCe(b'\x00'), '\x64' + '\145' + chr(0b1100011) + '\x6f' + '\144' + chr(8193 - 8092))('\165' + chr(9304 - 9188) + chr(4006 - 3904) + chr(45) + chr(0b111000)):
JWG5qApaeJkp = ehT0Px3KOsy9(JWG5qApaeJkp)
except jLmadlzMdunT:
pass
return JWG5qApaeJkp
return [m1sWr00SVpVY(JWG5qApaeJkp, jSV9IKnemH7K) for (JWG5qApaeJkp, jSV9IKnemH7K) in pZ0NK2y6HRbn(ShZmEKfTkAOZ, povqwBfbr44M)]
|
pandas-dev/pandas
|
pandas/core/dtypes/cast.py
|
astype_nansafe
|
def astype_nansafe(arr, dtype, copy=True, skipna=False):
"""
Cast the elements of an array to a given dtype a nan-safe manner.
Parameters
----------
arr : ndarray
dtype : np.dtype
copy : bool, default True
If False, a view will be attempted but may fail, if
e.g. the item sizes don't align.
skipna: bool, default False
Whether or not we should skip NaN when casting as a string-type.
Raises
------
ValueError
The dtype was a datetime64/timedelta64 dtype, but it had no unit.
"""
# dispatch on extension dtype if needed
if is_extension_array_dtype(dtype):
return dtype.construct_array_type()._from_sequence(
arr, dtype=dtype, copy=copy)
if not isinstance(dtype, np.dtype):
dtype = pandas_dtype(dtype)
if issubclass(dtype.type, str):
return lib.astype_str(arr.ravel(),
skipna=skipna).reshape(arr.shape)
elif is_datetime64_dtype(arr):
if is_object_dtype(dtype):
return tslib.ints_to_pydatetime(arr.view(np.int64))
elif dtype == np.int64:
return arr.view(dtype)
# allow frequency conversions
if dtype.kind == 'M':
return arr.astype(dtype)
raise TypeError("cannot astype a datetimelike from [{from_dtype}] "
"to [{to_dtype}]".format(from_dtype=arr.dtype,
to_dtype=dtype))
elif is_timedelta64_dtype(arr):
if is_object_dtype(dtype):
return tslibs.ints_to_pytimedelta(arr.view(np.int64))
elif dtype == np.int64:
return arr.view(dtype)
if dtype not in [_INT64_DTYPE, _TD_DTYPE]:
# allow frequency conversions
# we return a float here!
if dtype.kind == 'm':
mask = isna(arr)
result = arr.astype(dtype).astype(np.float64)
result[mask] = np.nan
return result
elif dtype == _TD_DTYPE:
return arr.astype(_TD_DTYPE, copy=copy)
raise TypeError("cannot astype a timedelta from [{from_dtype}] "
"to [{to_dtype}]".format(from_dtype=arr.dtype,
to_dtype=dtype))
elif (np.issubdtype(arr.dtype, np.floating) and
np.issubdtype(dtype, np.integer)):
if not np.isfinite(arr).all():
raise ValueError('Cannot convert non-finite values (NA or inf) to '
'integer')
elif is_object_dtype(arr):
# work around NumPy brokenness, #1987
if np.issubdtype(dtype.type, np.integer):
return lib.astype_intsafe(arr.ravel(), dtype).reshape(arr.shape)
# if we have a datetime/timedelta array of objects
# then coerce to a proper dtype and recall astype_nansafe
elif is_datetime64_dtype(dtype):
from pandas import to_datetime
return astype_nansafe(to_datetime(arr).values, dtype, copy=copy)
elif is_timedelta64_dtype(dtype):
from pandas import to_timedelta
return astype_nansafe(to_timedelta(arr).values, dtype, copy=copy)
if dtype.name in ("datetime64", "timedelta64"):
msg = ("The '{dtype}' dtype has no unit. "
"Please pass in '{dtype}[ns]' instead.")
raise ValueError(msg.format(dtype=dtype.name))
if copy or is_object_dtype(arr) or is_object_dtype(dtype):
# Explicit copy, or required since NumPy can't view from / to object.
return arr.astype(dtype, copy=True)
return arr.view(dtype)
|
python
|
def astype_nansafe(arr, dtype, copy=True, skipna=False):
"""
Cast the elements of an array to a given dtype a nan-safe manner.
Parameters
----------
arr : ndarray
dtype : np.dtype
copy : bool, default True
If False, a view will be attempted but may fail, if
e.g. the item sizes don't align.
skipna: bool, default False
Whether or not we should skip NaN when casting as a string-type.
Raises
------
ValueError
The dtype was a datetime64/timedelta64 dtype, but it had no unit.
"""
# dispatch on extension dtype if needed
if is_extension_array_dtype(dtype):
return dtype.construct_array_type()._from_sequence(
arr, dtype=dtype, copy=copy)
if not isinstance(dtype, np.dtype):
dtype = pandas_dtype(dtype)
if issubclass(dtype.type, str):
return lib.astype_str(arr.ravel(),
skipna=skipna).reshape(arr.shape)
elif is_datetime64_dtype(arr):
if is_object_dtype(dtype):
return tslib.ints_to_pydatetime(arr.view(np.int64))
elif dtype == np.int64:
return arr.view(dtype)
# allow frequency conversions
if dtype.kind == 'M':
return arr.astype(dtype)
raise TypeError("cannot astype a datetimelike from [{from_dtype}] "
"to [{to_dtype}]".format(from_dtype=arr.dtype,
to_dtype=dtype))
elif is_timedelta64_dtype(arr):
if is_object_dtype(dtype):
return tslibs.ints_to_pytimedelta(arr.view(np.int64))
elif dtype == np.int64:
return arr.view(dtype)
if dtype not in [_INT64_DTYPE, _TD_DTYPE]:
# allow frequency conversions
# we return a float here!
if dtype.kind == 'm':
mask = isna(arr)
result = arr.astype(dtype).astype(np.float64)
result[mask] = np.nan
return result
elif dtype == _TD_DTYPE:
return arr.astype(_TD_DTYPE, copy=copy)
raise TypeError("cannot astype a timedelta from [{from_dtype}] "
"to [{to_dtype}]".format(from_dtype=arr.dtype,
to_dtype=dtype))
elif (np.issubdtype(arr.dtype, np.floating) and
np.issubdtype(dtype, np.integer)):
if not np.isfinite(arr).all():
raise ValueError('Cannot convert non-finite values (NA or inf) to '
'integer')
elif is_object_dtype(arr):
# work around NumPy brokenness, #1987
if np.issubdtype(dtype.type, np.integer):
return lib.astype_intsafe(arr.ravel(), dtype).reshape(arr.shape)
# if we have a datetime/timedelta array of objects
# then coerce to a proper dtype and recall astype_nansafe
elif is_datetime64_dtype(dtype):
from pandas import to_datetime
return astype_nansafe(to_datetime(arr).values, dtype, copy=copy)
elif is_timedelta64_dtype(dtype):
from pandas import to_timedelta
return astype_nansafe(to_timedelta(arr).values, dtype, copy=copy)
if dtype.name in ("datetime64", "timedelta64"):
msg = ("The '{dtype}' dtype has no unit. "
"Please pass in '{dtype}[ns]' instead.")
raise ValueError(msg.format(dtype=dtype.name))
if copy or is_object_dtype(arr) or is_object_dtype(dtype):
# Explicit copy, or required since NumPy can't view from / to object.
return arr.astype(dtype, copy=True)
return arr.view(dtype)
|
[
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"astype_nansafe",
"(",
"arr",
",",
"dtype",
",",
"copy",
"=",
"True",
",",
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] |
Cast the elements of an array to a given dtype a nan-safe manner.
Parameters
----------
arr : ndarray
dtype : np.dtype
copy : bool, default True
If False, a view will be attempted but may fail, if
e.g. the item sizes don't align.
skipna: bool, default False
Whether or not we should skip NaN when casting as a string-type.
Raises
------
ValueError
The dtype was a datetime64/timedelta64 dtype, but it had no unit.
|
[
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"an",
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"a",
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"-",
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"manner",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/dtypes/cast.py#L610-L710
|
train
|
Cast the elements of an array to a given dtype a nan - safe manner.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b100011 + 0o16) + chr(52) + chr(0b110000), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(1058 - 1009) + chr(1814 - 1762) + '\066', 30009 - 30001), ehT0Px3KOsy9('\x30' + '\157' + chr(54) + '\062', 0b1000), ehT0Px3KOsy9(chr(0b101100 + 0o4) + chr(5245 - 5134) + '\x31' + chr(0b101000 + 0o11) + chr(0b10000 + 0o40), 0b1000), ehT0Px3KOsy9(chr(0b10001 + 0o37) + chr(0b1000 + 0o147) + chr(647 - 597) + '\x32' + chr(0b110010 + 0o0), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b1110 + 0o45) + chr(1941 - 1892) + chr(54), 0o10), ehT0Px3KOsy9(chr(0b11011 + 0o25) + chr(0b100111 + 0o110) + '\061' + chr(0b11110 + 0o30) + chr(314 - 262), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(50) + chr(0b110010 + 0o1) + chr(0b110100), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b100000 + 0o117) + chr(50) + '\x31' + chr(381 - 333), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x32' + '\x35' + chr(399 - 347), ord("\x08")), ehT0Px3KOsy9(chr(1080 - 1032) + chr(700 - 589) + chr(0b110001) + '\x32' + '\067', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b100111 + 0o12) + '\064' + '\x36', 8), ehT0Px3KOsy9(chr(1508 - 1460) + '\157' + chr(0b110010) + '\x35' + '\x30', 0o10), ehT0Px3KOsy9(chr(2120 - 2072) + chr(0b1101111) + chr(55), 53570 - 53562), ehT0Px3KOsy9(chr(290 - 242) + chr(111) + chr(1985 - 1934) + '\x36', 0b1000), ehT0Px3KOsy9('\x30' + chr(4010 - 3899) + chr(50) + chr(0b110011 + 0o0) + chr(0b11001 + 0o33), 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b1000011 + 0o54) + '\x32' + chr(52), 44901 - 44893), ehT0Px3KOsy9(chr(360 - 312) + '\157' + chr(0b100110 + 0o14) + chr(0b10000 + 0o40), 63576 - 63568), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b10100 + 0o35) + chr(723 - 668) + chr(0b100111 + 0o11), 2580 - 2572), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\062' + '\x37' + chr(0b1100 + 0o50), 0o10), ehT0Px3KOsy9(chr(261 - 213) + chr(111) + chr(0b1000 + 0o52) + chr(0b110110) + '\x32', 38670 - 38662), ehT0Px3KOsy9(chr(1039 - 991) + chr(0b1100100 + 0o13) + chr(2347 - 2295) + chr(54), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(2348 - 2298) + '\062' + chr(50), 8), ehT0Px3KOsy9('\x30' + chr(11291 - 11180) + chr(0b110001) + chr(2146 - 2095) + '\x33', 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(50) + chr(49) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(0b110 + 0o52) + chr(111) + '\x33' + chr(0b100100 + 0o22) + chr(48), 0o10), ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(111) + chr(0b101110 + 0o5) + chr(54) + chr(2396 - 2344), 21050 - 21042), ehT0Px3KOsy9('\x30' + chr(0b110110 + 0o71) + '\x31' + '\066' + chr(0b110111), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110100) + '\x35', 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(0b100001 + 0o22) + '\x37' + '\061', 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110010) + chr(0b101 + 0o57) + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(161 - 111) + chr(48) + chr(0b110100), 0b1000), ehT0Px3KOsy9('\060' + chr(9921 - 9810) + '\x36' + chr(0b110011), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(50) + '\x31' + '\063', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + '\x31' + '\x34' + chr(0b110110), 8), ehT0Px3KOsy9(chr(1696 - 1648) + '\x6f' + '\062' + chr(0b101011 + 0o7) + chr(0b110010), 8), ehT0Px3KOsy9('\x30' + chr(9215 - 9104) + '\062' + chr(0b11011 + 0o31) + chr(1506 - 1454), 12551 - 12543), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b0 + 0o63) + chr(50) + chr(160 - 111), ord("\x08")), ehT0Px3KOsy9(chr(1329 - 1281) + chr(8279 - 8168) + chr(49) + '\060' + '\062', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + '\062' + chr(0b110011) + chr(1938 - 1886), 8)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b10 + 0o63) + chr(0b0 + 0o60), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'N'), '\x64' + chr(101) + '\x63' + chr(0b100011 + 0o114) + '\144' + '\145')('\x75' + '\164' + chr(6429 - 6327) + chr(1083 - 1038) + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def ohhH0MLTXIg1(ZxkNvNvuRNy5, jSV9IKnemH7K, igThHS4jwVsa=ehT0Px3KOsy9(chr(980 - 932) + '\157' + '\061', 10218 - 10210), YLCdgpr_ZbeP=ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(269 - 221), 0o10)):
if BeeaaSlTfmO2(jSV9IKnemH7K):
return xafqLlk3kkUe(jSV9IKnemH7K.construct_array_type(), xafqLlk3kkUe(SXOLrMavuUCe(b"?\x00@'\xff\x91\x07\xf9\xf9\xd92\x08\xcbb"), chr(100) + chr(0b11110 + 0o107) + '\143' + '\157' + '\x64' + chr(101))(chr(0b1011001 + 0o34) + chr(116) + chr(0b1100110) + chr(0b101010 + 0o3) + '\x38'))(ZxkNvNvuRNy5, dtype=jSV9IKnemH7K, copy=igThHS4jwVsa)
if not PlSM16l2KDPD(jSV9IKnemH7K, xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\x04\x12K8\xf7'), chr(100) + '\x65' + '\143' + chr(0b1101111) + '\144' + chr(0b111100 + 0o51))(chr(0b1100000 + 0o25) + chr(0b1110100) + chr(102) + '\x2d' + '\x38'))):
jSV9IKnemH7K = ztkhtLN5RyzB(jSV9IKnemH7K)
if J6u1YyThfhgG(xafqLlk3kkUe(jSV9IKnemH7K, xafqLlk3kkUe(SXOLrMavuUCe(b'\x14\x1fB-'), chr(0b1100100) + chr(0b101101 + 0o70) + chr(2335 - 2236) + chr(0b1011111 + 0o20) + chr(0b1100010 + 0o2) + '\x65')('\x75' + '\164' + chr(102) + chr(0b101101) + chr(0b111000))), M8_cKLkHVB2V):
return xafqLlk3kkUe(JiWVXlj3BjzT.astype_str(ZxkNvNvuRNy5.ravel(), skipna=YLCdgpr_ZbeP), xafqLlk3kkUe(SXOLrMavuUCe(b'\x12\x03A \xf3\xbe\x11'), chr(0b101101 + 0o67) + chr(8931 - 8830) + chr(6642 - 6543) + '\157' + chr(1385 - 1285) + chr(101))('\165' + chr(116) + chr(0b1000111 + 0o37) + '\055' + chr(0b101001 + 0o17)))(xafqLlk3kkUe(ZxkNvNvuRNy5, xafqLlk3kkUe(SXOLrMavuUCe(b'\x13\x0eS8\xf7'), chr(8439 - 8339) + chr(101) + chr(0b1001111 + 0o24) + chr(0b1101111) + '\144' + chr(4456 - 4355))('\165' + chr(0b1110100) + chr(0b101100 + 0o72) + '\055' + chr(0b1001 + 0o57))))
elif o97MkxKQGNoK(ZxkNvNvuRNy5):
if NGkWsclKfnpq(jSV9IKnemH7K):
return xafqLlk3kkUe(vNWoJjphZK5I, xafqLlk3kkUe(SXOLrMavuUCe(b'\t\x08F;\xcd\xba\x1b\xc3\xf8\xd53\x07\xdcbj\xf5yu'), '\x64' + chr(101) + chr(0b1100011) + chr(772 - 661) + chr(0b1100100) + chr(101))(chr(0b1110101) + chr(116) + '\146' + '\x2d' + '\070'))(xafqLlk3kkUe(ZxkNvNvuRNy5, xafqLlk3kkUe(SXOLrMavuUCe(b'\x16\x0fW?'), chr(0b10000 + 0o124) + chr(0b1000000 + 0o45) + '\x63' + chr(6408 - 6297) + chr(0b1100100) + chr(0b1100101))(chr(117) + chr(0b1110100) + chr(0b1100110) + chr(0b101011 + 0o2) + chr(0b111000)))(xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\t\x08F~\xa6'), '\x64' + '\145' + '\x63' + chr(0b1101111) + chr(0b1100100) + chr(0b1100101))(chr(6712 - 6595) + chr(0b11100 + 0o130) + chr(5811 - 5709) + chr(0b101101) + chr(56)))))
elif jSV9IKnemH7K == xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\t\x08F~\xa6'), '\144' + chr(0b101101 + 0o70) + chr(99) + '\157' + '\144' + '\x65')('\x75' + chr(0b1000 + 0o154) + chr(102) + chr(1514 - 1469) + chr(0b111000))):
return xafqLlk3kkUe(ZxkNvNvuRNy5, xafqLlk3kkUe(SXOLrMavuUCe(b'\x16\x0fW?'), '\x64' + chr(0b1100101) + '\143' + chr(4806 - 4695) + chr(0b1100100) + '\145')(chr(0b110010 + 0o103) + chr(5145 - 5029) + chr(0b1100001 + 0o5) + '\055' + chr(56)))(jSV9IKnemH7K)
if xafqLlk3kkUe(jSV9IKnemH7K, xafqLlk3kkUe(SXOLrMavuUCe(b'\x0b\x0f\\,'), '\144' + '\x65' + chr(99) + chr(0b1101111) + chr(846 - 746) + chr(9669 - 9568))('\165' + chr(2172 - 2056) + chr(761 - 659) + chr(0b101101) + '\x38')) == xafqLlk3kkUe(SXOLrMavuUCe(b'-'), chr(100) + chr(0b1100101) + chr(99) + chr(9361 - 9250) + chr(0b1110 + 0o126) + chr(490 - 389))(chr(0b1001101 + 0o50) + chr(0b1110100) + chr(1793 - 1691) + chr(1758 - 1713) + '\x38'):
return xafqLlk3kkUe(ZxkNvNvuRNy5, xafqLlk3kkUe(SXOLrMavuUCe(b'\x01\x15F1\xe2\xab'), '\x64' + '\145' + chr(8933 - 8834) + chr(271 - 160) + '\x64' + '\x65')('\165' + chr(3408 - 3292) + chr(0b1111 + 0o127) + chr(0b101101) + chr(0b11101 + 0o33)))(jSV9IKnemH7K)
raise sznFqDbNBHlx(xafqLlk3kkUe(xafqLlk3kkUe(SXOLrMavuUCe(b"\x03\x07\\&\xfd\xbaT\xfd\xfb\xd8.\x16\xcd'\x7f\xbcpq\x0c\xd9\xc6O\xff>\xe1\x99\x9f\x12\x05\x9f\xd3\xeb^\xab=\xe9\xc2\xa3-\xf1?\x02F1\xe2\xab\t\xc1\xa8\xd88F\xf3|j\xf3Kt\x0c\xc5\xc2C\xef\x06"), chr(0b11001 + 0o113) + chr(4743 - 4642) + '\143' + chr(111) + chr(7407 - 7307) + chr(7998 - 7897))(chr(0b1110101) + chr(116) + chr(102) + '\x2d' + '\070'), xafqLlk3kkUe(SXOLrMavuUCe(b'\x06\t@%\xf3\xba'), chr(9222 - 9122) + '\145' + chr(99) + chr(3265 - 3154) + chr(0b1100100) + chr(0b1011110 + 0o7))('\x75' + chr(116) + chr(0b100001 + 0o105) + '\x2d' + chr(0b100101 + 0o23)))(from_dtype=xafqLlk3kkUe(ZxkNvNvuRNy5, xafqLlk3kkUe(SXOLrMavuUCe(b'\x04\x12K8\xf7'), '\144' + '\145' + chr(99) + '\157' + chr(100) + chr(0b1000000 + 0o45))('\165' + chr(116) + chr(9760 - 9658) + chr(1704 - 1659) + '\070')), to_dtype=jSV9IKnemH7K))
elif n1ufouZS6xrY(ZxkNvNvuRNy5):
if NGkWsclKfnpq(jSV9IKnemH7K):
return xafqLlk3kkUe(oBknBeXuTNVm, xafqLlk3kkUe(SXOLrMavuUCe(b'\t\x08F;\xcd\xba\x1b\xc3\xf8\xd5#\x0f\xc5bz\xf9xd\x19'), chr(6219 - 6119) + '\x65' + '\x63' + chr(0b1101111) + chr(7215 - 7115) + '\145')(chr(0b11010 + 0o133) + chr(4768 - 4652) + chr(0b1001101 + 0o31) + chr(45) + chr(716 - 660)))(xafqLlk3kkUe(ZxkNvNvuRNy5, xafqLlk3kkUe(SXOLrMavuUCe(b'\x16\x0fW?'), chr(0b100 + 0o140) + '\145' + chr(99) + '\157' + '\x64' + chr(0b1000011 + 0o42))(chr(117) + chr(0b111111 + 0o65) + chr(102) + '\x2d' + '\x38'))(xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\t\x08F~\xa6'), chr(0b1100100) + chr(101) + '\x63' + chr(111) + '\144' + '\x65')(chr(3429 - 3312) + chr(0b100100 + 0o120) + chr(102) + '\055' + chr(0b111000)))))
elif jSV9IKnemH7K == xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\t\x08F~\xa6'), chr(7487 - 7387) + chr(0b1100101) + chr(0b1100011) + '\x6f' + chr(0b100111 + 0o75) + chr(0b1100101))(chr(117) + chr(0b1011101 + 0o27) + chr(0b110 + 0o140) + chr(493 - 448) + chr(2572 - 2516))):
return xafqLlk3kkUe(ZxkNvNvuRNy5, xafqLlk3kkUe(SXOLrMavuUCe(b'\x16\x0fW?'), chr(8464 - 8364) + chr(0b1100101) + chr(0b101100 + 0o67) + chr(0b1101111) + chr(100) + chr(5078 - 4977))(chr(12915 - 12798) + chr(116) + chr(0b100111 + 0o77) + '\x2d' + '\x38'))(jSV9IKnemH7K)
if jSV9IKnemH7K not in [lYRy66BjmPF6, AMHqSK4wRc2k]:
if xafqLlk3kkUe(jSV9IKnemH7K, xafqLlk3kkUe(SXOLrMavuUCe(b'\x0b\x0f\\,'), chr(0b1100100) + chr(0b1100101) + '\143' + chr(0b111001 + 0o66) + chr(0b101010 + 0o72) + chr(0b100100 + 0o101))('\165' + '\164' + chr(4516 - 4414) + chr(45) + '\070')) == xafqLlk3kkUe(SXOLrMavuUCe(b'\r'), chr(100) + chr(6329 - 6228) + chr(0b1100011) + chr(111) + '\x64' + '\145')(chr(117) + chr(116) + chr(0b1100110) + chr(45) + '\070'):
Iz1jSgUKZDvt = yBUx5qcFiTz6(ZxkNvNvuRNy5)
ShZmEKfTkAOZ = ZxkNvNvuRNy5.astype(jSV9IKnemH7K).astype(WqUC3KWvYVup.float64)
ShZmEKfTkAOZ[Iz1jSgUKZDvt] = WqUC3KWvYVup.nan
return ShZmEKfTkAOZ
elif jSV9IKnemH7K == AMHqSK4wRc2k:
return xafqLlk3kkUe(ZxkNvNvuRNy5, xafqLlk3kkUe(SXOLrMavuUCe(b'\x01\x15F1\xe2\xab'), chr(100) + '\x65' + chr(0b1001010 + 0o31) + chr(8903 - 8792) + chr(0b1011010 + 0o12) + '\145')(chr(0b110010 + 0o103) + chr(0b1110100) + chr(102) + '\055' + chr(56)))(AMHqSK4wRc2k, copy=igThHS4jwVsa)
raise sznFqDbNBHlx(xafqLlk3kkUe(xafqLlk3kkUe(SXOLrMavuUCe(b"\x03\x07\\&\xfd\xbaT\xfd\xfb\xd8.\x16\xcd'\x7f\xbc`y\x15\xd9\xd6C\xfe/\xec\xd0\x92\x05J\x94\x81\xdfH\xed\x14\xfd\xc9\x8e&\xe8\x19\x16W5\xcf\xee\x00\xf3\xa8\xf7,\x12\xc7Xz\xe8m`\x1d\xc1\xef"), chr(0b1100100) + chr(9216 - 9115) + chr(99) + chr(3844 - 3733) + chr(0b100111 + 0o75) + chr(3593 - 3492))(chr(12924 - 12807) + chr(0b1100111 + 0o15) + chr(9233 - 9131) + chr(45) + '\070'), xafqLlk3kkUe(SXOLrMavuUCe(b'\x06\t@%\xf3\xba'), '\x64' + chr(0b1100101) + '\143' + '\x6f' + '\144' + chr(0b10101 + 0o120))(chr(0b1010101 + 0o40) + '\x74' + '\146' + chr(45) + '\070'))(from_dtype=xafqLlk3kkUe(ZxkNvNvuRNy5, xafqLlk3kkUe(SXOLrMavuUCe(b'\x04\x12K8\xf7'), chr(0b1100100) + '\x65' + chr(0b101 + 0o136) + chr(8907 - 8796) + chr(0b1000001 + 0o43) + chr(0b1010100 + 0o21))(chr(0b1100 + 0o151) + '\164' + chr(0b10001 + 0o125) + chr(45) + chr(56))), to_dtype=jSV9IKnemH7K))
elif xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\t\x15A=\xf0\xaa\x00\xe5\xf8\xc9'), '\x64' + chr(731 - 630) + chr(99) + chr(0b1000100 + 0o53) + '\x64' + chr(0b1100101))(chr(0b11111 + 0o126) + chr(116) + chr(0b1100110) + chr(45) + chr(0b111000)))(xafqLlk3kkUe(ZxkNvNvuRNy5, xafqLlk3kkUe(SXOLrMavuUCe(b'\x04\x12K8\xf7'), '\144' + chr(0b1100101) + '\x63' + '\157' + chr(0b1100100) + '\x65')('\x75' + chr(0b1011110 + 0o26) + chr(5771 - 5669) + chr(1146 - 1101) + '\070')), xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\x06\n])\xe6\xa7\x1a\xfb'), chr(4658 - 4558) + chr(1699 - 1598) + '\143' + '\157' + chr(0b1100100) + '\x65')(chr(0b1110101) + chr(0b1110100) + '\146' + chr(0b100101 + 0o10) + '\x38'))) and xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\t\x15A=\xf0\xaa\x00\xe5\xf8\xc9'), chr(0b1011110 + 0o6) + chr(101) + chr(99) + chr(0b1101111) + '\x64' + chr(6853 - 6752))('\x75' + chr(0b101111 + 0o105) + chr(4285 - 4183) + '\055' + chr(0b111000)))(jSV9IKnemH7K, xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\t\x08F-\xf5\xab\x06'), chr(100) + '\145' + chr(0b1100011) + '\157' + '\144' + chr(0b11011 + 0o112))(chr(9585 - 9468) + '\x74' + '\146' + '\x2d' + chr(2062 - 2006)))):
if not xafqLlk3kkUe(WqUC3KWvYVup.isfinite(ZxkNvNvuRNy5), xafqLlk3kkUe(SXOLrMavuUCe(b'$\n\x06p\xfc\xa4E\xee\xea\xc5eU'), '\x64' + chr(101) + '\143' + chr(111) + chr(0b101010 + 0o72) + chr(0b1100101))('\x75' + chr(1207 - 1091) + '\146' + chr(0b101101) + chr(56)))():
raise q1QCh3W88sgk(xafqLlk3kkUe(SXOLrMavuUCe(b'#\x07\\&\xfd\xbaT\xff\xe7\xc2!\x03\xdas>\xf2{~U\xda\xdbH\xfb/\xe8\xd0\x82\x16I\x8c\xc4\xf7\x13\xa3(\xd3\x84\xbe0\xbc\t\x08Ta\xb2\xba\x1b\xbc\xe1\xc2#\x03\xcfbl'), chr(0b110010 + 0o62) + '\x65' + '\x63' + '\157' + chr(0b1100100) + chr(0b10 + 0o143))(chr(0b1101001 + 0o14) + chr(116) + chr(5263 - 5161) + chr(632 - 587) + chr(787 - 731)))
elif NGkWsclKfnpq(ZxkNvNvuRNy5):
if xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\t\x15A=\xf0\xaa\x00\xe5\xf8\xc9'), chr(2048 - 1948) + '\145' + chr(0b1100011) + chr(0b1101111) + chr(0b1100100) + '\x65')(chr(0b1110101) + '\x74' + chr(0b1010 + 0o134) + '\055' + '\x38'))(xafqLlk3kkUe(jSV9IKnemH7K, xafqLlk3kkUe(SXOLrMavuUCe(b'\x14\x1fB-'), '\144' + '\145' + '\x63' + chr(111) + chr(0b1100100) + chr(101))('\165' + '\x74' + chr(102) + '\055' + chr(2000 - 1944))), xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\t\x08F-\xf5\xab\x06'), chr(0b1001100 + 0o30) + '\x65' + '\x63' + '\157' + chr(100) + '\x65')(chr(3971 - 3854) + '\164' + chr(102) + chr(0b101101) + chr(65 - 9)))):
return xafqLlk3kkUe(JiWVXlj3BjzT.astype_intsafe(ZxkNvNvuRNy5.ravel(), jSV9IKnemH7K), xafqLlk3kkUe(SXOLrMavuUCe(b'\x12\x03A \xf3\xbe\x11'), '\144' + '\145' + chr(3194 - 3095) + '\x6f' + chr(100) + chr(7130 - 7029))(chr(117) + '\164' + chr(0b111101 + 0o51) + chr(45) + chr(0b111000)))(xafqLlk3kkUe(ZxkNvNvuRNy5, xafqLlk3kkUe(SXOLrMavuUCe(b'\x13\x0eS8\xf7'), chr(100) + '\x65' + chr(0b1100011) + chr(0b1100011 + 0o14) + chr(100) + chr(101))('\x75' + '\164' + '\x66' + '\x2d' + chr(0b111000))))
elif o97MkxKQGNoK(jSV9IKnemH7K):
(IF08dLE993_s,) = (xafqLlk3kkUe(NPPHb59961Bv(xafqLlk3kkUe(SXOLrMavuUCe(b'\x10\x07\\,\xf3\xbd'), chr(0b100 + 0o140) + '\x65' + '\x63' + '\157' + chr(0b1001 + 0o133) + chr(0b111001 + 0o54))(chr(0b1011010 + 0o33) + '\164' + '\146' + chr(45) + chr(0b110111 + 0o1)), xafqLlk3kkUe(SXOLrMavuUCe(b'\x14\tm,\xf3\xba\x11\xe8\xe1\xc12'), '\144' + chr(0b1001000 + 0o35) + chr(6950 - 6851) + chr(111) + chr(0b1000100 + 0o40) + chr(8474 - 8373))('\x75' + chr(0b1110100) + chr(6909 - 6807) + '\055' + chr(56))), xafqLlk3kkUe(SXOLrMavuUCe(b'\x14\tm,\xf3\xba\x11\xe8\xe1\xc12'), chr(0b1001010 + 0o32) + chr(0b10001 + 0o124) + '\143' + '\x6f' + chr(7146 - 7046) + chr(0b1100 + 0o131))('\165' + chr(0b1110100) + chr(0b110111 + 0o57) + chr(0b101000 + 0o5) + chr(56))),)
return ohhH0MLTXIg1(xafqLlk3kkUe(IF08dLE993_s(ZxkNvNvuRNy5), xafqLlk3kkUe(SXOLrMavuUCe(b'36\\\x0b\xdc\xbbA\xa8\xc0\x9d3\x04'), chr(100) + chr(0b1100101) + chr(99) + '\x6f' + '\144' + chr(0b1100101))(chr(0b0 + 0o165) + chr(116) + chr(0b1100110) + chr(0b11010 + 0o23) + chr(56))), jSV9IKnemH7K, copy=igThHS4jwVsa)
elif n1ufouZS6xrY(jSV9IKnemH7K):
(o52vswvoQUMc,) = (xafqLlk3kkUe(NPPHb59961Bv(xafqLlk3kkUe(SXOLrMavuUCe(b'\x10\x07\\,\xf3\xbd'), '\144' + '\x65' + chr(0b1100011) + chr(0b1001110 + 0o41) + chr(7336 - 7236) + chr(0b1100101))(chr(117) + chr(0b1110100) + chr(3144 - 3042) + '\x2d' + chr(0b1101 + 0o53)), xafqLlk3kkUe(SXOLrMavuUCe(b'\x14\tm<\xfb\xa3\x11\xf8\xed\xc0#\x07'), '\144' + chr(101) + '\143' + chr(10243 - 10132) + chr(100) + chr(0b1100101))(chr(0b1110101) + chr(0b1110100) + chr(0b1100110) + chr(0b101 + 0o50) + chr(56))), xafqLlk3kkUe(SXOLrMavuUCe(b'\x14\tm<\xfb\xa3\x11\xf8\xed\xc0#\x07'), chr(0b1100100) + chr(0b1100101) + '\143' + chr(111) + '\x64' + chr(101))('\x75' + chr(0b1100100 + 0o20) + chr(200 - 98) + chr(0b1 + 0o54) + chr(624 - 568))),)
return ohhH0MLTXIg1(xafqLlk3kkUe(o52vswvoQUMc(ZxkNvNvuRNy5), xafqLlk3kkUe(SXOLrMavuUCe(b'36\\\x0b\xdc\xbbA\xa8\xc0\x9d3\x04'), chr(0b1100100) + '\145' + chr(5887 - 5788) + chr(0b1101100 + 0o3) + '\144' + chr(101))('\165' + chr(0b1110100) + chr(0b1100110) + chr(0b101101) + chr(0b0 + 0o70))), jSV9IKnemH7K, copy=igThHS4jwVsa)
if xafqLlk3kkUe(jSV9IKnemH7K, xafqLlk3kkUe(SXOLrMavuUCe(b'!/D\x02\xc0\xb48\xf8\xcc\xca0 '), chr(0b11 + 0o141) + chr(101) + '\x63' + chr(0b1101000 + 0o7) + chr(0b10000 + 0o124) + '\x65')('\165' + chr(0b10000 + 0o144) + chr(0b111000 + 0o56) + chr(45) + chr(0b1011 + 0o55))) in (xafqLlk3kkUe(SXOLrMavuUCe(b'\x04\x07F-\xe6\xa7\x19\xf9\xbe\x98'), chr(0b1100100) + '\145' + '\143' + chr(0b1101111) + chr(0b100101 + 0o77) + '\145')('\165' + '\x74' + '\146' + chr(45) + '\070'), xafqLlk3kkUe(SXOLrMavuUCe(b'\x14\x0f_-\xf6\xab\x18\xe8\xe9\x9ac'), '\144' + '\145' + chr(0b1100011) + chr(0b100100 + 0o113) + '\x64' + '\x65')(chr(0b1110101) + chr(116) + '\146' + chr(462 - 417) + chr(0b111000))):
jtbovtaIYjRB = xafqLlk3kkUe(SXOLrMavuUCe(b"4\x0eWh\xb5\xb5\x10\xe8\xf1\xdc2\x1b\x8f'z\xe8m`\x1d\x9c\xdaG\xe1{\xe3\x9f\xd4\x02K\x90\xd5\xaa\x13\xdb\n\xf7\xc5\xa2'\xbc\x10\x07A;\xb2\xa7\x1a\xbc\xaf\xd73\x12\xd1w{\xe1O~\x0b\xe1\x95\x06\xfb5\xfe\x84\x91\x16A\xd7"), '\x64' + chr(101) + '\x63' + chr(111) + chr(0b111 + 0o135) + chr(6924 - 6823))(chr(4297 - 4180) + '\164' + chr(0b1100110) + chr(725 - 680) + chr(56))
raise q1QCh3W88sgk(xafqLlk3kkUe(jtbovtaIYjRB, xafqLlk3kkUe(SXOLrMavuUCe(b'\x06\t@%\xf3\xba'), '\144' + chr(0b1001011 + 0o32) + chr(0b1100011) + chr(3425 - 3314) + '\x64' + '\x65')(chr(0b1001101 + 0o50) + chr(116) + chr(0b110101 + 0o61) + '\x2d' + '\x38'))(dtype=xafqLlk3kkUe(jSV9IKnemH7K, xafqLlk3kkUe(SXOLrMavuUCe(b'!/D\x02\xc0\xb48\xf8\xcc\xca0 '), chr(2243 - 2143) + chr(0b1100101) + chr(706 - 607) + '\157' + chr(0b1100100) + chr(6244 - 6143))(chr(6911 - 6794) + '\x74' + chr(10112 - 10010) + chr(45) + chr(715 - 659)))))
if igThHS4jwVsa or NGkWsclKfnpq(ZxkNvNvuRNy5) or NGkWsclKfnpq(jSV9IKnemH7K):
return xafqLlk3kkUe(ZxkNvNvuRNy5, xafqLlk3kkUe(SXOLrMavuUCe(b'\x01\x15F1\xe2\xab'), '\x64' + chr(7103 - 7002) + chr(99) + chr(9245 - 9134) + chr(9448 - 9348) + '\145')(chr(117) + '\x74' + chr(102) + chr(45) + chr(3045 - 2989)))(jSV9IKnemH7K, copy=ehT0Px3KOsy9(chr(1826 - 1778) + chr(11366 - 11255) + chr(49), 8))
return xafqLlk3kkUe(ZxkNvNvuRNy5, xafqLlk3kkUe(SXOLrMavuUCe(b'\x16\x0fW?'), '\x64' + chr(563 - 462) + chr(5320 - 5221) + chr(0b1101111) + '\144' + '\x65')(chr(117) + chr(0b1110100) + chr(0b110100 + 0o62) + chr(45) + '\x38'))(jSV9IKnemH7K)
|
pandas-dev/pandas
|
pandas/core/dtypes/cast.py
|
maybe_convert_objects
|
def maybe_convert_objects(values, convert_dates=True, convert_numeric=True,
convert_timedeltas=True, copy=True):
""" if we have an object dtype, try to coerce dates and/or numbers """
# if we have passed in a list or scalar
if isinstance(values, (list, tuple)):
values = np.array(values, dtype=np.object_)
if not hasattr(values, 'dtype'):
values = np.array([values], dtype=np.object_)
# convert dates
if convert_dates and values.dtype == np.object_:
# we take an aggressive stance and convert to datetime64[ns]
if convert_dates == 'coerce':
new_values = maybe_cast_to_datetime(
values, 'M8[ns]', errors='coerce')
# if we are all nans then leave me alone
if not isna(new_values).all():
values = new_values
else:
values = lib.maybe_convert_objects(values,
convert_datetime=convert_dates)
# convert timedeltas
if convert_timedeltas and values.dtype == np.object_:
if convert_timedeltas == 'coerce':
from pandas.core.tools.timedeltas import to_timedelta
new_values = to_timedelta(values, errors='coerce')
# if we are all nans then leave me alone
if not isna(new_values).all():
values = new_values
else:
values = lib.maybe_convert_objects(
values, convert_timedelta=convert_timedeltas)
# convert to numeric
if values.dtype == np.object_:
if convert_numeric:
try:
new_values = lib.maybe_convert_numeric(values, set(),
coerce_numeric=True)
# if we are all nans then leave me alone
if not isna(new_values).all():
values = new_values
except Exception:
pass
else:
# soft-conversion
values = lib.maybe_convert_objects(values)
values = values.copy() if copy else values
return values
|
python
|
def maybe_convert_objects(values, convert_dates=True, convert_numeric=True,
convert_timedeltas=True, copy=True):
""" if we have an object dtype, try to coerce dates and/or numbers """
# if we have passed in a list or scalar
if isinstance(values, (list, tuple)):
values = np.array(values, dtype=np.object_)
if not hasattr(values, 'dtype'):
values = np.array([values], dtype=np.object_)
# convert dates
if convert_dates and values.dtype == np.object_:
# we take an aggressive stance and convert to datetime64[ns]
if convert_dates == 'coerce':
new_values = maybe_cast_to_datetime(
values, 'M8[ns]', errors='coerce')
# if we are all nans then leave me alone
if not isna(new_values).all():
values = new_values
else:
values = lib.maybe_convert_objects(values,
convert_datetime=convert_dates)
# convert timedeltas
if convert_timedeltas and values.dtype == np.object_:
if convert_timedeltas == 'coerce':
from pandas.core.tools.timedeltas import to_timedelta
new_values = to_timedelta(values, errors='coerce')
# if we are all nans then leave me alone
if not isna(new_values).all():
values = new_values
else:
values = lib.maybe_convert_objects(
values, convert_timedelta=convert_timedeltas)
# convert to numeric
if values.dtype == np.object_:
if convert_numeric:
try:
new_values = lib.maybe_convert_numeric(values, set(),
coerce_numeric=True)
# if we are all nans then leave me alone
if not isna(new_values).all():
values = new_values
except Exception:
pass
else:
# soft-conversion
values = lib.maybe_convert_objects(values)
values = values.copy() if copy else values
return values
|
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] |
if we have an object dtype, try to coerce dates and/or numbers
|
[
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] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/dtypes/cast.py#L713-L773
|
train
|
Try to coerce dates and numbers to the correct types.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(1426 - 1378) + chr(111) + '\x37', 9288 - 9280), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x32' + chr(0b110011), 0o10), ehT0Px3KOsy9('\060' + chr(0b110111 + 0o70) + chr(0b110001) + chr(0b110100) + chr(54), 0b1000), ehT0Px3KOsy9(chr(0b1011 + 0o45) + chr(111) + '\063' + chr(0b100001 + 0o20), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110011) + chr(0b100 + 0o60) + chr(0b110111), ord("\x08")), ehT0Px3KOsy9(chr(2137 - 2089) + chr(0b1101111) + '\x34' + chr(0b101100 + 0o5), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b11011 + 0o26) + chr(0b110001) + chr(51), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + '\x31' + chr(0b101110 + 0o5) + '\060', 0o10), ehT0Px3KOsy9(chr(0b101111 + 0o1) + chr(7480 - 7369) + chr(0b10110 + 0o37) + '\066', 64223 - 64215), ehT0Px3KOsy9('\x30' + '\x6f' + '\x32' + '\063' + chr(2093 - 2038), 0o10), ehT0Px3KOsy9(chr(48) + chr(8338 - 8227) + chr(0b11011 + 0o26) + chr(0b101111 + 0o10) + chr(1335 - 1284), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b101111 + 0o100) + chr(0b110011) + '\x32' + chr(54), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1000010 + 0o55) + chr(167 - 117) + '\065' + '\062', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b101101 + 0o102) + chr(0b110011) + chr(55) + '\x34', 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110011) + '\062' + chr(148 - 98), 3508 - 3500), ehT0Px3KOsy9(chr(2021 - 1973) + chr(0b1011010 + 0o25) + chr(2112 - 2063) + chr(2254 - 2204) + chr(0b110100), ord("\x08")), ehT0Px3KOsy9(chr(1008 - 960) + '\x6f' + '\065' + chr(0b10101 + 0o33), 0b1000), ehT0Px3KOsy9(chr(48) + chr(6497 - 6386) + chr(50) + '\060', 0b1000), ehT0Px3KOsy9(chr(1095 - 1047) + chr(0b110001 + 0o76) + chr(1244 - 1195) + chr(0b110101) + '\x30', 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110001) + chr(51) + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(6009 - 5898) + chr(0b11001 + 0o30) + '\064' + '\x31', 18097 - 18089), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(1917 - 1868) + chr(0b100000 + 0o24) + '\065', ord("\x08")), ehT0Px3KOsy9(chr(0b1011 + 0o45) + chr(0b1101111) + chr(1685 - 1636) + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110010) + '\x34' + chr(0b110100), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b10011 + 0o134) + chr(2292 - 2243) + '\x31' + chr(0b101 + 0o56), 8), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\067' + chr(50), 0b1000), ehT0Px3KOsy9(chr(0b110 + 0o52) + '\157' + chr(50) + chr(0b110000) + '\x36', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b111110 + 0o61) + '\x33' + '\063', 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + '\062', 0o10), ehT0Px3KOsy9(chr(1411 - 1363) + chr(10754 - 10643) + '\x31' + chr(1486 - 1432) + '\060', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\062' + chr(0b110110) + chr(1644 - 1589), 0b1000), ehT0Px3KOsy9(chr(387 - 339) + chr(6765 - 6654) + chr(0b110011), 0b1000), ehT0Px3KOsy9(chr(0b11101 + 0o23) + chr(0b1010110 + 0o31) + chr(51) + chr(158 - 107) + chr(0b110110), 0o10), ehT0Px3KOsy9(chr(0b10100 + 0o34) + chr(0b1000 + 0o147) + '\x31' + '\060' + '\062', ord("\x08")), ehT0Px3KOsy9(chr(1017 - 969) + '\x6f' + chr(0b101101 + 0o12) + chr(870 - 819), 0b1000), ehT0Px3KOsy9(chr(0b1 + 0o57) + chr(0b1010101 + 0o32) + chr(0b11 + 0o60) + '\x36' + chr(0b110100), 0b1000), ehT0Px3KOsy9('\060' + chr(0b11100 + 0o123) + '\x33' + chr(0b110101) + chr(693 - 639), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(1826 - 1777) + chr(0b110000), 0b1000), ehT0Px3KOsy9('\x30' + chr(4355 - 4244) + chr(53) + chr(948 - 895), 0o10), ehT0Px3KOsy9(chr(134 - 86) + chr(0b110001 + 0o76) + chr(0b11011 + 0o30) + chr(0b111 + 0o51) + chr(54), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + chr(2598 - 2487) + chr(0b110101) + chr(0b110000), 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b')'), chr(0b10110 + 0o116) + chr(8626 - 8525) + '\x63' + '\x6f' + chr(0b1010000 + 0o24) + chr(0b1100101))(chr(12225 - 12108) + '\x74' + chr(3244 - 3142) + chr(45) + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def LmdyYdHcjYjV(SPnCNu54H1db, JcOfGmhCIjpm=ehT0Px3KOsy9(chr(48) + chr(733 - 622) + '\061', ord("\x08")), WN1Hv0UPGMWY=ehT0Px3KOsy9('\x30' + '\157' + chr(1168 - 1119), 8), G9I7StJQU4i7=ehT0Px3KOsy9('\060' + '\157' + chr(49), 8), igThHS4jwVsa=ehT0Px3KOsy9(chr(0b110000) + chr(1032 - 921) + '\061', 8)):
if PlSM16l2KDPD(SPnCNu54H1db, (YyaZ4tpXu4lf, KNyTy8rYcwji)):
SPnCNu54H1db = WqUC3KWvYVup.array(SPnCNu54H1db, dtype=WqUC3KWvYVup.object_)
if not lot1PSoAwYhj(SPnCNu54H1db, xafqLlk3kkUe(SXOLrMavuUCe(b'cg\x1fi\x82'), chr(0b1100100) + chr(6254 - 6153) + '\143' + chr(111) + '\144' + chr(101))('\x75' + chr(0b1110100) + '\146' + '\055' + '\x38')):
SPnCNu54H1db = WqUC3KWvYVup.array([SPnCNu54H1db], dtype=WqUC3KWvYVup.object_)
if JcOfGmhCIjpm and xafqLlk3kkUe(SPnCNu54H1db, xafqLlk3kkUe(SXOLrMavuUCe(b'cg\x1fi\x82'), chr(100) + chr(0b1100101) + chr(0b1100011) + chr(111) + chr(0b101011 + 0o71) + chr(0b1001111 + 0o26))(chr(117) + '\164' + '\x66' + chr(0b101101) + '\x38')) == xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'hq\x0c|\x84U\x14'), '\x64' + chr(0b10111 + 0o116) + chr(0b1100011) + '\x6f' + chr(100) + chr(101))(chr(0b1110101) + '\164' + chr(0b1100110) + chr(0b101101) + '\x38')):
if JcOfGmhCIjpm == xafqLlk3kkUe(SXOLrMavuUCe(b'd|\x03k\x84D'), chr(100) + '\145' + chr(0b1001011 + 0o30) + chr(0b110 + 0o151) + '\144' + chr(101))(chr(0b1010000 + 0o45) + chr(0b1110100) + '\146' + chr(1815 - 1770) + chr(2574 - 2518)):
kXymhoFJ12ZA = OyAUwM2pEbUC(SPnCNu54H1db, xafqLlk3kkUe(SXOLrMavuUCe(b'J+=w\x94|'), '\x64' + chr(0b1100101) + chr(0b101001 + 0o72) + chr(4050 - 3939) + '\x64' + '\x65')('\165' + chr(116) + chr(102) + chr(1092 - 1047) + '\070'), errors=xafqLlk3kkUe(SXOLrMavuUCe(b'd|\x03k\x84D'), '\x64' + chr(0b1100101) + chr(0b1001100 + 0o27) + '\157' + '\144' + chr(0b1100101))('\165' + chr(11450 - 11334) + '\x66' + chr(45) + chr(0b100010 + 0o26)))
if not xafqLlk3kkUe(yBUx5qcFiTz6(kXymhoFJ12ZA), xafqLlk3kkUe(SXOLrMavuUCe(b'C\x7fR!\x89Kz*L\xf6I\xe5'), '\144' + chr(7195 - 7094) + '\x63' + chr(0b1001110 + 0o41) + chr(100) + '\x65')('\x75' + chr(0b1110100) + chr(0b11011 + 0o113) + chr(0b101101) + '\x38'))():
SPnCNu54H1db = kXymhoFJ12ZA
else:
SPnCNu54H1db = JiWVXlj3BjzT.maybe_convert_objects(SPnCNu54H1db, convert_datetime=JcOfGmhCIjpm)
if G9I7StJQU4i7 and xafqLlk3kkUe(SPnCNu54H1db, xafqLlk3kkUe(SXOLrMavuUCe(b'cg\x1fi\x82'), chr(2694 - 2594) + chr(0b11101 + 0o110) + '\143' + chr(0b1101111) + chr(0b10100 + 0o120) + chr(0b1100101))(chr(0b1001101 + 0o50) + chr(116) + chr(102) + chr(0b10111 + 0o26) + chr(0b111000))) == xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'hq\x0c|\x84U\x14'), chr(0b1100100) + '\x65' + chr(0b1011111 + 0o4) + chr(111) + chr(0b101101 + 0o67) + chr(0b1100101))('\x75' + chr(0b100000 + 0o124) + chr(0b1100110) + chr(0b101101) + chr(0b111000))):
if G9I7StJQU4i7 == xafqLlk3kkUe(SXOLrMavuUCe(b'd|\x03k\x84D'), '\x64' + chr(0b101100 + 0o71) + chr(6405 - 6306) + chr(0b1101111) + chr(6345 - 6245) + chr(0b101111 + 0o66))(chr(0b1010000 + 0o45) + '\x74' + '\x66' + chr(508 - 463) + chr(2466 - 2410)):
(o52vswvoQUMc,) = (xafqLlk3kkUe(xafqLlk3kkUe(xafqLlk3kkUe(xafqLlk3kkUe(NPPHb59961Bv(xafqLlk3kkUe(SXOLrMavuUCe(b"wr\x08}\x86Re;A\xed\x1e\xf8\xde\x93\xbd8[>\x1c7\x0c\x00k\xc1'N\xe7h"), '\144' + '\145' + chr(0b101000 + 0o73) + chr(6613 - 6502) + '\144' + chr(101))(chr(117) + chr(3523 - 3407) + chr(102) + '\055' + '\070'), xafqLlk3kkUe(SXOLrMavuUCe(b's|9m\x8eL.<K\xf3\x0f\xb7'), chr(100) + '\x65' + '\x63' + chr(9481 - 9370) + chr(0b1100100) + chr(0b1100101))(chr(0b1110101) + chr(0b1001100 + 0o50) + chr(0b1100110) + '\x2d' + '\070')), xafqLlk3kkUe(SXOLrMavuUCe(b'd|\x14|'), chr(100) + chr(3326 - 3225) + chr(0b1001000 + 0o33) + chr(9174 - 9063) + '\x64' + '\x65')(chr(9837 - 9720) + '\164' + '\x66' + chr(0b1010 + 0o43) + '\x38')), xafqLlk3kkUe(SXOLrMavuUCe(b's|\tu\x94'), chr(0b1100100) + chr(0b1100101) + chr(6161 - 6062) + chr(0b1101111) + chr(0b1100100) + chr(6025 - 5924))(chr(0b101000 + 0o115) + chr(116) + chr(0b1100110) + '\055' + '\x38')), xafqLlk3kkUe(SXOLrMavuUCe(b"sz\x0b|\x83D',O\xec"), chr(0b1011000 + 0o14) + '\x65' + chr(5331 - 5232) + chr(1422 - 1311) + chr(0b1100100) + chr(3801 - 3700))(chr(3416 - 3299) + chr(0b1110100) + '\146' + chr(45) + chr(781 - 725))), xafqLlk3kkUe(SXOLrMavuUCe(b's|9m\x8eL.<K\xf3\x0f\xb7'), chr(0b100101 + 0o77) + chr(0b1100101) + chr(99) + chr(111) + chr(0b100 + 0o140) + chr(0b100000 + 0o105))('\x75' + chr(154 - 38) + '\x66' + '\x2d' + chr(56))),)
kXymhoFJ12ZA = o52vswvoQUMc(SPnCNu54H1db, errors=xafqLlk3kkUe(SXOLrMavuUCe(b'd|\x03k\x84D'), chr(0b100101 + 0o77) + '\x65' + chr(4327 - 4228) + chr(0b111011 + 0o64) + '\144' + chr(101))('\165' + '\x74' + chr(0b1100010 + 0o4) + chr(0b101101) + chr(202 - 146)))
if not xafqLlk3kkUe(yBUx5qcFiTz6(kXymhoFJ12ZA), xafqLlk3kkUe(SXOLrMavuUCe(b'C\x7fR!\x89Kz*L\xf6I\xe5'), '\144' + chr(0b1100101) + '\143' + chr(10980 - 10869) + '\x64' + chr(0b110 + 0o137))(chr(5529 - 5412) + '\164' + chr(0b100110 + 0o100) + '\055' + '\x38'))():
SPnCNu54H1db = kXymhoFJ12ZA
else:
SPnCNu54H1db = JiWVXlj3BjzT.maybe_convert_objects(SPnCNu54H1db, convert_timedelta=G9I7StJQU4i7)
if xafqLlk3kkUe(SPnCNu54H1db, xafqLlk3kkUe(SXOLrMavuUCe(b'cg\x1fi\x82'), chr(7819 - 7719) + chr(9106 - 9005) + '\143' + chr(5185 - 5074) + chr(0b1100100) + chr(0b1000010 + 0o43))(chr(5891 - 5774) + chr(116) + '\146' + chr(679 - 634) + '\x38')) == xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'hq\x0c|\x84U\x14'), chr(0b1001010 + 0o32) + '\x65' + chr(0b1001100 + 0o27) + chr(268 - 157) + '\x64' + '\x65')(chr(9393 - 9276) + chr(6724 - 6608) + chr(7911 - 7809) + chr(405 - 360) + chr(56))):
if WN1Hv0UPGMWY:
try:
kXymhoFJ12ZA = JiWVXlj3BjzT.maybe_convert_numeric(SPnCNu54H1db, MVEN8G6CxlvR(), coerce_numeric=ehT0Px3KOsy9('\060' + chr(111) + '\x31', 8))
if not xafqLlk3kkUe(yBUx5qcFiTz6(kXymhoFJ12ZA), xafqLlk3kkUe(SXOLrMavuUCe(b'C\x7fR!\x89Kz*L\xf6I\xe5'), chr(0b1100100) + chr(0b1100101) + chr(0b1000001 + 0o42) + chr(0b1011010 + 0o25) + chr(8167 - 8067) + chr(101))(chr(0b111101 + 0o70) + chr(0b1010100 + 0o40) + '\x66' + chr(45) + chr(56)))():
SPnCNu54H1db = kXymhoFJ12ZA
except jLmadlzMdunT:
pass
else:
SPnCNu54H1db = JiWVXlj3BjzT.maybe_convert_objects(SPnCNu54H1db)
SPnCNu54H1db = SPnCNu54H1db.igThHS4jwVsa() if igThHS4jwVsa else SPnCNu54H1db
return SPnCNu54H1db
|
pandas-dev/pandas
|
pandas/core/dtypes/cast.py
|
soft_convert_objects
|
def soft_convert_objects(values, datetime=True, numeric=True, timedelta=True,
coerce=False, copy=True):
""" if we have an object dtype, try to coerce dates and/or numbers """
conversion_count = sum((datetime, numeric, timedelta))
if conversion_count == 0:
raise ValueError('At least one of datetime, numeric or timedelta must '
'be True.')
elif conversion_count > 1 and coerce:
raise ValueError("Only one of 'datetime', 'numeric' or "
"'timedelta' can be True when when coerce=True.")
if isinstance(values, (list, tuple)):
# List or scalar
values = np.array(values, dtype=np.object_)
elif not hasattr(values, 'dtype'):
values = np.array([values], dtype=np.object_)
elif not is_object_dtype(values.dtype):
# If not object, do not attempt conversion
values = values.copy() if copy else values
return values
# If 1 flag is coerce, ensure 2 others are False
if coerce:
# Immediate return if coerce
if datetime:
from pandas import to_datetime
return to_datetime(values, errors='coerce').to_numpy()
elif timedelta:
from pandas import to_timedelta
return to_timedelta(values, errors='coerce').to_numpy()
elif numeric:
from pandas import to_numeric
return to_numeric(values, errors='coerce')
# Soft conversions
if datetime:
# GH 20380, when datetime is beyond year 2262, hence outside
# bound of nanosecond-resolution 64-bit integers.
try:
values = lib.maybe_convert_objects(values,
convert_datetime=datetime)
except OutOfBoundsDatetime:
pass
if timedelta and is_object_dtype(values.dtype):
# Object check to ensure only run if previous did not convert
values = lib.maybe_convert_objects(values, convert_timedelta=timedelta)
if numeric and is_object_dtype(values.dtype):
try:
converted = lib.maybe_convert_numeric(values, set(),
coerce_numeric=True)
# If all NaNs, then do not-alter
values = converted if not isna(converted).all() else values
values = values.copy() if copy else values
except Exception:
pass
return values
|
python
|
def soft_convert_objects(values, datetime=True, numeric=True, timedelta=True,
coerce=False, copy=True):
""" if we have an object dtype, try to coerce dates and/or numbers """
conversion_count = sum((datetime, numeric, timedelta))
if conversion_count == 0:
raise ValueError('At least one of datetime, numeric or timedelta must '
'be True.')
elif conversion_count > 1 and coerce:
raise ValueError("Only one of 'datetime', 'numeric' or "
"'timedelta' can be True when when coerce=True.")
if isinstance(values, (list, tuple)):
# List or scalar
values = np.array(values, dtype=np.object_)
elif not hasattr(values, 'dtype'):
values = np.array([values], dtype=np.object_)
elif not is_object_dtype(values.dtype):
# If not object, do not attempt conversion
values = values.copy() if copy else values
return values
# If 1 flag is coerce, ensure 2 others are False
if coerce:
# Immediate return if coerce
if datetime:
from pandas import to_datetime
return to_datetime(values, errors='coerce').to_numpy()
elif timedelta:
from pandas import to_timedelta
return to_timedelta(values, errors='coerce').to_numpy()
elif numeric:
from pandas import to_numeric
return to_numeric(values, errors='coerce')
# Soft conversions
if datetime:
# GH 20380, when datetime is beyond year 2262, hence outside
# bound of nanosecond-resolution 64-bit integers.
try:
values = lib.maybe_convert_objects(values,
convert_datetime=datetime)
except OutOfBoundsDatetime:
pass
if timedelta and is_object_dtype(values.dtype):
# Object check to ensure only run if previous did not convert
values = lib.maybe_convert_objects(values, convert_timedelta=timedelta)
if numeric and is_object_dtype(values.dtype):
try:
converted = lib.maybe_convert_numeric(values, set(),
coerce_numeric=True)
# If all NaNs, then do not-alter
values = converted if not isna(converted).all() else values
values = values.copy() if copy else values
except Exception:
pass
return values
|
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] |
if we have an object dtype, try to coerce dates and/or numbers
|
[
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] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/dtypes/cast.py#L776-L835
|
train
|
Convert a list of objects into a single object.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b110000) + chr(5876 - 5765) + '\x32' + '\063', 0o10), ehT0Px3KOsy9('\060' + chr(9465 - 9354) + chr(2497 - 2446) + chr(0b110011) + chr(49), ord("\x08")), ehT0Px3KOsy9('\060' + chr(11153 - 11042) + chr(1337 - 1286) + chr(0b1111 + 0o50) + chr(0b110 + 0o61), 34789 - 34781), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(1013 - 963) + chr(0b100010 + 0o20) + '\x36', 41908 - 41900), ehT0Px3KOsy9(chr(1840 - 1792) + chr(8321 - 8210) + chr(2201 - 2150) + chr(0b110111) + chr(0b100010 + 0o25), 8), ehT0Px3KOsy9(chr(97 - 49) + chr(9738 - 9627) + chr(1654 - 1604) + chr(2175 - 2120), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(1845 - 1794) + chr(2101 - 2051) + '\x34', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b100001 + 0o22) + chr(112 - 57) + chr(50), 0b1000), ehT0Px3KOsy9(chr(0b100110 + 0o12) + '\157' + chr(0b101101 + 0o7) + chr(52), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1000111 + 0o50) + chr(0b101101 + 0o5) + chr(0b110110) + chr(53), ord("\x08")), ehT0Px3KOsy9(chr(2185 - 2137) + chr(0b1101111) + '\x33' + '\x36' + chr(49), 11353 - 11345), ehT0Px3KOsy9(chr(0b10110 + 0o32) + '\x6f' + chr(882 - 831) + chr(1414 - 1361) + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(0b111 + 0o51) + chr(0b1101111) + '\063' + '\x36' + '\x36', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b11000 + 0o34) + chr(0b110011), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b1010 + 0o47) + '\x35' + chr(0b110011), 37239 - 37231), ehT0Px3KOsy9('\060' + chr(111) + chr(2191 - 2136) + '\x31', ord("\x08")), ehT0Px3KOsy9(chr(1299 - 1251) + chr(1424 - 1313) + '\063' + chr(0b11101 + 0o32) + chr(2923 - 2868), 8), ehT0Px3KOsy9(chr(890 - 842) + '\x6f' + chr(2359 - 2307) + chr(2140 - 2089), 8), ehT0Px3KOsy9(chr(48) + chr(6583 - 6472) + '\062' + chr(2322 - 2267) + chr(0b10011 + 0o44), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110011) + chr(50) + chr(0b10 + 0o60), 28257 - 28249), ehT0Px3KOsy9('\x30' + chr(111) + chr(50) + chr(0b100011 + 0o15) + chr(0b110110), 0o10), ehT0Px3KOsy9('\x30' + '\157' + '\061' + chr(1620 - 1572) + chr(975 - 927), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110001) + '\x32' + chr(556 - 505), 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(988 - 938) + chr(0b110111) + '\062', ord("\x08")), ehT0Px3KOsy9(chr(2278 - 2230) + chr(7797 - 7686) + '\061' + chr(48) + chr(637 - 583), ord("\x08")), ehT0Px3KOsy9(chr(0b1 + 0o57) + chr(0b1100100 + 0o13) + '\063' + '\x32' + chr(0b110101), 37865 - 37857), ehT0Px3KOsy9('\060' + '\x6f' + chr(50) + chr(0b110011) + '\x31', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b100010 + 0o20) + chr(54) + chr(567 - 516), 4103 - 4095), ehT0Px3KOsy9(chr(938 - 890) + '\x6f' + '\062' + '\066' + chr(0b10110 + 0o36), 20015 - 20007), ehT0Px3KOsy9(chr(1822 - 1774) + chr(111) + chr(0b110001) + chr(506 - 455) + chr(2842 - 2788), 43792 - 43784), ehT0Px3KOsy9('\x30' + chr(4261 - 4150) + chr(1166 - 1115) + chr(55) + '\067', 8), ehT0Px3KOsy9(chr(48) + chr(111) + '\066' + '\x35', 17962 - 17954), ehT0Px3KOsy9(chr(1102 - 1054) + chr(111) + chr(0b101110 + 0o5) + chr(53) + chr(49), 0o10), ehT0Px3KOsy9(chr(1122 - 1074) + '\157' + '\x33' + chr(2390 - 2337) + chr(0b110100), 8), ehT0Px3KOsy9(chr(2057 - 2009) + '\157' + chr(0b100011 + 0o20) + chr(51) + '\x33', 51492 - 51484), ehT0Px3KOsy9('\060' + chr(111) + chr(1853 - 1804) + '\x33' + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(1936 - 1888) + '\x6f' + chr(51) + chr(144 - 96) + chr(0b10000 + 0o41), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + '\x31' + chr(0b101101 + 0o10), ord("\x08")), ehT0Px3KOsy9(chr(2074 - 2026) + '\x6f' + chr(0b110001) + chr(0b110011 + 0o2), 8), ehT0Px3KOsy9('\060' + '\157' + chr(49) + chr(55) + chr(52), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + '\157' + chr(53) + '\060', 52929 - 52921)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'='), chr(9929 - 9829) + '\145' + chr(99) + chr(0b10 + 0o155) + chr(9897 - 9797) + chr(0b10 + 0o143))(chr(0b1000011 + 0o62) + chr(0b1101000 + 0o14) + chr(0b1100110) + chr(0b101101) + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def YE6aYwH5E6Rt(SPnCNu54H1db, zKdiQFzuryNR=ehT0Px3KOsy9(chr(0b10 + 0o56) + '\157' + chr(2019 - 1970), 0o10), carEtu1CAKcf=ehT0Px3KOsy9('\x30' + '\157' + '\x31', 8), UYrFWngYaD_b=ehT0Px3KOsy9('\060' + chr(0b1010000 + 0o37) + chr(966 - 917), 8), t5Z6okQoi2Br=ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b100001 + 0o17), 12415 - 12407), igThHS4jwVsa=ehT0Px3KOsy9('\x30' + chr(0b11001 + 0o126) + chr(0b110001), 8)):
vlyBGWpiRMbp = xkxBmo49x2An((zKdiQFzuryNR, carEtu1CAKcf, UYrFWngYaD_b))
if vlyBGWpiRMbp == ehT0Px3KOsy9('\060' + chr(9069 - 8958) + '\x30', 8):
raise q1QCh3W88sgk(xafqLlk3kkUe(SXOLrMavuUCe(b'R\xad\xdf\xfa\x9av\xa7\x8e\x04\xda\x9f\x89\xd6L\r\x19\x9bB\xcb\xb7\xf2)>\xdfj\xf5\xf7\xc6\xd9;\x8d\\\x8a\xcc\xb4.\xe1yd\x11v\xbd\x9a\xfa\x8bv\xf4\x97Q\xc6\x85\xcc\x94FKm\x8dV\xda\xfc'), chr(0b1100100) + '\145' + '\143' + chr(0b1101111) + '\144' + chr(7295 - 7194))(chr(0b1110101) + '\164' + chr(4993 - 4891) + chr(45) + chr(56)))
elif vlyBGWpiRMbp > ehT0Px3KOsy9(chr(0b101100 + 0o4) + chr(0b1101111) + chr(508 - 459), 8) and t5Z6okQoi2Br:
raise q1QCh3W88sgk(xafqLlk3kkUe(SXOLrMavuUCe(b'\\\xb7\x93\xef\xdfx\xba\x9f\x04\xda\x97\xcc\xd1G\nM\x9aW\xd6\xbf\xe3g\x7f\x9aa\xbb\xec\xde\xd1,\x96V\xce\xcc\xb4.\xe1*y\x15~\xbc\x9b\xf3\x93c\xb5\xdd\x04\xd6\x90\x82\xd6A\x0e\x19\xabQ\xca\xb7\xa67;\xdf(\xf5\xee\xdb\xd10\xdfV\x86\x89\xa9?\xa40Y\x0ef\xbc\xd1'), chr(100) + chr(0b1100101) + '\143' + '\x6f' + '\x64' + chr(0b10110 + 0o117))(chr(117) + chr(12234 - 12118) + chr(8849 - 8747) + '\x2d' + chr(56)))
if PlSM16l2KDPD(SPnCNu54H1db, (YyaZ4tpXu4lf, KNyTy8rYcwji)):
SPnCNu54H1db = WqUC3KWvYVup.array(SPnCNu54H1db, dtype=WqUC3KWvYVup.object_)
elif not lot1PSoAwYhj(SPnCNu54H1db, xafqLlk3kkUe(SXOLrMavuUCe(b'w\xad\x86\xe6\x9a'), chr(0b100101 + 0o77) + chr(5145 - 5044) + chr(0b1010010 + 0o21) + chr(9132 - 9021) + chr(0b1100100) + '\145')(chr(3633 - 3516) + chr(0b1110100) + '\146' + chr(45) + chr(0b110110 + 0o2))):
SPnCNu54H1db = WqUC3KWvYVup.array([SPnCNu54H1db], dtype=WqUC3KWvYVup.object_)
elif not NGkWsclKfnpq(xafqLlk3kkUe(SPnCNu54H1db, xafqLlk3kkUe(SXOLrMavuUCe(b'w\xad\x86\xe6\x9a'), chr(100) + '\x65' + chr(0b1010001 + 0o22) + '\x6f' + chr(0b1000110 + 0o36) + chr(0b1010011 + 0o22))(chr(0b101 + 0o160) + chr(2677 - 2561) + chr(102) + chr(1296 - 1251) + '\x38'))):
SPnCNu54H1db = SPnCNu54H1db.igThHS4jwVsa() if igThHS4jwVsa else SPnCNu54H1db
return SPnCNu54H1db
if t5Z6okQoi2Br:
if zKdiQFzuryNR:
(IF08dLE993_s,) = (xafqLlk3kkUe(NPPHb59961Bv(xafqLlk3kkUe(SXOLrMavuUCe(b'c\xb8\x91\xf2\x9ed'), chr(100) + chr(7701 - 7600) + '\x63' + '\157' + chr(100) + chr(101))('\165' + '\164' + chr(102) + '\x2d' + '\070'), xafqLlk3kkUe(SXOLrMavuUCe(b'g\xb6\xa0\xf2\x9ec\xb1\x8eM\xd8\x94'), '\144' + '\145' + '\x63' + chr(8536 - 8425) + '\144' + '\x65')(chr(0b1110101) + chr(0b101001 + 0o113) + chr(2136 - 2034) + chr(0b101101) + chr(0b111000))), xafqLlk3kkUe(SXOLrMavuUCe(b'g\xb6\xa0\xf2\x9ec\xb1\x8eM\xd8\x94'), chr(0b1011011 + 0o11) + chr(0b110010 + 0o63) + chr(0b1100011) + '\157' + chr(100) + chr(0b111001 + 0o54))('\x75' + chr(116) + chr(5389 - 5287) + chr(45) + chr(0b111000))),)
return xafqLlk3kkUe(IF08dLE993_s(SPnCNu54H1db, errors=xafqLlk3kkUe(SXOLrMavuUCe(b'p\xb6\x9a\xe4\x9cr'), '\144' + chr(0b1001111 + 0o26) + chr(0b1100011) + chr(0b1101111) + chr(100) + '\x65')('\x75' + chr(116) + chr(0b1100110) + '\055' + chr(0b111 + 0o61))), xafqLlk3kkUe(SXOLrMavuUCe(b'g\xb6\xa0\xf8\x8az\xa4\x83'), chr(9890 - 9790) + chr(2814 - 2713) + '\143' + '\157' + '\144' + chr(101))(chr(0b10111 + 0o136) + '\x74' + '\146' + '\x2d' + chr(0b100000 + 0o30)))()
elif UYrFWngYaD_b:
(o52vswvoQUMc,) = (xafqLlk3kkUe(NPPHb59961Bv(xafqLlk3kkUe(SXOLrMavuUCe(b'c\xb8\x91\xf2\x9ed'), chr(100) + '\x65' + chr(99) + chr(4931 - 4820) + chr(1189 - 1089) + chr(0b1100101))(chr(0b1110101) + chr(1753 - 1637) + chr(0b1101 + 0o131) + '\055' + chr(56)), xafqLlk3kkUe(SXOLrMavuUCe(b'g\xb6\xa0\xe2\x96z\xb1\x9eA\xd9\x85\x8d'), chr(100) + '\145' + '\x63' + chr(111) + '\144' + '\x65')(chr(7784 - 7667) + '\x74' + chr(0b1100110) + chr(45) + chr(56))), xafqLlk3kkUe(SXOLrMavuUCe(b'g\xb6\xa0\xe2\x96z\xb1\x9eA\xd9\x85\x8d'), chr(6862 - 6762) + '\x65' + '\143' + chr(0b1011111 + 0o20) + chr(0b1100100) + chr(101))(chr(8280 - 8163) + '\164' + '\x66' + chr(0b10000 + 0o35) + '\070')),)
return xafqLlk3kkUe(o52vswvoQUMc(SPnCNu54H1db, errors=xafqLlk3kkUe(SXOLrMavuUCe(b'p\xb6\x9a\xe4\x9cr'), chr(100) + chr(0b1010101 + 0o20) + chr(0b1000011 + 0o40) + chr(0b1101111) + '\x64' + '\x65')(chr(8546 - 8429) + chr(0b101001 + 0o113) + chr(9053 - 8951) + chr(0b10100 + 0o31) + chr(0b111000))), xafqLlk3kkUe(SXOLrMavuUCe(b'g\xb6\xa0\xf8\x8az\xa4\x83'), chr(0b1100100) + chr(0b1100101) + chr(0b1100011) + chr(0b111001 + 0o66) + chr(100) + '\145')(chr(0b101111 + 0o106) + chr(0b110011 + 0o101) + chr(0b1010010 + 0o24) + chr(1490 - 1445) + chr(0b111000)))()
elif carEtu1CAKcf:
(D3UiWg6YVSO0,) = (xafqLlk3kkUe(NPPHb59961Bv(xafqLlk3kkUe(SXOLrMavuUCe(b'c\xb8\x91\xf2\x9ed'), chr(0b1110 + 0o126) + chr(6287 - 6186) + chr(99) + '\157' + chr(100) + chr(101))(chr(11716 - 11599) + '\164' + chr(5556 - 5454) + chr(962 - 917) + '\070'), xafqLlk3kkUe(SXOLrMavuUCe(b'g\xb6\xa0\xf8\x8az\xb1\x88M\xd6'), '\144' + '\145' + chr(0b110111 + 0o54) + chr(4796 - 4685) + chr(0b1100100) + chr(0b100000 + 0o105))(chr(0b1110101) + '\x74' + chr(0b1100110) + chr(0b101101 + 0o0) + '\x38')), xafqLlk3kkUe(SXOLrMavuUCe(b'g\xb6\xa0\xf8\x8az\xb1\x88M\xd6'), chr(8629 - 8529) + chr(0b1100101) + chr(0b1100011) + '\157' + chr(0b1001001 + 0o33) + chr(0b1100101))(chr(0b1110100 + 0o1) + chr(116) + chr(0b1100110) + chr(0b101101) + chr(420 - 364))),)
return D3UiWg6YVSO0(SPnCNu54H1db, errors=xafqLlk3kkUe(SXOLrMavuUCe(b'p\xb6\x9a\xe4\x9cr'), '\x64' + chr(0b1100101) + chr(6016 - 5917) + '\x6f' + chr(4363 - 4263) + chr(8393 - 8292))('\x75' + chr(0b1110100) + '\x66' + '\x2d' + '\x38'))
if zKdiQFzuryNR:
try:
SPnCNu54H1db = JiWVXlj3BjzT.maybe_convert_objects(SPnCNu54H1db, convert_datetime=zKdiQFzuryNR)
except ihnyQ_QFyBaj:
pass
if UYrFWngYaD_b and NGkWsclKfnpq(xafqLlk3kkUe(SPnCNu54H1db, xafqLlk3kkUe(SXOLrMavuUCe(b'w\xad\x86\xe6\x9a'), chr(0b110101 + 0o57) + '\x65' + chr(0b111 + 0o134) + chr(409 - 298) + '\144' + '\x65')(chr(0b1010000 + 0o45) + chr(0b1110100) + chr(0b111101 + 0o51) + chr(940 - 895) + chr(56)))):
SPnCNu54H1db = JiWVXlj3BjzT.maybe_convert_objects(SPnCNu54H1db, convert_timedelta=UYrFWngYaD_b)
if carEtu1CAKcf and NGkWsclKfnpq(xafqLlk3kkUe(SPnCNu54H1db, xafqLlk3kkUe(SXOLrMavuUCe(b'w\xad\x86\xe6\x9a'), chr(0b11100 + 0o110) + chr(0b1100101) + chr(99) + '\157' + '\144' + chr(5043 - 4942))('\x75' + '\x74' + chr(0b1100110) + chr(0b101011 + 0o2) + '\070'))):
try:
ekolk5wRLA_R = JiWVXlj3BjzT.maybe_convert_numeric(SPnCNu54H1db, MVEN8G6CxlvR(), coerce_numeric=ehT0Px3KOsy9(chr(357 - 309) + chr(0b1101111) + chr(0b11100 + 0o25), 8))
SPnCNu54H1db = ekolk5wRLA_R if not yBUx5qcFiTz6(ekolk5wRLA_R).Dl48nj1rbi23() else SPnCNu54H1db
SPnCNu54H1db = SPnCNu54H1db.igThHS4jwVsa() if igThHS4jwVsa else SPnCNu54H1db
except jLmadlzMdunT:
pass
return SPnCNu54H1db
|
pandas-dev/pandas
|
pandas/core/dtypes/cast.py
|
maybe_infer_to_datetimelike
|
def maybe_infer_to_datetimelike(value, convert_dates=False):
"""
we might have a array (or single object) that is datetime like,
and no dtype is passed don't change the value unless we find a
datetime/timedelta set
this is pretty strict in that a datetime/timedelta is REQUIRED
in addition to possible nulls/string likes
Parameters
----------
value : np.array / Series / Index / list-like
convert_dates : boolean, default False
if True try really hard to convert dates (such as datetime.date), other
leave inferred dtype 'date' alone
"""
# TODO: why not timedelta?
if isinstance(value, (ABCDatetimeIndex, ABCPeriodIndex,
ABCDatetimeArray, ABCPeriodArray)):
return value
elif isinstance(value, ABCSeries):
if isinstance(value._values, ABCDatetimeIndex):
return value._values
v = value
if not is_list_like(v):
v = [v]
v = np.array(v, copy=False)
# we only care about object dtypes
if not is_object_dtype(v):
return value
shape = v.shape
if not v.ndim == 1:
v = v.ravel()
if not len(v):
return value
def try_datetime(v):
# safe coerce to datetime64
try:
# GH19671
v = tslib.array_to_datetime(v,
require_iso8601=True,
errors='raise')[0]
except ValueError:
# we might have a sequence of the same-datetimes with tz's
# if so coerce to a DatetimeIndex; if they are not the same,
# then these stay as object dtype, xref GH19671
try:
from pandas._libs.tslibs import conversion
from pandas import DatetimeIndex
values, tz = conversion.datetime_to_datetime64(v)
return DatetimeIndex(values).tz_localize(
'UTC').tz_convert(tz=tz)
except (ValueError, TypeError):
pass
except Exception:
pass
return v.reshape(shape)
def try_timedelta(v):
# safe coerce to timedelta64
# will try first with a string & object conversion
from pandas import to_timedelta
try:
return to_timedelta(v)._ndarray_values.reshape(shape)
except Exception:
return v.reshape(shape)
inferred_type = lib.infer_datetimelike_array(ensure_object(v))
if inferred_type == 'date' and convert_dates:
value = try_datetime(v)
elif inferred_type == 'datetime':
value = try_datetime(v)
elif inferred_type == 'timedelta':
value = try_timedelta(v)
elif inferred_type == 'nat':
# if all NaT, return as datetime
if isna(v).all():
value = try_datetime(v)
else:
# We have at least a NaT and a string
# try timedelta first to avoid spurious datetime conversions
# e.g. '00:00:01' is a timedelta but technically is also a datetime
value = try_timedelta(v)
if lib.infer_dtype(value, skipna=False) in ['mixed']:
# cannot skip missing values, as NaT implies that the string
# is actually a datetime
value = try_datetime(v)
return value
|
python
|
def maybe_infer_to_datetimelike(value, convert_dates=False):
"""
we might have a array (or single object) that is datetime like,
and no dtype is passed don't change the value unless we find a
datetime/timedelta set
this is pretty strict in that a datetime/timedelta is REQUIRED
in addition to possible nulls/string likes
Parameters
----------
value : np.array / Series / Index / list-like
convert_dates : boolean, default False
if True try really hard to convert dates (such as datetime.date), other
leave inferred dtype 'date' alone
"""
# TODO: why not timedelta?
if isinstance(value, (ABCDatetimeIndex, ABCPeriodIndex,
ABCDatetimeArray, ABCPeriodArray)):
return value
elif isinstance(value, ABCSeries):
if isinstance(value._values, ABCDatetimeIndex):
return value._values
v = value
if not is_list_like(v):
v = [v]
v = np.array(v, copy=False)
# we only care about object dtypes
if not is_object_dtype(v):
return value
shape = v.shape
if not v.ndim == 1:
v = v.ravel()
if not len(v):
return value
def try_datetime(v):
# safe coerce to datetime64
try:
# GH19671
v = tslib.array_to_datetime(v,
require_iso8601=True,
errors='raise')[0]
except ValueError:
# we might have a sequence of the same-datetimes with tz's
# if so coerce to a DatetimeIndex; if they are not the same,
# then these stay as object dtype, xref GH19671
try:
from pandas._libs.tslibs import conversion
from pandas import DatetimeIndex
values, tz = conversion.datetime_to_datetime64(v)
return DatetimeIndex(values).tz_localize(
'UTC').tz_convert(tz=tz)
except (ValueError, TypeError):
pass
except Exception:
pass
return v.reshape(shape)
def try_timedelta(v):
# safe coerce to timedelta64
# will try first with a string & object conversion
from pandas import to_timedelta
try:
return to_timedelta(v)._ndarray_values.reshape(shape)
except Exception:
return v.reshape(shape)
inferred_type = lib.infer_datetimelike_array(ensure_object(v))
if inferred_type == 'date' and convert_dates:
value = try_datetime(v)
elif inferred_type == 'datetime':
value = try_datetime(v)
elif inferred_type == 'timedelta':
value = try_timedelta(v)
elif inferred_type == 'nat':
# if all NaT, return as datetime
if isna(v).all():
value = try_datetime(v)
else:
# We have at least a NaT and a string
# try timedelta first to avoid spurious datetime conversions
# e.g. '00:00:01' is a timedelta but technically is also a datetime
value = try_timedelta(v)
if lib.infer_dtype(value, skipna=False) in ['mixed']:
# cannot skip missing values, as NaT implies that the string
# is actually a datetime
value = try_datetime(v)
return value
|
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we might have a array (or single object) that is datetime like,
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this is pretty strict in that a datetime/timedelta is REQUIRED
in addition to possible nulls/string likes
Parameters
----------
value : np.array / Series / Index / list-like
convert_dates : boolean, default False
if True try really hard to convert dates (such as datetime.date), other
leave inferred dtype 'date' alone
|
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] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/dtypes/cast.py#L852-L956
|
train
|
Try to infer the value of a node from a datetime - like object.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\063' + chr(2684 - 2629) + chr(0b110100), 0o10), ehT0Px3KOsy9(chr(267 - 219) + chr(0b1101111) + chr(1456 - 1407) + chr(0b110000) + chr(1628 - 1575), 0o10), ehT0Px3KOsy9(chr(0b10001 + 0o37) + chr(0b1101111) + chr(54) + '\064', 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b1110 + 0o44) + '\064', 0o10), ehT0Px3KOsy9(chr(0b1101 + 0o43) + chr(111) + chr(0b100010 + 0o20) + chr(51) + chr(49), 5036 - 5028), ehT0Px3KOsy9(chr(1390 - 1342) + chr(0b1101010 + 0o5) + '\063' + chr(2318 - 2266) + chr(0b110101 + 0o0), 0b1000), ehT0Px3KOsy9('\060' + chr(0b101 + 0o152) + '\x31' + '\063' + chr(53), 57920 - 57912), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(2073 - 2022) + '\x31' + chr(2151 - 2101), 24558 - 24550), ehT0Px3KOsy9(chr(0b0 + 0o60) + '\157' + '\065' + chr(0b110100), 30112 - 30104), ehT0Px3KOsy9('\060' + chr(11385 - 11274) + chr(98 - 47) + '\062' + chr(2342 - 2292), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(0b1000 + 0o53) + '\x30' + chr(717 - 664), 33992 - 33984), ehT0Px3KOsy9('\060' + chr(111) + '\x31' + '\067' + chr(0b10011 + 0o44), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(51) + '\065' + chr(50), 0b1000), ehT0Px3KOsy9(chr(48) + chr(1149 - 1038) + '\x32' + chr(49) + chr(55), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\063' + chr(52) + chr(51), 0o10), ehT0Px3KOsy9(chr(1629 - 1581) + chr(111) + chr(49) + chr(0b110110) + chr(1259 - 1208), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1011011 + 0o24) + chr(0b110010) + chr(0b110010 + 0o3) + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1011001 + 0o26) + chr(50) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + '\x32' + '\x36' + chr(0b110111), 59202 - 59194), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b100 + 0o57) + chr(54) + chr(51), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110110) + chr(55), 0b1000), ehT0Px3KOsy9('\x30' + chr(5508 - 5397) + chr(0b110010), 63659 - 63651), ehT0Px3KOsy9(chr(740 - 692) + chr(0b1001101 + 0o42) + '\062' + chr(51) + chr(80 - 27), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1001011 + 0o44) + chr(49) + chr(50) + chr(50), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(51) + chr(49), 0b1000), ehT0Px3KOsy9('\x30' + chr(10807 - 10696) + chr(0b100 + 0o56) + chr(0b110001), 0b1000), ehT0Px3KOsy9(chr(1391 - 1343) + chr(0b1000 + 0o147) + chr(0b100011 + 0o16) + chr(2057 - 2009) + chr(49), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(4937 - 4826) + '\067' + chr(0b110011), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\063' + chr(0b10111 + 0o33), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b10011 + 0o134) + chr(2259 - 2210) + chr(54) + chr(0b110001), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x32' + chr(0b110010) + chr(0b110110), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111 + 0o0) + chr(51) + chr(0b110000) + chr(2025 - 1975), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101 + 0o142) + chr(623 - 572) + chr(0b110100), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x35' + '\x37', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(931 - 881) + chr(0b10100 + 0o34) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110111) + '\063', 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b111111 + 0o60) + chr(50) + chr(681 - 628) + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(4871 - 4760) + chr(0b110001) + chr(126 - 74) + chr(0b11100 + 0o33), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\061' + chr(1707 - 1652) + chr(810 - 761), 0b1000), ehT0Px3KOsy9(chr(1207 - 1159) + '\x6f' + chr(50) + chr(0b100000 + 0o20) + chr(50), 8)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(1657 - 1609) + chr(0b1010011 + 0o34) + '\065' + '\060', ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xd2'), chr(0b1100100) + chr(101) + chr(9520 - 9421) + '\157' + '\144' + chr(0b1100101))(chr(117) + '\x74' + chr(0b1100110) + chr(45) + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def Y5DUCg1pxiDF(QmmgWUB13VCJ, JcOfGmhCIjpm=ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\060', 0b1000)):
if PlSM16l2KDPD(QmmgWUB13VCJ, (YZ5LDy5fOv72, FsR2PdYNld4H, LDvXXFwOdOvg, uO8SSrhjUClc)):
return QmmgWUB13VCJ
elif PlSM16l2KDPD(QmmgWUB13VCJ, essMXh4s9f1w):
if PlSM16l2KDPD(xafqLlk3kkUe(QmmgWUB13VCJ, xafqLlk3kkUe(SXOLrMavuUCe(b'\xa33Ux\xec\x80.'), chr(0b1100100) + chr(101) + '\143' + chr(0b1101111) + chr(100) + chr(0b101110 + 0o67))(chr(0b1110101) + chr(0b1001111 + 0o45) + '\x66' + chr(45) + '\070')), YZ5LDy5fOv72):
return xafqLlk3kkUe(QmmgWUB13VCJ, xafqLlk3kkUe(SXOLrMavuUCe(b'\xa33Ux\xec\x80.'), chr(100) + chr(0b1100101) + '\143' + chr(0b1101111) + chr(4210 - 4110) + '\x65')(chr(7169 - 7052) + '\x74' + chr(0b1100110) + chr(0b101101) + chr(2956 - 2900)))
cMbll0QYhULo = QmmgWUB13VCJ
if not bAgBF7jXI53B(cMbll0QYhULo):
cMbll0QYhULo = [cMbll0QYhULo]
cMbll0QYhULo = WqUC3KWvYVup.array(cMbll0QYhULo, copy=ehT0Px3KOsy9(chr(1661 - 1613) + '\x6f' + chr(0b110000), 8))
if not NGkWsclKfnpq(cMbll0QYhULo):
return QmmgWUB13VCJ
nauYfLglTpcb = cMbll0QYhULo.shape
if not xafqLlk3kkUe(cMbll0QYhULo, xafqLlk3kkUe(SXOLrMavuUCe(b'\x9b*Yd\xd1\xa74\x9e_\xb4\x8f+'), '\x64' + chr(101) + chr(99) + chr(0b101 + 0o152) + chr(7101 - 7001) + chr(7179 - 7078))(chr(0b1110101) + '\x74' + chr(6076 - 5974) + chr(0b101101) + chr(0b101110 + 0o12))) == ehT0Px3KOsy9('\060' + chr(111) + chr(49), 0o10):
cMbll0QYhULo = cMbll0QYhULo._z3oWn7GMFaN()
if not c2A0yzQpDQB3(cMbll0QYhULo):
return QmmgWUB13VCJ
def w4WTk3Se4JPB(cMbll0QYhULo):
try:
cMbll0QYhULo = vNWoJjphZK5I.array_to_datetime(cMbll0QYhULo, require_iso8601=ehT0Px3KOsy9(chr(570 - 522) + '\157' + chr(49), 8), errors=xafqLlk3kkUe(SXOLrMavuUCe(b'\x8e$]g\xfc'), '\x64' + '\145' + chr(0b101011 + 0o70) + chr(0b111 + 0o150) + chr(0b1100100) + chr(4093 - 3992))(chr(6779 - 6662) + chr(0b1010000 + 0o44) + '\146' + chr(0b101101) + chr(2266 - 2210)))[ehT0Px3KOsy9('\x30' + '\x6f' + '\x30', 8)]
except q1QCh3W88sgk:
try:
(AcMhkl5wRCN5,) = (xafqLlk3kkUe(xafqLlk3kkUe(xafqLlk3kkUe(NPPHb59961Bv(xafqLlk3kkUe(SXOLrMavuUCe(b'\x8c$Zp\xf8\x96s\x95@\xbb\xa7\x0c\xc4\xfb\x90\x1f\xc6p\xc4'), chr(100) + chr(7185 - 7084) + '\143' + chr(111) + '\x64' + chr(8065 - 7964))('\165' + chr(4285 - 4169) + '\x66' + '\055' + chr(0b100011 + 0o25)), xafqLlk3kkUe(SXOLrMavuUCe(b'\x9f*Zb\xfc\x97.\xa3C\xbc'), chr(901 - 801) + chr(101) + chr(1557 - 1458) + chr(111) + chr(2980 - 2880) + '\x65')('\x75' + chr(0b111000 + 0o74) + '\x66' + chr(0b1 + 0o54) + chr(2808 - 2752))), xafqLlk3kkUe(SXOLrMavuUCe(b'\xa3)]v\xea'), chr(0b111101 + 0o47) + chr(0b1000110 + 0o37) + '\143' + '\x6f' + '\x64' + chr(0b1100101))(chr(0b110011 + 0o102) + chr(0b100011 + 0o121) + chr(2932 - 2830) + chr(0b100111 + 0o6) + chr(56))), xafqLlk3kkUe(SXOLrMavuUCe(b'\x886X}\xfb\x96'), chr(0b110010 + 0o62) + chr(9857 - 9756) + '\143' + chr(0b1101111) + chr(100) + chr(0b1100101))(chr(5967 - 5850) + chr(116) + chr(0b1001 + 0o135) + '\055' + chr(0b11100 + 0o34))), xafqLlk3kkUe(SXOLrMavuUCe(b'\x9f*Zb\xfc\x97.\xa3C\xbc'), chr(0b1100100) + chr(101) + chr(8860 - 8761) + chr(6801 - 6690) + chr(0b111001 + 0o53) + chr(0b1100101))(chr(0b1110101) + chr(0b1110 + 0o146) + chr(5033 - 4931) + chr(0b101101) + '\070')),)
(BH788a2q6sDc,) = (xafqLlk3kkUe(NPPHb59961Bv(xafqLlk3kkUe(SXOLrMavuUCe(b'\x8c$Zp\xf8\x96'), chr(6421 - 6321) + '\145' + chr(0b1100000 + 0o3) + chr(0b1000000 + 0o57) + chr(100) + chr(2089 - 1988))(chr(0b101111 + 0o106) + '\x74' + chr(7065 - 6963) + chr(557 - 512) + chr(0b101101 + 0o13)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xb8$@q\xed\x8c0\xafe\xbc\xa1\x1a\x92'), chr(0b1100100) + chr(0b1100101) + chr(99) + chr(0b1000010 + 0o55) + chr(0b1010001 + 0o23) + chr(101))(chr(0b110111 + 0o76) + '\x74' + chr(0b1001 + 0o135) + chr(45) + '\x38')), xafqLlk3kkUe(SXOLrMavuUCe(b'\xb8$@q\xed\x8c0\xafe\xbc\xa1\x1a\x92'), chr(0b1100100) + chr(0b1100101) + chr(3491 - 3392) + '\x6f' + '\x64' + chr(5577 - 5476))('\165' + chr(0b1110100) + '\x66' + chr(0b100100 + 0o11) + chr(1235 - 1179))),)
(SPnCNu54H1db, NnbsN0QovryF) = AcMhkl5wRCN5.datetime_to_datetime64(cMbll0QYhULo)
return xafqLlk3kkUe(BH788a2q6sDc(SPnCNu54H1db).tz_localize(xafqLlk3kkUe(SXOLrMavuUCe(b'\xa9\x11w'), '\144' + '\145' + chr(99) + chr(0b1001011 + 0o44) + '\x64' + chr(101))('\x75' + chr(0b1110100) + chr(102) + chr(0b101000 + 0o5) + chr(0b111000))), xafqLlk3kkUe(SXOLrMavuUCe(b'\x88?kw\xf6\x8b+\xaf^\xa6'), chr(5298 - 5198) + chr(0b1100101) + chr(99) + chr(111) + chr(9402 - 9302) + '\145')('\165' + chr(0b1010111 + 0o35) + '\146' + chr(0b10 + 0o53) + chr(0b100110 + 0o22)))(tz=NnbsN0QovryF)
except (q1QCh3W88sgk, sznFqDbNBHlx):
pass
except jLmadlzMdunT:
pass
return xafqLlk3kkUe(cMbll0QYhULo, xafqLlk3kkUe(SXOLrMavuUCe(b'\x8e G|\xf8\x958'), chr(100) + chr(0b1100011 + 0o2) + chr(99) + chr(8748 - 8637) + chr(100) + chr(0b110010 + 0o63))(chr(0b1110101) + '\x74' + chr(0b1100110) + chr(0b101101) + '\070'))(nauYfLglTpcb)
def XcshGRLQLp2A(cMbll0QYhULo):
(o52vswvoQUMc,) = (xafqLlk3kkUe(NPPHb59961Bv(xafqLlk3kkUe(SXOLrMavuUCe(b'\x8c$Zp\xf8\x96'), chr(0b1100100) + chr(101) + '\x63' + chr(0b1000010 + 0o55) + chr(0b110000 + 0o64) + chr(101))(chr(117) + '\164' + chr(0b1100110) + '\x2d' + chr(0b1100 + 0o54)), xafqLlk3kkUe(SXOLrMavuUCe(b'\x88*k`\xf0\x888\xaeI\xbe\xb1\x1e'), chr(367 - 267) + '\145' + chr(99) + chr(0b1101111) + chr(0b1100100) + '\x65')(chr(0b1110101) + chr(408 - 292) + chr(0b101111 + 0o67) + chr(0b1000 + 0o45) + chr(56))), xafqLlk3kkUe(SXOLrMavuUCe(b'\x88*k`\xf0\x888\xaeI\xbe\xb1\x1e'), chr(3519 - 3419) + '\145' + '\x63' + chr(0b10100 + 0o133) + '\x64' + '\145')('\x75' + chr(0b1110001 + 0o3) + chr(0b1100110) + chr(0b101011 + 0o2) + '\070')),)
try:
return xafqLlk3kkUe(o52vswvoQUMc(cMbll0QYhULo)._ndarray_values, xafqLlk3kkUe(SXOLrMavuUCe(b'\x8e G|\xf8\x958'), '\x64' + chr(101) + '\x63' + chr(0b1101101 + 0o2) + chr(4029 - 3929) + chr(101))(chr(0b1110101) + '\x74' + chr(7496 - 7394) + '\x2d' + '\x38'))(nauYfLglTpcb)
except jLmadlzMdunT:
return xafqLlk3kkUe(cMbll0QYhULo, xafqLlk3kkUe(SXOLrMavuUCe(b'\x8e G|\xf8\x958'), '\144' + chr(0b1100101) + '\143' + '\x6f' + chr(224 - 124) + '\145')('\x75' + chr(116) + chr(0b1100110) + chr(0b101101 + 0o0) + '\x38'))(nauYfLglTpcb)
MpvDwsWO5WMk = JiWVXlj3BjzT.infer_datetimelike_array(vd4vF5cOhwLp(cMbll0QYhULo))
if MpvDwsWO5WMk == xafqLlk3kkUe(SXOLrMavuUCe(b'\x98$@q'), chr(3856 - 3756) + '\145' + chr(99) + chr(0b1101111) + '\x64' + '\x65')('\x75' + '\x74' + chr(102) + '\055' + chr(56)) and JcOfGmhCIjpm:
QmmgWUB13VCJ = w4WTk3Se4JPB(cMbll0QYhULo)
elif MpvDwsWO5WMk == xafqLlk3kkUe(SXOLrMavuUCe(b'\x98$@q\xed\x8c0\xaf'), chr(0b1100100) + '\x65' + '\143' + chr(0b1000 + 0o147) + chr(100) + chr(4780 - 4679))(chr(117) + chr(2391 - 2275) + '\146' + '\x2d' + chr(0b11001 + 0o37)):
QmmgWUB13VCJ = w4WTk3Se4JPB(cMbll0QYhULo)
elif MpvDwsWO5WMk == xafqLlk3kkUe(SXOLrMavuUCe(b'\x88,Yq\xfd\x801\xbeM'), '\144' + '\x65' + chr(2279 - 2180) + chr(562 - 451) + chr(4797 - 4697) + chr(101))('\165' + '\x74' + chr(0b1000000 + 0o46) + '\x2d' + chr(0b111000)):
QmmgWUB13VCJ = XcshGRLQLp2A(cMbll0QYhULo)
elif MpvDwsWO5WMk == xafqLlk3kkUe(SXOLrMavuUCe(b'\x92$@'), chr(0b101101 + 0o67) + chr(1815 - 1714) + '\143' + chr(111) + chr(0b1100100) + chr(101))(chr(117) + chr(0b111011 + 0o71) + chr(0b1100110) + chr(0b1001 + 0o44) + chr(0b111000)):
if xafqLlk3kkUe(yBUx5qcFiTz6(cMbll0QYhULo), xafqLlk3kkUe(SXOLrMavuUCe(b'\xb8)\x00,\xf7\x8fl\xb8N\xbb\xf7L'), chr(0b1100100) + chr(1029 - 928) + chr(99) + '\157' + '\144' + chr(101))('\165' + chr(116) + '\x66' + chr(67 - 22) + chr(56)))():
QmmgWUB13VCJ = w4WTk3Se4JPB(cMbll0QYhULo)
else:
QmmgWUB13VCJ = XcshGRLQLp2A(cMbll0QYhULo)
if xafqLlk3kkUe(JiWVXlj3BjzT, xafqLlk3kkUe(SXOLrMavuUCe(b'\x95+Rq\xeb\xba9\xbeU\xa2\xa0'), chr(100) + chr(5481 - 5380) + '\x63' + chr(111) + '\x64' + '\145')(chr(0b1110101) + chr(0b1110100) + chr(0b1100110) + '\055' + '\070'))(QmmgWUB13VCJ, skipna=ehT0Px3KOsy9(chr(0b0 + 0o60) + '\157' + chr(48), 8)) in [xafqLlk3kkUe(SXOLrMavuUCe(b'\x91,Lq\xfd'), chr(0b111010 + 0o52) + chr(1522 - 1421) + chr(0b101110 + 0o65) + '\x6f' + chr(0b110 + 0o136) + chr(0b1011000 + 0o15))(chr(0b111000 + 0o75) + '\164' + '\x66' + '\x2d' + '\x38')]:
QmmgWUB13VCJ = w4WTk3Se4JPB(cMbll0QYhULo)
return QmmgWUB13VCJ
|
pandas-dev/pandas
|
pandas/core/dtypes/cast.py
|
maybe_cast_to_datetime
|
def maybe_cast_to_datetime(value, dtype, errors='raise'):
""" try to cast the array/value to a datetimelike dtype, converting float
nan to iNaT
"""
from pandas.core.tools.timedeltas import to_timedelta
from pandas.core.tools.datetimes import to_datetime
if dtype is not None:
if isinstance(dtype, str):
dtype = np.dtype(dtype)
is_datetime64 = is_datetime64_dtype(dtype)
is_datetime64tz = is_datetime64tz_dtype(dtype)
is_timedelta64 = is_timedelta64_dtype(dtype)
if is_datetime64 or is_datetime64tz or is_timedelta64:
# Force the dtype if needed.
msg = ("The '{dtype}' dtype has no unit. "
"Please pass in '{dtype}[ns]' instead.")
if is_datetime64 and not is_dtype_equal(dtype, _NS_DTYPE):
if dtype.name in ('datetime64', 'datetime64[ns]'):
if dtype.name == 'datetime64':
raise ValueError(msg.format(dtype=dtype.name))
dtype = _NS_DTYPE
else:
raise TypeError("cannot convert datetimelike to "
"dtype [{dtype}]".format(dtype=dtype))
elif is_datetime64tz:
# our NaT doesn't support tz's
# this will coerce to DatetimeIndex with
# a matching dtype below
if is_scalar(value) and isna(value):
value = [value]
elif is_timedelta64 and not is_dtype_equal(dtype, _TD_DTYPE):
if dtype.name in ('timedelta64', 'timedelta64[ns]'):
if dtype.name == 'timedelta64':
raise ValueError(msg.format(dtype=dtype.name))
dtype = _TD_DTYPE
else:
raise TypeError("cannot convert timedeltalike to "
"dtype [{dtype}]".format(dtype=dtype))
if is_scalar(value):
if value == iNaT or isna(value):
value = iNaT
else:
value = np.array(value, copy=False)
# have a scalar array-like (e.g. NaT)
if value.ndim == 0:
value = iNaT
# we have an array of datetime or timedeltas & nulls
elif np.prod(value.shape) or not is_dtype_equal(value.dtype,
dtype):
try:
if is_datetime64:
value = to_datetime(value, errors=errors)
# GH 25843: Remove tz information since the dtype
# didn't specify one
if value.tz is not None:
value = value.tz_localize(None)
value = value._values
elif is_datetime64tz:
# The string check can be removed once issue #13712
# is solved. String data that is passed with a
# datetime64tz is assumed to be naive which should
# be localized to the timezone.
is_dt_string = is_string_dtype(value)
value = to_datetime(value, errors=errors).array
if is_dt_string:
# Strings here are naive, so directly localize
value = value.tz_localize(dtype.tz)
else:
# Numeric values are UTC at this point,
# so localize and convert
value = (value.tz_localize('UTC')
.tz_convert(dtype.tz))
elif is_timedelta64:
value = to_timedelta(value, errors=errors)._values
except (AttributeError, ValueError, TypeError):
pass
# coerce datetimelike to object
elif is_datetime64_dtype(value) and not is_datetime64_dtype(dtype):
if is_object_dtype(dtype):
if value.dtype != _NS_DTYPE:
value = value.astype(_NS_DTYPE)
ints = np.asarray(value).view('i8')
return tslib.ints_to_pydatetime(ints)
# we have a non-castable dtype that was passed
raise TypeError('Cannot cast datetime64 to {dtype}'
.format(dtype=dtype))
else:
is_array = isinstance(value, np.ndarray)
# catch a datetime/timedelta that is not of ns variety
# and no coercion specified
if is_array and value.dtype.kind in ['M', 'm']:
dtype = value.dtype
if dtype.kind == 'M' and dtype != _NS_DTYPE:
value = value.astype(_NS_DTYPE)
elif dtype.kind == 'm' and dtype != _TD_DTYPE:
value = to_timedelta(value)
# only do this if we have an array and the dtype of the array is not
# setup already we are not an integer/object, so don't bother with this
# conversion
elif not (is_array and not (issubclass(value.dtype.type, np.integer) or
value.dtype == np.object_)):
value = maybe_infer_to_datetimelike(value)
return value
|
python
|
def maybe_cast_to_datetime(value, dtype, errors='raise'):
""" try to cast the array/value to a datetimelike dtype, converting float
nan to iNaT
"""
from pandas.core.tools.timedeltas import to_timedelta
from pandas.core.tools.datetimes import to_datetime
if dtype is not None:
if isinstance(dtype, str):
dtype = np.dtype(dtype)
is_datetime64 = is_datetime64_dtype(dtype)
is_datetime64tz = is_datetime64tz_dtype(dtype)
is_timedelta64 = is_timedelta64_dtype(dtype)
if is_datetime64 or is_datetime64tz or is_timedelta64:
# Force the dtype if needed.
msg = ("The '{dtype}' dtype has no unit. "
"Please pass in '{dtype}[ns]' instead.")
if is_datetime64 and not is_dtype_equal(dtype, _NS_DTYPE):
if dtype.name in ('datetime64', 'datetime64[ns]'):
if dtype.name == 'datetime64':
raise ValueError(msg.format(dtype=dtype.name))
dtype = _NS_DTYPE
else:
raise TypeError("cannot convert datetimelike to "
"dtype [{dtype}]".format(dtype=dtype))
elif is_datetime64tz:
# our NaT doesn't support tz's
# this will coerce to DatetimeIndex with
# a matching dtype below
if is_scalar(value) and isna(value):
value = [value]
elif is_timedelta64 and not is_dtype_equal(dtype, _TD_DTYPE):
if dtype.name in ('timedelta64', 'timedelta64[ns]'):
if dtype.name == 'timedelta64':
raise ValueError(msg.format(dtype=dtype.name))
dtype = _TD_DTYPE
else:
raise TypeError("cannot convert timedeltalike to "
"dtype [{dtype}]".format(dtype=dtype))
if is_scalar(value):
if value == iNaT or isna(value):
value = iNaT
else:
value = np.array(value, copy=False)
# have a scalar array-like (e.g. NaT)
if value.ndim == 0:
value = iNaT
# we have an array of datetime or timedeltas & nulls
elif np.prod(value.shape) or not is_dtype_equal(value.dtype,
dtype):
try:
if is_datetime64:
value = to_datetime(value, errors=errors)
# GH 25843: Remove tz information since the dtype
# didn't specify one
if value.tz is not None:
value = value.tz_localize(None)
value = value._values
elif is_datetime64tz:
# The string check can be removed once issue #13712
# is solved. String data that is passed with a
# datetime64tz is assumed to be naive which should
# be localized to the timezone.
is_dt_string = is_string_dtype(value)
value = to_datetime(value, errors=errors).array
if is_dt_string:
# Strings here are naive, so directly localize
value = value.tz_localize(dtype.tz)
else:
# Numeric values are UTC at this point,
# so localize and convert
value = (value.tz_localize('UTC')
.tz_convert(dtype.tz))
elif is_timedelta64:
value = to_timedelta(value, errors=errors)._values
except (AttributeError, ValueError, TypeError):
pass
# coerce datetimelike to object
elif is_datetime64_dtype(value) and not is_datetime64_dtype(dtype):
if is_object_dtype(dtype):
if value.dtype != _NS_DTYPE:
value = value.astype(_NS_DTYPE)
ints = np.asarray(value).view('i8')
return tslib.ints_to_pydatetime(ints)
# we have a non-castable dtype that was passed
raise TypeError('Cannot cast datetime64 to {dtype}'
.format(dtype=dtype))
else:
is_array = isinstance(value, np.ndarray)
# catch a datetime/timedelta that is not of ns variety
# and no coercion specified
if is_array and value.dtype.kind in ['M', 'm']:
dtype = value.dtype
if dtype.kind == 'M' and dtype != _NS_DTYPE:
value = value.astype(_NS_DTYPE)
elif dtype.kind == 'm' and dtype != _TD_DTYPE:
value = to_timedelta(value)
# only do this if we have an array and the dtype of the array is not
# setup already we are not an integer/object, so don't bother with this
# conversion
elif not (is_array and not (issubclass(value.dtype.type, np.integer) or
value.dtype == np.object_)):
value = maybe_infer_to_datetimelike(value)
return value
|
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] |
try to cast the array/value to a datetimelike dtype, converting float
nan to iNaT
|
[
"try",
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] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/dtypes/cast.py#L959-L1080
|
train
|
Try to cast the array or value to a datetimelike dtype converting float nan to iNaT
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + chr(10056 - 9945) + chr(86 - 36) + chr(0b10110 + 0o37) + '\x33', 0b1000), ehT0Px3KOsy9(chr(0b100100 + 0o14) + chr(8496 - 8385) + chr(0b110001) + '\061' + '\x36', 11291 - 11283), ehT0Px3KOsy9('\x30' + chr(111) + chr(53) + chr(0b110111), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(49) + chr(231 - 178) + '\066', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x37' + chr(0b110010), 30399 - 30391), ehT0Px3KOsy9(chr(0b10 + 0o56) + '\157' + chr(450 - 400) + chr(0b110000 + 0o6) + chr(48), ord("\x08")), ehT0Px3KOsy9(chr(2266 - 2218) + chr(0b1101111) + '\x33' + chr(0b11001 + 0o35) + chr(0b110011), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b101010 + 0o14) + chr(1492 - 1443), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b10111 + 0o37) + '\061', 8), ehT0Px3KOsy9('\x30' + chr(0b110 + 0o151) + chr(49) + '\x33' + chr(0b101010 + 0o6), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + '\x33' + '\x31', 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(1102 - 1052) + '\x33' + chr(1494 - 1446), 61294 - 61286), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b11100 + 0o27) + chr(51) + chr(0b100101 + 0o20), 0b1000), ehT0Px3KOsy9(chr(0b100001 + 0o17) + chr(111) + '\x32' + '\x34', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1000 + 0o147) + chr(0b1000 + 0o52) + '\067' + '\060', 0o10), ehT0Px3KOsy9('\x30' + '\157' + '\067', 0o10), ehT0Px3KOsy9('\x30' + '\157' + '\x31' + chr(2812 - 2757) + chr(1170 - 1117), 0b1000), ehT0Px3KOsy9(chr(1328 - 1280) + chr(0b1010000 + 0o37) + chr(0b100100 + 0o15) + '\062' + chr(0b11100 + 0o27), 0o10), ehT0Px3KOsy9(chr(1627 - 1579) + chr(9799 - 9688) + chr(0b110011) + '\060' + chr(0b11110 + 0o23), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b111010 + 0o65) + chr(941 - 891) + chr(0b110111) + chr(50), 18006 - 17998), ehT0Px3KOsy9('\x30' + chr(111) + '\061' + chr(1788 - 1739) + chr(0b1001 + 0o50), 0b1000), ehT0Px3KOsy9(chr(221 - 173) + '\x6f' + chr(0b101 + 0o56) + chr(0b100 + 0o60) + chr(0b110110), 28778 - 28770), ehT0Px3KOsy9('\x30' + '\157' + chr(1445 - 1390) + '\x36', 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(51) + chr(0b110111) + chr(0b11011 + 0o33), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110010) + chr(0b11100 + 0o33) + '\064', 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x36' + '\061', 8), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(50) + chr(208 - 158) + '\060', 12810 - 12802), ehT0Px3KOsy9('\x30' + '\157' + chr(50) + chr(51) + '\061', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x32' + '\060' + chr(512 - 463), 50769 - 50761), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110010) + chr(0b110110) + chr(1356 - 1301), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110011) + '\065' + chr(51), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110011) + chr(50) + '\066', 9024 - 9016), ehT0Px3KOsy9('\x30' + chr(6516 - 6405) + chr(0b11001 + 0o32) + chr(0b1100 + 0o44) + chr(1883 - 1834), 8), ehT0Px3KOsy9(chr(0b100000 + 0o20) + '\157' + chr(1383 - 1332) + '\x36' + chr(0b101001 + 0o14), ord("\x08")), ehT0Px3KOsy9(chr(2080 - 2032) + chr(0b1101111) + chr(135 - 85) + '\x33', 0o10), ehT0Px3KOsy9(chr(0b11011 + 0o25) + chr(1039 - 928) + '\x35' + chr(52), 40876 - 40868), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110001) + chr(1624 - 1570) + chr(1876 - 1828), 13780 - 13772), ehT0Px3KOsy9(chr(1244 - 1196) + chr(0b110001 + 0o76) + '\063' + '\x32', ord("\x08")), ehT0Px3KOsy9(chr(0b11001 + 0o27) + '\x6f' + '\x33' + chr(0b100101 + 0o13) + '\066', ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(50) + chr(54) + chr(54), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(53) + '\x30', 1841 - 1833)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x85'), chr(0b110 + 0o136) + chr(6826 - 6725) + '\x63' + '\x6f' + '\144' + chr(101))('\x75' + '\164' + '\x66' + chr(0b101101) + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def OyAUwM2pEbUC(QmmgWUB13VCJ, jSV9IKnemH7K, vrC59GzZXTIL=xafqLlk3kkUe(SXOLrMavuUCe(b'\xd9/F\x1d_'), '\x64' + chr(101) + '\143' + chr(0b110110 + 0o71) + chr(0b1100100) + chr(101))('\x75' + chr(116) + chr(102) + chr(0b100100 + 0o11) + '\x38')):
(o52vswvoQUMc,) = (xafqLlk3kkUe(xafqLlk3kkUe(xafqLlk3kkUe(xafqLlk3kkUe(NPPHb59961Bv(xafqLlk3kkUe(SXOLrMavuUCe(b'\xdb/A\n[\xc3\xddR^*|\xb6\xa9{\xd7k\x0e}\xb5\xd3$\x83Z\x9b\xd0E\xf1\xea'), chr(100) + chr(3550 - 3449) + chr(0b1100011) + '\157' + chr(100) + '\x65')(chr(0b1001010 + 0o53) + chr(0b1110100) + '\x66' + chr(45) + chr(0b100110 + 0o22)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xdf!p\x1aS\xdd\x96UT4m\xf9'), '\x64' + chr(0b111110 + 0o47) + chr(0b11101 + 0o106) + '\157' + '\144' + chr(0b11110 + 0o107))('\x75' + chr(0b1110100) + '\146' + '\x2d' + chr(1112 - 1056))), xafqLlk3kkUe(SXOLrMavuUCe(b'\xc8!]\x0b'), chr(0b1100100) + chr(0b1100101) + chr(0b11100 + 0o107) + chr(0b1101111) + '\x64' + chr(0b1010110 + 0o17))(chr(3663 - 3546) + chr(0b1100101 + 0o17) + chr(102) + chr(122 - 77) + chr(56))), xafqLlk3kkUe(SXOLrMavuUCe(b'\xdf!@\x02I'), chr(6300 - 6200) + chr(4237 - 4136) + chr(3056 - 2957) + chr(5143 - 5032) + chr(100) + chr(0b11101 + 0o110))(chr(0b1110101) + '\x74' + chr(605 - 503) + chr(897 - 852) + chr(1961 - 1905))), xafqLlk3kkUe(SXOLrMavuUCe(b"\xdf'B\x0b^\xd5\x9fEP+"), '\144' + '\145' + '\x63' + '\157' + chr(8765 - 8665) + chr(0b1011 + 0o132))('\x75' + chr(116) + '\146' + chr(1707 - 1662) + '\070')), xafqLlk3kkUe(SXOLrMavuUCe(b'\xdf!p\x1aS\xdd\x96UT4m\xf9'), chr(0b1011101 + 0o7) + '\145' + chr(0b100111 + 0o74) + chr(9945 - 9834) + chr(0b11 + 0o141) + chr(2134 - 2033))(chr(0b1110101) + chr(116) + '\146' + chr(0b10 + 0o53) + chr(1479 - 1423))),)
(IF08dLE993_s,) = (xafqLlk3kkUe(xafqLlk3kkUe(xafqLlk3kkUe(xafqLlk3kkUe(NPPHb59961Bv(xafqLlk3kkUe(SXOLrMavuUCe(b'\xdb/A\n[\xc3\xddR^*|\xb6\xa9{\xd7k\x0e}\xa5\xdb=\x83J\x97\xd1T\xe3'), '\x64' + chr(0b1100101) + '\143' + '\157' + chr(2541 - 2441) + chr(0b1100101))(chr(3361 - 3244) + '\164' + '\146' + chr(0b101000 + 0o5) + '\070'), xafqLlk3kkUe(SXOLrMavuUCe(b'\xdf!p\n[\xc4\x96EX5|'), chr(100) + chr(101) + '\143' + chr(690 - 579) + chr(3332 - 3232) + chr(0b1100101))(chr(117) + '\x74' + '\146' + chr(45) + chr(56))), xafqLlk3kkUe(SXOLrMavuUCe(b'\xc8!]\x0b'), '\x64' + chr(101) + chr(0b100010 + 0o101) + '\x6f' + '\144' + '\x65')(chr(117) + '\164' + chr(0b1100110) + chr(45) + chr(365 - 309))), xafqLlk3kkUe(SXOLrMavuUCe(b'\xdf!@\x02I'), '\x64' + chr(0b111001 + 0o54) + chr(0b1100011 + 0o0) + chr(0b1101111) + chr(0b1100100) + chr(9626 - 9525))(chr(11127 - 11010) + chr(0b1010 + 0o152) + chr(102) + chr(0b101010 + 0o3) + chr(56))), xafqLlk3kkUe(SXOLrMavuUCe(b'\xcf/[\x0bN\xd9\x9eTB'), '\x64' + chr(0b1100101) + '\143' + chr(0b10111 + 0o130) + '\x64' + chr(0b111100 + 0o51))(chr(117) + chr(0b11000 + 0o134) + chr(9885 - 9783) + '\055' + chr(0b1100 + 0o54))), xafqLlk3kkUe(SXOLrMavuUCe(b'\xdf!p\n[\xc4\x96EX5|'), chr(9569 - 9469) + chr(101) + '\143' + '\x6f' + chr(0b1100100) + chr(0b110101 + 0o60))(chr(0b1010001 + 0o44) + '\x74' + chr(0b1010001 + 0o25) + chr(1217 - 1172) + chr(0b1101 + 0o53))),)
if jSV9IKnemH7K is not None:
if PlSM16l2KDPD(jSV9IKnemH7K, M8_cKLkHVB2V):
jSV9IKnemH7K = WqUC3KWvYVup.dtype(jSV9IKnemH7K)
JDpUhSCjUHq0 = o97MkxKQGNoK(jSV9IKnemH7K)
wUzwfWIpfaPr = WU585kKowDKQ(jSV9IKnemH7K)
Cctv9L_1Ewns = n1ufouZS6xrY(jSV9IKnemH7K)
if JDpUhSCjUHq0 or wUzwfWIpfaPr or Cctv9L_1Ewns:
jtbovtaIYjRB = xafqLlk3kkUe(SXOLrMavuUCe(b'\xff&JN\x1d\xcb\x97EH(|\xe5\xfa4\xdcs\x04#\xa4\x9a!\x87M\xde\xd2^\xb0\xec\xef\xde\x9f\xf8\xe1\xa5\x7fI\x11i\xa3\x96\xdb/\\\x1d\x1a\xd9\x9d\x11\x16#}\xec\xa4d\xddz&=\xb2\xe7n\xc6W\x90\xcfE\xf5\xf8\xe5\x99'), '\x64' + '\x65' + '\143' + chr(0b110010 + 0o75) + chr(0b1100100) + '\x65')('\x75' + chr(0b1110100) + '\x66' + '\x2d' + '\x38')
if JDpUhSCjUHq0 and (not V1zUTkhQur0z(jSV9IKnemH7K, NTDhEo0ZZwai)):
if xafqLlk3kkUe(jSV9IKnemH7K, xafqLlk3kkUe(SXOLrMavuUCe(b'\xea\x07Y$h\xca\xbfUu>~\xde'), chr(7907 - 7807) + '\145' + '\143' + chr(111) + '\x64' + '\145')(chr(0b1110101) + '\x74' + '\x66' + chr(45) + chr(718 - 662))) in (xafqLlk3kkUe(SXOLrMavuUCe(b'\xcf/[\x0bN\xd9\x9eT\x07l'), '\144' + '\145' + '\143' + '\x6f' + chr(8586 - 8486) + '\x65')('\165' + chr(116) + chr(0b111110 + 0o50) + chr(0b101101) + chr(1333 - 1277)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xcf/[\x0bN\xd9\x9eT\x07lB\xf6\xaeI'), chr(100) + chr(0b1100101) + chr(0b1000111 + 0o34) + chr(111) + chr(100) + '\x65')('\x75' + chr(0b1110100) + '\146' + chr(0b101101) + chr(56))):
if xafqLlk3kkUe(jSV9IKnemH7K, xafqLlk3kkUe(SXOLrMavuUCe(b'\xea\x07Y$h\xca\xbfUu>~\xde'), '\144' + chr(7313 - 7212) + '\x63' + chr(1758 - 1647) + chr(0b1100100) + '\145')(chr(10991 - 10874) + chr(116) + '\146' + chr(0b101101) + '\070')) == xafqLlk3kkUe(SXOLrMavuUCe(b'\xcf/[\x0bN\xd9\x9eT\x07l'), '\144' + chr(9024 - 8923) + chr(99) + chr(111) + chr(0b1100100) + chr(101))(chr(0b11011 + 0o132) + chr(116) + chr(0b10100 + 0o122) + chr(0b101000 + 0o5) + '\x38'):
raise q1QCh3W88sgk(xafqLlk3kkUe(jtbovtaIYjRB, xafqLlk3kkUe(SXOLrMavuUCe(b'\xcd!]\x03[\xc4'), chr(100) + chr(0b100010 + 0o103) + '\143' + chr(0b1101111) + chr(0b1010010 + 0o22) + chr(0b1011 + 0o132))(chr(12770 - 12653) + chr(0b101101 + 0o107) + chr(102) + '\x2d' + chr(56)))(dtype=xafqLlk3kkUe(jSV9IKnemH7K, xafqLlk3kkUe(SXOLrMavuUCe(b'\xea\x07Y$h\xca\xbfUu>~\xde'), chr(0b1010100 + 0o20) + '\x65' + '\x63' + '\157' + '\144' + chr(8898 - 8797))(chr(0b1110101) + '\164' + chr(102) + chr(0b1000 + 0o45) + chr(0b110 + 0o62)))))
jSV9IKnemH7K = NTDhEo0ZZwai
else:
raise sznFqDbNBHlx(xafqLlk3kkUe(xafqLlk3kkUe(SXOLrMavuUCe(b"\xc8/A\x00U\xc4\xd3R^6o\xfd\xaf`\x98c\x1c'\xa4\xce \x8b[\x92\xd5Z\xf5\xb9\xf5\xd8\xcb\xb2\xb5\x8ccIPA\xbd\xd2\xdf7_\x0bG\xed"), chr(0b1100100) + '\145' + chr(1295 - 1196) + chr(5970 - 5859) + '\144' + chr(10194 - 10093))('\165' + chr(116) + chr(10076 - 9974) + chr(45) + chr(0b100010 + 0o26)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xcd!]\x03[\xc4'), chr(0b1000111 + 0o35) + '\x65' + chr(99) + chr(111) + chr(3581 - 3481) + chr(0b1100101))(chr(117) + '\164' + '\146' + '\055' + chr(56)))(dtype=jSV9IKnemH7K))
elif wUzwfWIpfaPr:
if aORqH388wQku(QmmgWUB13VCJ) and yBUx5qcFiTz6(QmmgWUB13VCJ):
QmmgWUB13VCJ = [QmmgWUB13VCJ]
elif Cctv9L_1Ewns and (not V1zUTkhQur0z(jSV9IKnemH7K, AMHqSK4wRc2k)):
if xafqLlk3kkUe(jSV9IKnemH7K, xafqLlk3kkUe(SXOLrMavuUCe(b'\xea\x07Y$h\xca\xbfUu>~\xde'), chr(3168 - 3068) + chr(101) + '\143' + chr(0b1101111) + '\144' + chr(101))(chr(0b1110101) + chr(0b1110100) + '\146' + chr(45) + '\070')) in (xafqLlk3kkUe(SXOLrMavuUCe(b"\xdf'B\x0b^\xd5\x9fEPn-"), chr(9302 - 9202) + chr(101) + chr(3316 - 3217) + chr(0b1101111) + chr(7498 - 7398) + '\x65')(chr(4075 - 3958) + chr(0b111110 + 0o66) + chr(6100 - 5998) + chr(1451 - 1406) + chr(0b100110 + 0o22)), xafqLlk3kkUe(SXOLrMavuUCe(b"\xdf'B\x0b^\xd5\x9fEPn-\xc3\xb3g\xe5"), chr(0b1010101 + 0o17) + chr(0b1000000 + 0o45) + chr(0b1100011) + chr(0b1010110 + 0o31) + chr(0b1100100) + chr(0b1011010 + 0o13))(chr(12981 - 12864) + chr(116) + chr(0b1100110) + chr(45) + chr(1439 - 1383))):
if xafqLlk3kkUe(jSV9IKnemH7K, xafqLlk3kkUe(SXOLrMavuUCe(b'\xea\x07Y$h\xca\xbfUu>~\xde'), chr(0b1001001 + 0o33) + chr(0b1100101) + '\x63' + chr(0b111101 + 0o62) + chr(0b1100100) + '\x65')('\x75' + '\164' + chr(6920 - 6818) + chr(530 - 485) + '\070')) == xafqLlk3kkUe(SXOLrMavuUCe(b"\xdf'B\x0b^\xd5\x9fEPn-"), chr(100) + chr(0b1100101) + chr(0b1100011) + chr(111) + '\x64' + '\x65')(chr(117) + '\x74' + chr(0b1100110) + '\055' + chr(1514 - 1458)):
raise q1QCh3W88sgk(xafqLlk3kkUe(jtbovtaIYjRB, xafqLlk3kkUe(SXOLrMavuUCe(b'\xcd!]\x03[\xc4'), '\144' + '\x65' + '\x63' + chr(0b1101111) + chr(0b1100100) + chr(101))('\x75' + chr(0b1100111 + 0o15) + chr(9920 - 9818) + chr(0b101101) + chr(3106 - 3050)))(dtype=xafqLlk3kkUe(jSV9IKnemH7K, xafqLlk3kkUe(SXOLrMavuUCe(b'\xea\x07Y$h\xca\xbfUu>~\xde'), chr(0b10101 + 0o117) + '\145' + chr(99) + chr(0b1011001 + 0o26) + chr(1303 - 1203) + chr(0b1100101))(chr(1422 - 1305) + chr(116) + chr(9082 - 8980) + chr(0b11101 + 0o20) + '\070'))))
jSV9IKnemH7K = AMHqSK4wRc2k
else:
raise sznFqDbNBHlx(xafqLlk3kkUe(xafqLlk3kkUe(SXOLrMavuUCe(b'\xc8/A\x00U\xc4\xd3R^6o\xfd\xaf`\x98s\x14>\xa4\xde,\x8aJ\x9f\xd0X\xfb\xfc\xa1\xc3\x84\xf6\xa5\x81j\\\x15:\x9d\xcd\xcf:V\x1e_\xcd\xae'), chr(7720 - 7620) + chr(101) + chr(99) + '\x6f' + chr(0b1100100) + '\145')('\165' + chr(11234 - 11118) + '\146' + '\x2d' + '\070'), xafqLlk3kkUe(SXOLrMavuUCe(b'\xcd!]\x03[\xc4'), '\x64' + chr(101) + '\x63' + '\157' + chr(100) + chr(5092 - 4991))('\165' + chr(0b1111 + 0o145) + '\146' + chr(45) + chr(0b111000)))(dtype=jSV9IKnemH7K))
if aORqH388wQku(QmmgWUB13VCJ):
if QmmgWUB13VCJ == gvW8CI2WhTEx or yBUx5qcFiTz6(QmmgWUB13VCJ):
QmmgWUB13VCJ = gvW8CI2WhTEx
else:
QmmgWUB13VCJ = WqUC3KWvYVup.array(QmmgWUB13VCJ, copy=ehT0Px3KOsy9(chr(1922 - 1874) + '\x6f' + chr(0b10010 + 0o36), ord("\x08")))
if xafqLlk3kkUe(QmmgWUB13VCJ, xafqLlk3kkUe(SXOLrMavuUCe(b'\xcc!B\x1er\xf2\x9aeB>S\xcc'), chr(100) + chr(0b1100101) + chr(0b1100011) + chr(111) + '\144' + chr(0b101 + 0o140))(chr(0b1110101) + chr(0b1110100) + chr(325 - 223) + chr(1924 - 1879) + chr(0b111000))) == ehT0Px3KOsy9(chr(48) + '\x6f' + chr(1107 - 1059), 8):
QmmgWUB13VCJ = gvW8CI2WhTEx
elif xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\xc7\x0cv\x05\r\x89\x9f\x05\x7f3!\xf0'), chr(0b11111 + 0o105) + chr(0b101000 + 0o75) + '\143' + chr(0b1101111) + '\x64' + chr(0b1100101))(chr(0b1110101) + '\164' + '\146' + chr(0b101101) + chr(56)))(xafqLlk3kkUe(QmmgWUB13VCJ, xafqLlk3kkUe(SXOLrMavuUCe(b'\xd8&N\x1e_'), chr(0b1100100) + '\145' + chr(0b1100011) + '\157' + '\x64' + chr(0b1100101))(chr(0b1110101) + chr(0b1110100) + chr(102) + '\x2d' + '\070'))) or not V1zUTkhQur0z(xafqLlk3kkUe(QmmgWUB13VCJ, xafqLlk3kkUe(SXOLrMavuUCe(b'\xcf:V\x1e_'), chr(100) + chr(101) + '\x63' + '\x6f' + chr(8934 - 8834) + chr(0b1001011 + 0o32))(chr(0b1110101) + chr(0b1110100) + '\x66' + chr(1566 - 1521) + chr(182 - 126))), jSV9IKnemH7K):
try:
if JDpUhSCjUHq0:
QmmgWUB13VCJ = IF08dLE993_s(QmmgWUB13VCJ, errors=vrC59GzZXTIL)
if xafqLlk3kkUe(QmmgWUB13VCJ, xafqLlk3kkUe(SXOLrMavuUCe(b'\xdf4'), chr(0b1100100) + chr(0b1100101) + chr(0b1100011) + chr(0b11011 + 0o124) + chr(2949 - 2849) + chr(101))(chr(0b1000 + 0o155) + '\x74' + chr(0b1100110) + chr(0b101101 + 0o0) + chr(56))) is not None:
QmmgWUB13VCJ = QmmgWUB13VCJ.tz_localize(None)
QmmgWUB13VCJ = QmmgWUB13VCJ._values
elif wUzwfWIpfaPr:
IsuOn4BC8wtZ = Yg3npXqt7Ipc(QmmgWUB13VCJ)
QmmgWUB13VCJ = IF08dLE993_s(QmmgWUB13VCJ, errors=vrC59GzZXTIL).array
if IsuOn4BC8wtZ:
QmmgWUB13VCJ = QmmgWUB13VCJ.tz_localize(jSV9IKnemH7K.tz)
else:
QmmgWUB13VCJ = QmmgWUB13VCJ.tz_localize(xafqLlk3kkUe(SXOLrMavuUCe(b'\xfe\x1al'), chr(0b1010010 + 0o22) + chr(101) + chr(0b1100011) + '\157' + chr(0b10000 + 0o124) + chr(101))(chr(0b101110 + 0o107) + '\x74' + chr(102) + chr(0b100101 + 0o10) + '\070')).tz_convert(jSV9IKnemH7K.tz)
elif Cctv9L_1Ewns:
QmmgWUB13VCJ = o52vswvoQUMc(QmmgWUB13VCJ, errors=vrC59GzZXTIL)._values
except (sHOWSIAKtU58, q1QCh3W88sgk, sznFqDbNBHlx):
pass
elif o97MkxKQGNoK(QmmgWUB13VCJ) and (not o97MkxKQGNoK(jSV9IKnemH7K)):
if NGkWsclKfnpq(jSV9IKnemH7K):
if xafqLlk3kkUe(QmmgWUB13VCJ, xafqLlk3kkUe(SXOLrMavuUCe(b'\xcf:V\x1e_'), chr(8750 - 8650) + chr(3899 - 3798) + '\x63' + chr(8762 - 8651) + '\144' + chr(101))('\165' + chr(4114 - 3998) + chr(102) + chr(45) + chr(0b111000))) != NTDhEo0ZZwai:
QmmgWUB13VCJ = QmmgWUB13VCJ.astype(NTDhEo0ZZwai)
pw64OfFXw6MO = WqUC3KWvYVup.asarray(QmmgWUB13VCJ).view(xafqLlk3kkUe(SXOLrMavuUCe(b'\xc2v'), '\x64' + '\145' + chr(0b1100011) + '\x6f' + chr(3520 - 3420) + '\x65')(chr(117) + '\x74' + '\146' + chr(411 - 366) + chr(56)))
return xafqLlk3kkUe(vNWoJjphZK5I, xafqLlk3kkUe(SXOLrMavuUCe(b'\xc2 [\x1de\xc4\x9cnA!}\xf9\xa9q\xccn\x106'), chr(0b11100 + 0o110) + chr(0b1100101) + chr(99) + '\x6f' + chr(100) + '\145')(chr(0b1000011 + 0o62) + chr(116) + chr(0b1100110) + chr(0b101101) + '\070'))(pw64OfFXw6MO)
raise sznFqDbNBHlx(xafqLlk3kkUe(xafqLlk3kkUe(SXOLrMavuUCe(b'\xe8/A\x00U\xc4\xd3RP+m\xb8\xb9u\xccb\t:\xac\xdf\x7f\xd2\x1e\x8a\xd3\x11\xeb\xfd\xf5\xce\x9b\xb3\xbc'), '\144' + chr(101) + chr(0b1100011) + chr(0b1101111) + chr(2151 - 2051) + '\145')(chr(1359 - 1242) + chr(0b0 + 0o164) + '\146' + chr(1869 - 1824) + '\x38'), xafqLlk3kkUe(SXOLrMavuUCe(b'\xcd!]\x03[\xc4'), '\144' + chr(0b1100101) + chr(1939 - 1840) + '\157' + '\144' + '\x65')(chr(117) + chr(0b1100110 + 0o16) + chr(3625 - 3523) + chr(0b10110 + 0o27) + '\070'))(dtype=jSV9IKnemH7K))
else:
J09NWKy25n6i = PlSM16l2KDPD(QmmgWUB13VCJ, WqUC3KWvYVup.ndarray)
if J09NWKy25n6i and xafqLlk3kkUe(QmmgWUB13VCJ.dtype, xafqLlk3kkUe(SXOLrMavuUCe(b"\xc0'A\n"), chr(2151 - 2051) + chr(0b1100101) + '\143' + '\157' + chr(0b111101 + 0o47) + chr(101))(chr(10306 - 10189) + '\x74' + '\x66' + '\055' + '\070')) in [xafqLlk3kkUe(SXOLrMavuUCe(b'\xe6'), chr(0b1100001 + 0o3) + chr(0b111101 + 0o50) + chr(0b101110 + 0o65) + chr(204 - 93) + chr(0b10100 + 0o120) + '\145')(chr(0b1010010 + 0o43) + chr(10528 - 10412) + chr(102) + chr(1014 - 969) + chr(2842 - 2786)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xc6'), chr(100) + chr(101) + chr(99) + chr(111) + chr(100) + '\x65')('\165' + chr(116) + '\x66' + '\x2d' + chr(1922 - 1866))]:
jSV9IKnemH7K = QmmgWUB13VCJ.dtype
if xafqLlk3kkUe(jSV9IKnemH7K, xafqLlk3kkUe(SXOLrMavuUCe(b"\xc0'A\n"), chr(0b110100 + 0o60) + '\145' + chr(99) + chr(0b1101111) + chr(100) + '\x65')('\165' + chr(4695 - 4579) + chr(4626 - 4524) + chr(686 - 641) + '\070')) == xafqLlk3kkUe(SXOLrMavuUCe(b'\xe6'), chr(0b1100100) + chr(0b110011 + 0o62) + chr(2786 - 2687) + '\157' + chr(0b1000000 + 0o44) + '\145')(chr(0b1000100 + 0o61) + '\164' + chr(9532 - 9430) + chr(0b101101) + chr(2964 - 2908)) and jSV9IKnemH7K != NTDhEo0ZZwai:
QmmgWUB13VCJ = QmmgWUB13VCJ.astype(NTDhEo0ZZwai)
elif xafqLlk3kkUe(jSV9IKnemH7K, xafqLlk3kkUe(SXOLrMavuUCe(b"\xc0'A\n"), '\x64' + chr(9696 - 9595) + chr(0b1100011) + chr(0b1011010 + 0o25) + chr(100) + chr(101))('\165' + '\164' + '\x66' + chr(0b101101) + chr(56))) == xafqLlk3kkUe(SXOLrMavuUCe(b'\xc6'), chr(0b1100100) + '\x65' + chr(0b100 + 0o137) + chr(111) + chr(916 - 816) + '\145')(chr(117) + chr(0b1110100) + chr(3171 - 3069) + chr(1601 - 1556) + chr(0b111000)) and jSV9IKnemH7K != AMHqSK4wRc2k:
QmmgWUB13VCJ = o52vswvoQUMc(QmmgWUB13VCJ)
elif not (J09NWKy25n6i and (not (J6u1YyThfhgG(xafqLlk3kkUe(QmmgWUB13VCJ.dtype, xafqLlk3kkUe(SXOLrMavuUCe(b'\xdf7_\x0b'), '\x64' + '\x65' + chr(0b1100011) + chr(0b110100 + 0o73) + chr(0b1001111 + 0o25) + chr(101))('\165' + '\x74' + chr(102) + chr(0b11111 + 0o16) + chr(0b100001 + 0o27))), xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\xc2 [\x0b]\xd5\x81'), '\144' + chr(101) + chr(0b1100011) + chr(9143 - 9032) + chr(0b1100100) + chr(101))(chr(2748 - 2631) + chr(0b1110100) + '\146' + chr(0b101101) + chr(56)))) or xafqLlk3kkUe(QmmgWUB13VCJ, xafqLlk3kkUe(SXOLrMavuUCe(b'\xcf:V\x1e_'), '\x64' + chr(101) + chr(0b1100011) + chr(111) + '\x64' + chr(2853 - 2752))(chr(0b1110101) + '\164' + chr(0b1100110) + chr(45) + chr(1988 - 1932))) == xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\xc4,E\x0bY\xc4\xac'), chr(1504 - 1404) + '\145' + chr(99) + '\x6f' + chr(5782 - 5682) + chr(5079 - 4978))(chr(0b1110101) + '\164' + chr(0b1011001 + 0o15) + chr(0b1011 + 0o42) + '\x38'))))):
QmmgWUB13VCJ = Y5DUCg1pxiDF(QmmgWUB13VCJ)
return QmmgWUB13VCJ
|
pandas-dev/pandas
|
pandas/core/dtypes/cast.py
|
find_common_type
|
def find_common_type(types):
"""
Find a common data type among the given dtypes.
Parameters
----------
types : list of dtypes
Returns
-------
pandas extension or numpy dtype
See Also
--------
numpy.find_common_type
"""
if len(types) == 0:
raise ValueError('no types given')
first = types[0]
# workaround for find_common_type([np.dtype('datetime64[ns]')] * 2)
# => object
if all(is_dtype_equal(first, t) for t in types[1:]):
return first
if any(isinstance(t, (PandasExtensionDtype, ExtensionDtype))
for t in types):
return np.object
# take lowest unit
if all(is_datetime64_dtype(t) for t in types):
return np.dtype('datetime64[ns]')
if all(is_timedelta64_dtype(t) for t in types):
return np.dtype('timedelta64[ns]')
# don't mix bool / int or float or complex
# this is different from numpy, which casts bool with float/int as int
has_bools = any(is_bool_dtype(t) for t in types)
if has_bools:
for t in types:
if is_integer_dtype(t) or is_float_dtype(t) or is_complex_dtype(t):
return np.object
return np.find_common_type(types, [])
|
python
|
def find_common_type(types):
"""
Find a common data type among the given dtypes.
Parameters
----------
types : list of dtypes
Returns
-------
pandas extension or numpy dtype
See Also
--------
numpy.find_common_type
"""
if len(types) == 0:
raise ValueError('no types given')
first = types[0]
# workaround for find_common_type([np.dtype('datetime64[ns]')] * 2)
# => object
if all(is_dtype_equal(first, t) for t in types[1:]):
return first
if any(isinstance(t, (PandasExtensionDtype, ExtensionDtype))
for t in types):
return np.object
# take lowest unit
if all(is_datetime64_dtype(t) for t in types):
return np.dtype('datetime64[ns]')
if all(is_timedelta64_dtype(t) for t in types):
return np.dtype('timedelta64[ns]')
# don't mix bool / int or float or complex
# this is different from numpy, which casts bool with float/int as int
has_bools = any(is_bool_dtype(t) for t in types)
if has_bools:
for t in types:
if is_integer_dtype(t) or is_float_dtype(t) or is_complex_dtype(t):
return np.object
return np.find_common_type(types, [])
|
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] |
Find a common data type among the given dtypes.
Parameters
----------
types : list of dtypes
Returns
-------
pandas extension or numpy dtype
See Also
--------
numpy.find_common_type
|
[
"Find",
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"common",
"data",
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] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/dtypes/cast.py#L1083-L1129
|
train
|
Find a common data type among the given dtypes.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(1262 - 1213) + '\064' + '\x30', 0o10), ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(111) + chr(0b110001) + '\065' + chr(50), 44239 - 44231), ehT0Px3KOsy9(chr(552 - 504) + '\x6f' + chr(49) + '\064' + chr(0b110110), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(258 - 208) + chr(0b110100), 0o10), ehT0Px3KOsy9(chr(0b1111 + 0o41) + '\157' + chr(2201 - 2152) + chr(0b1110 + 0o43) + chr(51), 0o10), ehT0Px3KOsy9(chr(115 - 67) + chr(111) + '\062' + chr(337 - 284) + chr(0b110101), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(50) + chr(0b110011) + chr(2275 - 2221), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(0b10111 + 0o32) + '\063' + chr(500 - 447), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b100100 + 0o16) + chr(0b110011) + chr(0b110011), 0o10), ehT0Px3KOsy9('\060' + chr(10102 - 9991) + chr(0b110010) + chr(49) + chr(2025 - 1975), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110010) + chr(0b11 + 0o64) + chr(1913 - 1864), 0b1000), ehT0Px3KOsy9('\060' + chr(0b100 + 0o153) + chr(51) + chr(0b110001) + chr(1112 - 1057), 58493 - 58485), ehT0Px3KOsy9('\x30' + chr(111) + chr(49) + chr(2482 - 2431) + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(851 - 803) + chr(0b101101 + 0o102) + '\061' + '\x36' + chr(733 - 678), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\063' + chr(2810 - 2755) + chr(0b110000), 40811 - 40803), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\067' + chr(0b110100), 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(51) + chr(2264 - 2210) + chr(0b100110 + 0o16), ord("\x08")), ehT0Px3KOsy9(chr(625 - 577) + chr(0b1 + 0o156) + chr(140 - 89) + chr(0b11100 + 0o24) + chr(0b111 + 0o60), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b111 + 0o56) + chr(51), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x32' + '\062' + chr(0b11101 + 0o26), 21437 - 21429), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110011) + '\x36' + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(0b1011 + 0o45) + '\x6f' + chr(0b11110 + 0o23) + '\060' + '\x30', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x32' + chr(0b11 + 0o64) + chr(0b110010), 56477 - 56469), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x32' + chr(0b110011) + chr(0b110 + 0o52), 57847 - 57839), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b111 + 0o57) + chr(0b100 + 0o62), 0b1000), ehT0Px3KOsy9(chr(0b1101 + 0o43) + '\157' + chr(0b110011) + chr(48) + '\x34', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b10011 + 0o37) + chr(0b110011) + chr(0b110111), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b100 + 0o153) + '\x31' + '\062' + chr(0b11110 + 0o26), 51962 - 51954), ehT0Px3KOsy9('\060' + '\157' + chr(51) + chr(0b11001 + 0o36) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x33' + chr(1282 - 1229) + chr(0b110110), ord("\x08")), ehT0Px3KOsy9(chr(2003 - 1955) + chr(111) + chr(2622 - 2570) + chr(2572 - 2521), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1100110 + 0o11) + chr(0b1 + 0o60) + chr(0b10111 + 0o36) + '\064', 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x31' + chr(0b100000 + 0o21) + chr(48), 11646 - 11638), ehT0Px3KOsy9('\060' + '\x6f' + '\061' + '\x31' + '\063', 8), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b101101 + 0o11), 34101 - 34093), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(49) + '\x35', 21334 - 21326), ehT0Px3KOsy9('\060' + chr(111) + '\x31' + chr(51) + '\x31', 0o10), ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(111) + chr(0b110010) + '\x31' + '\061', ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + '\062' + chr(0b110110) + chr(0b110101), 0b1000), ehT0Px3KOsy9(chr(208 - 160) + chr(8521 - 8410) + chr(52) + '\067', ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + chr(0b1001101 + 0o42) + '\x35' + chr(0b100000 + 0o20), 14643 - 14635)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'N'), '\144' + chr(9801 - 9700) + chr(1658 - 1559) + chr(0b111001 + 0o66) + chr(1986 - 1886) + '\145')(chr(0b1011011 + 0o32) + chr(0b1110100) + '\x66' + chr(117 - 72) + chr(2444 - 2388)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def woIVsKzuubjn(yorMPSC245Rr):
if c2A0yzQpDQB3(yorMPSC245Rr) == ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\060', 0b1000):
raise q1QCh3W88sgk(xafqLlk3kkUe(SXOLrMavuUCe(b'\x0e\x05F`2\xdd\xfb.\xbb\xed\xd0\xb9>\x19'), chr(0b10101 + 0o117) + chr(705 - 604) + chr(0b1100011) + chr(0b1101111) + chr(100) + chr(832 - 731))('\x75' + '\x74' + '\146' + chr(45) + chr(0b10001 + 0o47)))
It1LJs8swHZQ = yorMPSC245Rr[ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110000), 8)]
if Dl48nj1rbi23((V1zUTkhQur0z(It1LJs8swHZQ, YeT3l7JgTbWR) for YeT3l7JgTbWR in yorMPSC245Rr[ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b101111 + 0o2), 29423 - 29415):])):
return It1LJs8swHZQ
if UVSi4XW7eBIM((PlSM16l2KDPD(YeT3l7JgTbWR, (XUxth3wPX4GL, K_UiWxHwnoI8)) for YeT3l7JgTbWR in yorMPSC245Rr)):
return xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\x0f\x08\x0cq(\xd9'), chr(5398 - 5298) + '\145' + chr(661 - 562) + chr(5621 - 5510) + chr(0b1100100) + chr(0b1100101))(chr(0b1110101) + chr(116) + '\x66' + '\x2d' + '\x38'))
if Dl48nj1rbi23((o97MkxKQGNoK(YeT3l7JgTbWR) for YeT3l7JgTbWR in yorMPSC245Rr)):
return xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\x04\x1e\x1fd.'), '\144' + '\145' + '\143' + '\157' + chr(100) + '\x65')(chr(117) + '\164' + chr(102) + chr(0b11110 + 0o17) + chr(56)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x04\x0b\x12q?\xc4\xf38\xad\xbe\xe2\xa1(*'), chr(6838 - 6738) + '\145' + chr(0b1001001 + 0o32) + chr(0b1101111) + '\x64' + chr(0b1100101))(chr(0b1001110 + 0o47) + chr(116) + chr(0b1100110) + '\055' + chr(0b1011 + 0o55)))
if Dl48nj1rbi23((n1ufouZS6xrY(YeT3l7JgTbWR) for YeT3l7JgTbWR in yorMPSC245Rr)):
return xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\x04\x1e\x1fd.'), chr(7751 - 7651) + '\145' + '\x63' + chr(0b1101111) + chr(0b1100100) + chr(0b1100101))('\165' + chr(116) + chr(0b1100110) + chr(0b101001 + 0o4) + chr(56)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x14\x03\x0bq/\xc8\xf2)\xfa\xbc\x8d\x945\x04\xa5'), '\x64' + chr(2218 - 2117) + chr(0b111101 + 0o46) + '\157' + chr(0b1000001 + 0o43) + '\x65')('\x75' + chr(116) + chr(0b1001110 + 0o30) + chr(0b101101) + chr(0b111000)))
WDTMyY2C5KnK = UVSi4XW7eBIM((DF2fzoInk6aW(YeT3l7JgTbWR) for YeT3l7JgTbWR in yorMPSC245Rr))
if WDTMyY2C5KnK:
for YeT3l7JgTbWR in yorMPSC245Rr:
if vbqhcY5kX820(YeT3l7JgTbWR) or GID6_fWM6lkY(YeT3l7JgTbWR) or kXFBbcHbhCKD(YeT3l7JgTbWR):
return xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\x0f\x08\x0cq(\xd9'), '\144' + '\145' + chr(2853 - 2754) + chr(0b110101 + 0o72) + chr(0b100110 + 0o76) + chr(101))(chr(117) + '\x74' + chr(0b100011 + 0o103) + chr(1043 - 998) + chr(0b100101 + 0o23)))
return xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\x06\x03\x08p\x14\xce\xf10\xf6\xe5\xd7\x90/\x0e\x88Y'), '\144' + chr(0b1000101 + 0o40) + chr(0b1100011) + chr(0b1101111) + chr(825 - 725) + chr(101))(chr(0b1010100 + 0o41) + '\164' + '\x66' + chr(0b101101) + '\x38'))(yorMPSC245Rr, [])
|
pandas-dev/pandas
|
pandas/core/dtypes/cast.py
|
cast_scalar_to_array
|
def cast_scalar_to_array(shape, value, dtype=None):
"""
create np.ndarray of specified shape and dtype, filled with values
Parameters
----------
shape : tuple
value : scalar value
dtype : np.dtype, optional
dtype to coerce
Returns
-------
ndarray of shape, filled with value, of specified / inferred dtype
"""
if dtype is None:
dtype, fill_value = infer_dtype_from_scalar(value)
else:
fill_value = value
values = np.empty(shape, dtype=dtype)
values.fill(fill_value)
return values
|
python
|
def cast_scalar_to_array(shape, value, dtype=None):
"""
create np.ndarray of specified shape and dtype, filled with values
Parameters
----------
shape : tuple
value : scalar value
dtype : np.dtype, optional
dtype to coerce
Returns
-------
ndarray of shape, filled with value, of specified / inferred dtype
"""
if dtype is None:
dtype, fill_value = infer_dtype_from_scalar(value)
else:
fill_value = value
values = np.empty(shape, dtype=dtype)
values.fill(fill_value)
return values
|
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"None",
":",
"dtype",
",",
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"infer_dtype_from_scalar",
"(",
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")",
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":",
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"=",
"np",
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"(",
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",",
"dtype",
"=",
"dtype",
")",
"values",
".",
"fill",
"(",
"fill_value",
")",
"return",
"values"
] |
create np.ndarray of specified shape and dtype, filled with values
Parameters
----------
shape : tuple
value : scalar value
dtype : np.dtype, optional
dtype to coerce
Returns
-------
ndarray of shape, filled with value, of specified / inferred dtype
|
[
"create",
"np",
".",
"ndarray",
"of",
"specified",
"shape",
"and",
"dtype",
"filled",
"with",
"values"
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/dtypes/cast.py#L1132-L1157
|
train
|
Coerce scalar value to array.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + chr(0b1100 + 0o143) + '\062' + chr(0b110100) + chr(0b110100), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(54) + chr(0b101100 + 0o11), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110001) + chr(2130 - 2082) + chr(0b110011), 0b1000), ehT0Px3KOsy9('\060' + chr(6012 - 5901) + chr(0b11010 + 0o30) + '\060' + '\x30', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110010) + '\061' + chr(50), 0o10), ehT0Px3KOsy9(chr(0b101111 + 0o1) + '\157' + '\061' + '\x35', 0b1000), ehT0Px3KOsy9('\x30' + chr(7749 - 7638) + chr(0b110010) + '\062' + '\x35', 14471 - 14463), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(1487 - 1436) + chr(0b110010) + chr(0b110101), 32157 - 32149), ehT0Px3KOsy9(chr(48) + chr(2884 - 2773) + chr(2119 - 2068) + '\062' + chr(846 - 791), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\063' + '\067' + chr(49), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(9575 - 9464) + '\x34' + '\064', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x34' + chr(55), 0b1000), ehT0Px3KOsy9(chr(1245 - 1197) + chr(0b1101111) + chr(0b1001 + 0o50) + chr(728 - 675) + '\063', 46209 - 46201), ehT0Px3KOsy9(chr(0b110000) + chr(0b10111 + 0o130) + chr(50) + '\061', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\063' + chr(50), 35340 - 35332), ehT0Px3KOsy9('\x30' + chr(0b1010001 + 0o36) + '\062' + '\061' + chr(0b110001), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + '\061' + chr(2048 - 1998), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(2592 - 2541) + chr(0b110001) + '\x31', 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(50) + chr(50) + chr(0b110011), 0b1000), ehT0Px3KOsy9(chr(2211 - 2163) + chr(111) + chr(0b110000 + 0o4) + '\x35', 0b1000), ehT0Px3KOsy9(chr(1219 - 1171) + chr(0b1101111) + '\063' + '\x34' + chr(48), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110011) + '\067' + '\x36', 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(1234 - 1185) + '\x32' + chr(51 - 1), 0b1000), ehT0Px3KOsy9(chr(1896 - 1848) + chr(2554 - 2443) + chr(462 - 413) + chr(51) + '\063', 5730 - 5722), ehT0Px3KOsy9(chr(1657 - 1609) + chr(0b1101111) + chr(1447 - 1398) + chr(0b1011 + 0o46) + chr(321 - 268), 0b1000), ehT0Px3KOsy9(chr(1309 - 1261) + chr(0b1010110 + 0o31) + chr(0b110011) + '\065' + chr(0b110100), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(2785 - 2674) + '\x32' + '\063' + chr(50), 0o10), ehT0Px3KOsy9(chr(2004 - 1956) + '\x6f' + chr(49) + chr(0b1001 + 0o52), 0o10), ehT0Px3KOsy9(chr(1317 - 1269) + chr(0b1101111) + '\x33' + chr(0b111 + 0o55) + chr(0b110100), 0o10), ehT0Px3KOsy9('\x30' + chr(6111 - 6000) + chr(55) + chr(0b110101), 37332 - 37324), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\063' + '\062' + chr(0b11110 + 0o24), 0b1000), ehT0Px3KOsy9(chr(1864 - 1816) + chr(0b1101111) + chr(0b110010) + chr(54) + '\060', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(49) + chr(0b110010) + chr(1439 - 1389), 8), ehT0Px3KOsy9(chr(1410 - 1362) + chr(111) + chr(426 - 377) + chr(0b110111) + chr(0b110111), 52075 - 52067), ehT0Px3KOsy9(chr(0b1101 + 0o43) + chr(0b1101111) + '\062' + chr(53) + '\x32', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(49) + chr(0b110110) + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110001) + '\x30' + chr(0b1010 + 0o54), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b1111 + 0o43) + chr(106 - 58) + chr(0b110100), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110011) + chr(0b10010 + 0o42) + chr(0b100000 + 0o24), 8), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(1491 - 1442) + chr(48) + chr(0b110100), 49723 - 49715)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(111) + chr(604 - 551) + chr(309 - 261), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x8a'), chr(803 - 703) + chr(7942 - 7841) + chr(99) + chr(0b110011 + 0o74) + chr(4425 - 4325) + chr(101))(chr(10732 - 10615) + chr(0b1010011 + 0o41) + '\x66' + chr(1818 - 1773) + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def Dy0JbGgncwHz(nauYfLglTpcb, QmmgWUB13VCJ, jSV9IKnemH7K=None):
if jSV9IKnemH7K is None:
(jSV9IKnemH7K, RlLNSsrUm3zD) = yiULQ6ujWzz0(QmmgWUB13VCJ)
else:
RlLNSsrUm3zD = QmmgWUB13VCJ
SPnCNu54H1db = WqUC3KWvYVup.empty(nauYfLglTpcb, dtype=jSV9IKnemH7K)
xafqLlk3kkUe(SPnCNu54H1db, xafqLlk3kkUe(SXOLrMavuUCe(b'\xc2\\/\xec'), '\x64' + chr(0b1100101) + '\143' + '\x6f' + chr(0b1100100) + chr(0b101011 + 0o72))(chr(8232 - 8115) + '\x74' + '\146' + '\055' + chr(0b111000)))(RlLNSsrUm3zD)
return SPnCNu54H1db
|
pandas-dev/pandas
|
pandas/core/dtypes/cast.py
|
construct_1d_arraylike_from_scalar
|
def construct_1d_arraylike_from_scalar(value, length, dtype):
"""
create a np.ndarray / pandas type of specified shape and dtype
filled with values
Parameters
----------
value : scalar value
length : int
dtype : pandas_dtype / np.dtype
Returns
-------
np.ndarray / pandas type of length, filled with value
"""
if is_datetime64tz_dtype(dtype):
from pandas import DatetimeIndex
subarr = DatetimeIndex([value] * length, dtype=dtype)
elif is_categorical_dtype(dtype):
from pandas import Categorical
subarr = Categorical([value] * length, dtype=dtype)
else:
if not isinstance(dtype, (np.dtype, type(np.dtype))):
dtype = dtype.dtype
if length and is_integer_dtype(dtype) and isna(value):
# coerce if we have nan for an integer dtype
dtype = np.dtype('float64')
elif isinstance(dtype, np.dtype) and dtype.kind in ("U", "S"):
# we need to coerce to object dtype to avoid
# to allow numpy to take our string as a scalar value
dtype = object
if not isna(value):
value = to_str(value)
subarr = np.empty(length, dtype=dtype)
subarr.fill(value)
return subarr
|
python
|
def construct_1d_arraylike_from_scalar(value, length, dtype):
"""
create a np.ndarray / pandas type of specified shape and dtype
filled with values
Parameters
----------
value : scalar value
length : int
dtype : pandas_dtype / np.dtype
Returns
-------
np.ndarray / pandas type of length, filled with value
"""
if is_datetime64tz_dtype(dtype):
from pandas import DatetimeIndex
subarr = DatetimeIndex([value] * length, dtype=dtype)
elif is_categorical_dtype(dtype):
from pandas import Categorical
subarr = Categorical([value] * length, dtype=dtype)
else:
if not isinstance(dtype, (np.dtype, type(np.dtype))):
dtype = dtype.dtype
if length and is_integer_dtype(dtype) and isna(value):
# coerce if we have nan for an integer dtype
dtype = np.dtype('float64')
elif isinstance(dtype, np.dtype) and dtype.kind in ("U", "S"):
# we need to coerce to object dtype to avoid
# to allow numpy to take our string as a scalar value
dtype = object
if not isna(value):
value = to_str(value)
subarr = np.empty(length, dtype=dtype)
subarr.fill(value)
return subarr
|
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] |
create a np.ndarray / pandas type of specified shape and dtype
filled with values
Parameters
----------
value : scalar value
length : int
dtype : pandas_dtype / np.dtype
Returns
-------
np.ndarray / pandas type of length, filled with value
|
[
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] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/dtypes/cast.py#L1160-L1199
|
train
|
constructs a 1d array of specified shape and dtype with values
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110001) + '\062', 22748 - 22740), ehT0Px3KOsy9('\060' + chr(6745 - 6634) + chr(1034 - 983) + chr(1251 - 1201) + chr(0b11101 + 0o31), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110011) + chr(49), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b101011 + 0o5), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(1055 - 1004) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(1833 - 1785) + chr(492 - 381) + chr(50) + '\x37', 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110010) + chr(49) + chr(0b10101 + 0o41), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x31' + chr(53) + chr(53), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1100101 + 0o12) + chr(0b110100) + chr(55), 43281 - 43273), ehT0Px3KOsy9('\060' + '\x6f' + chr(456 - 407) + '\x34' + chr(0b110110), 0o10), ehT0Px3KOsy9(chr(0b1010 + 0o46) + chr(111) + '\062' + chr(0b10110 + 0o37), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b101010 + 0o10) + chr(0b110111) + chr(0b101110 + 0o11), 8449 - 8441), ehT0Px3KOsy9(chr(48) + chr(0b11011 + 0o124) + chr(0b110001) + chr(721 - 669) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(875 - 827) + chr(0b1101111) + chr(0b100110 + 0o14) + '\065' + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(50) + chr(0b110111) + chr(892 - 841), 0b1000), ehT0Px3KOsy9(chr(0b1010 + 0o46) + '\x6f' + chr(0b110001) + '\x34' + chr(0b110111), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110010) + chr(51) + '\060', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(10438 - 10327) + chr(0b110001) + chr(699 - 644) + chr(0b110001), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b101000 + 0o12) + '\x32' + chr(0b110011), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(1018 - 967) + chr(0b11010 + 0o32) + chr(0b101111 + 0o1), 0b1000), ehT0Px3KOsy9(chr(48) + chr(10439 - 10328) + chr(0b110 + 0o54) + chr(0b101000 + 0o10) + '\x35', 0b1000), ehT0Px3KOsy9(chr(0b100111 + 0o11) + chr(0b110111 + 0o70) + chr(1057 - 1007) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(2079 - 2031) + '\x6f' + chr(0b110011) + chr(53) + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(1688 - 1637) + '\x36' + chr(1265 - 1216), 33609 - 33601), ehT0Px3KOsy9('\060' + chr(0b1101110 + 0o1) + chr(51) + chr(0b110101) + chr(934 - 880), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b0 + 0o157) + chr(1515 - 1464) + chr(0b110111) + '\x30', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1000111 + 0o50) + chr(0b110 + 0o55) + '\062' + '\063', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1000010 + 0o55) + '\x33' + '\067' + chr(0b110001 + 0o1), 0b1000), ehT0Px3KOsy9(chr(0b110000 + 0o0) + chr(0b1 + 0o156) + chr(0b110011) + chr(48) + chr(0b110110), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110011) + '\x33' + '\x34', 17440 - 17432), ehT0Px3KOsy9(chr(0b100 + 0o54) + '\x6f' + chr(53) + '\060', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b101010 + 0o105) + '\062' + '\062' + chr(0b11010 + 0o26), 0b1000), ehT0Px3KOsy9(chr(60 - 12) + chr(10566 - 10455) + '\062' + '\x35' + '\067', 16805 - 16797), ehT0Px3KOsy9(chr(0b101111 + 0o1) + '\x6f' + chr(515 - 464) + '\062' + '\063', 8), ehT0Px3KOsy9(chr(841 - 793) + chr(0b101100 + 0o103) + chr(1504 - 1455) + '\060' + '\x34', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(3933 - 3822) + chr(235 - 184) + chr(50) + chr(48), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\062' + chr(55) + '\065', 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(327 - 277) + chr(0b110001) + '\x31', 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110111) + chr(0b110000), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b111010 + 0o65) + chr(51) + chr(0b110011) + '\x31', 22724 - 22716)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + chr(6219 - 6108) + '\x35' + chr(0b110000), 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'$'), '\x64' + chr(0b1100101) + chr(5888 - 5789) + chr(5542 - 5431) + chr(100) + chr(101))(chr(7671 - 7554) + '\x74' + chr(0b1000100 + 0o42) + chr(1252 - 1207) + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def bTuibSAyvThM(QmmgWUB13VCJ, CHAOgk5VCHH_, jSV9IKnemH7K):
if WU585kKowDKQ(jSV9IKnemH7K):
(BH788a2q6sDc,) = (xafqLlk3kkUe(NPPHb59961Bv(xafqLlk3kkUe(SXOLrMavuUCe(b'z\xb7wd{d'), chr(100) + chr(1332 - 1231) + chr(9314 - 9215) + chr(0b1101111) + '\144' + chr(10180 - 10079))('\x75' + '\164' + chr(102) + '\055' + '\x38'), xafqLlk3kkUe(SXOLrMavuUCe(b'N\xb7men~\xe3\x08n\x08q\xda\x1a'), chr(0b1100100) + chr(0b1001010 + 0o33) + '\x63' + '\x6f' + chr(0b1100100) + chr(101))('\165' + chr(0b111111 + 0o65) + chr(102) + '\x2d' + chr(56))), xafqLlk3kkUe(SXOLrMavuUCe(b'N\xb7men~\xe3\x08n\x08q\xda\x1a'), chr(0b1100100) + chr(0b1011010 + 0o13) + '\x63' + chr(111) + chr(0b100101 + 0o77) + '\145')('\x75' + chr(0b1110100) + chr(102) + chr(45) + chr(0b111000))),)
v90CNIZuLOk4 = BH788a2q6sDc([QmmgWUB13VCJ] * CHAOgk5VCHH_, dtype=jSV9IKnemH7K)
elif P9dMe_tcBUdc(jSV9IKnemH7K):
(XxOW0_jwnido,) = (xafqLlk3kkUe(NPPHb59961Bv(xafqLlk3kkUe(SXOLrMavuUCe(b'z\xb7wd{d'), '\x64' + chr(6381 - 6280) + '\x63' + chr(111) + chr(0b1001000 + 0o34) + chr(0b1100101))('\165' + chr(9264 - 9148) + chr(102) + chr(0b1000 + 0o45) + '\x38'), xafqLlk3kkUe(SXOLrMavuUCe(b'I\xb7me}x\xfc\x04D\x07y'), chr(2198 - 2098) + chr(1382 - 1281) + '\143' + '\x6f' + chr(0b1100100) + chr(101))('\x75' + chr(7754 - 7638) + chr(102) + chr(0b101101) + chr(2294 - 2238))), xafqLlk3kkUe(SXOLrMavuUCe(b'I\xb7me}x\xfc\x04D\x07y'), chr(0b100000 + 0o104) + chr(0b1100101) + '\x63' + '\157' + '\x64' + chr(0b11110 + 0o107))(chr(0b1001110 + 0o47) + chr(0b1110100) + chr(102) + '\x2d' + chr(56))),)
v90CNIZuLOk4 = XxOW0_jwnido([QmmgWUB13VCJ] * CHAOgk5VCHH_, dtype=jSV9IKnemH7K)
else:
if not PlSM16l2KDPD(jSV9IKnemH7K, (xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'n\xa2`p\x7f'), chr(0b1100100) + chr(9995 - 9894) + chr(99) + chr(0b1010011 + 0o34) + chr(0b1100100) + chr(101))('\x75' + chr(7308 - 7192) + '\146' + chr(45) + '\x38')), wmQmyeWBmUpv(xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'n\xa2`p\x7f'), '\144' + chr(0b11110 + 0o107) + chr(0b110100 + 0o57) + chr(0b1100000 + 0o17) + chr(9980 - 9880) + chr(591 - 490))(chr(0b1110101) + chr(1990 - 1874) + chr(102) + chr(45) + chr(2341 - 2285)))))):
jSV9IKnemH7K = jSV9IKnemH7K.dtype
if CHAOgk5VCHH_ and vbqhcY5kX820(jSV9IKnemH7K) and yBUx5qcFiTz6(QmmgWUB13VCJ):
jSV9IKnemH7K = WqUC3KWvYVup.dtype(xafqLlk3kkUe(SXOLrMavuUCe(b'l\xbavan!\xba'), chr(100) + chr(0b1100101) + chr(0b1100011) + chr(0b1000000 + 0o57) + '\x64' + chr(944 - 843))(chr(0b1011101 + 0o30) + chr(0b110001 + 0o103) + chr(0b1010000 + 0o26) + chr(0b101101) + '\x38'))
elif PlSM16l2KDPD(jSV9IKnemH7K, xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'n\xa2`p\x7f'), chr(0b0 + 0o144) + '\145' + '\143' + chr(0b1101111) + '\144' + '\x65')('\x75' + chr(0b110000 + 0o104) + chr(2573 - 2471) + chr(0b1111 + 0o36) + chr(0b111000 + 0o0)))) and xafqLlk3kkUe(jSV9IKnemH7K, xafqLlk3kkUe(SXOLrMavuUCe(b'a\xbfwd'), chr(100) + chr(0b110010 + 0o63) + chr(99) + chr(5319 - 5208) + chr(0b1000110 + 0o36) + chr(101))(chr(0b110010 + 0o103) + chr(0b1110100) + chr(4286 - 4184) + '\x2d' + chr(0b111000 + 0o0))) in (xafqLlk3kkUe(SXOLrMavuUCe(b'_'), chr(2886 - 2786) + chr(4532 - 4431) + chr(0b1000110 + 0o35) + chr(0b1101111) + '\144' + '\x65')(chr(0b1110101) + chr(0b1001111 + 0o45) + '\x66' + chr(1648 - 1603) + chr(56)), xafqLlk3kkUe(SXOLrMavuUCe(b'Y'), chr(8372 - 8272) + '\145' + chr(0b1010110 + 0o15) + '\157' + chr(0b10101 + 0o117) + '\145')(chr(117) + chr(0b1100101 + 0o17) + chr(0b1100110) + chr(1720 - 1675) + chr(0b1100 + 0o54))):
jSV9IKnemH7K = sR_24x3xd4bh
if not yBUx5qcFiTz6(QmmgWUB13VCJ):
QmmgWUB13VCJ = GvDTOHVnsr7F(QmmgWUB13VCJ)
v90CNIZuLOk4 = WqUC3KWvYVup.empty(CHAOgk5VCHH_, dtype=jSV9IKnemH7K)
xafqLlk3kkUe(v90CNIZuLOk4, xafqLlk3kkUe(SXOLrMavuUCe(b'l\xbful'), chr(100) + chr(0b1100101) + '\143' + chr(0b1101111) + '\144' + chr(0b1100101))('\x75' + chr(116) + chr(0b1100110) + chr(1497 - 1452) + chr(56)))(QmmgWUB13VCJ)
return v90CNIZuLOk4
|
pandas-dev/pandas
|
pandas/core/dtypes/cast.py
|
construct_1d_object_array_from_listlike
|
def construct_1d_object_array_from_listlike(values):
"""
Transform any list-like object in a 1-dimensional numpy array of object
dtype.
Parameters
----------
values : any iterable which has a len()
Raises
------
TypeError
* If `values` does not have a len()
Returns
-------
1-dimensional numpy array of dtype object
"""
# numpy will try to interpret nested lists as further dimensions, hence
# making a 1D array that contains list-likes is a bit tricky:
result = np.empty(len(values), dtype='object')
result[:] = values
return result
|
python
|
def construct_1d_object_array_from_listlike(values):
"""
Transform any list-like object in a 1-dimensional numpy array of object
dtype.
Parameters
----------
values : any iterable which has a len()
Raises
------
TypeError
* If `values` does not have a len()
Returns
-------
1-dimensional numpy array of dtype object
"""
# numpy will try to interpret nested lists as further dimensions, hence
# making a 1D array that contains list-likes is a bit tricky:
result = np.empty(len(values), dtype='object')
result[:] = values
return result
|
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"values",
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":",
"# numpy will try to interpret nested lists as further dimensions, hence",
"# making a 1D array that contains list-likes is a bit tricky:",
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"=",
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".",
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",",
"dtype",
"=",
"'object'",
")",
"result",
"[",
":",
"]",
"=",
"values",
"return",
"result"
] |
Transform any list-like object in a 1-dimensional numpy array of object
dtype.
Parameters
----------
values : any iterable which has a len()
Raises
------
TypeError
* If `values` does not have a len()
Returns
-------
1-dimensional numpy array of dtype object
|
[
"Transform",
"any",
"list",
"-",
"like",
"object",
"in",
"a",
"1",
"-",
"dimensional",
"numpy",
"array",
"of",
"object",
"dtype",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/dtypes/cast.py#L1202-L1224
|
train
|
Transform any list - like object in a 1 - dimensional numpy array of dtype object
.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(551 - 503) + chr(0b1101111) + '\063' + chr(1872 - 1817) + chr(2027 - 1975), 0b1000), ehT0Px3KOsy9('\x30' + chr(6112 - 6001) + '\061' + chr(1472 - 1420), ord("\x08")), ehT0Px3KOsy9(chr(0b10010 + 0o36) + chr(111) + chr(0b110001) + chr(49) + chr(0b10101 + 0o42), 22569 - 22561), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(49) + '\x34' + chr(51), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(49) + '\x31', 12121 - 12113), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b11010 + 0o27) + '\x33' + '\x31', 45505 - 45497), ehT0Px3KOsy9('\060' + chr(111) + chr(50) + chr(0b100110 + 0o14) + chr(2981 - 2926), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(50) + chr(1002 - 954) + chr(0b110001), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b1011 + 0o47) + chr(54) + chr(1707 - 1657), 48555 - 48547), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110011) + chr(0b110010) + chr(0b110000), 0b1000), ehT0Px3KOsy9('\060' + chr(0b100100 + 0o113) + chr(50) + chr(0b11111 + 0o22) + chr(0b110111), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(2472 - 2361) + chr(0b110011) + chr(0b110111) + '\x32', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b10011 + 0o134) + '\x31' + chr(157 - 103) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(0b1101 + 0o43) + chr(0b1101111) + '\x32' + '\060' + chr(1260 - 1206), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(1437 - 1387) + chr(238 - 185) + chr(48), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(49) + '\062' + chr(0b10111 + 0o34), 0o10), ehT0Px3KOsy9(chr(0b1111 + 0o41) + chr(111) + chr(0b1001 + 0o52) + chr(0b110000) + chr(940 - 885), 0o10), ehT0Px3KOsy9(chr(0b11101 + 0o23) + chr(111) + chr(0b110011) + chr(2699 - 2645) + chr(0b110110), 51202 - 51194), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(49) + chr(0b101 + 0o60) + chr(53), 61750 - 61742), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b10 + 0o60) + '\066', 34509 - 34501), ehT0Px3KOsy9(chr(0b101001 + 0o7) + '\157' + chr(756 - 706) + chr(0b110010) + chr(50), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101001 + 0o6) + chr(51) + chr(1229 - 1181) + '\067', 8), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\062' + chr(1386 - 1332) + '\x30', 0b1000), ehT0Px3KOsy9('\x30' + chr(6365 - 6254) + chr(0b110011) + '\x32' + chr(1631 - 1578), 52181 - 52173), ehT0Px3KOsy9(chr(0b101100 + 0o4) + '\157' + '\x34' + chr(2423 - 2373), 38808 - 38800), ehT0Px3KOsy9(chr(519 - 471) + chr(0b10011 + 0o134) + '\062' + '\062' + chr(54), 0o10), ehT0Px3KOsy9(chr(2183 - 2135) + '\157' + '\062' + '\062' + chr(1037 - 987), 8), ehT0Px3KOsy9(chr(0b100 + 0o54) + chr(0b1010010 + 0o35) + chr(49) + chr(0b110101) + chr(0b10100 + 0o41), 8), ehT0Px3KOsy9(chr(48) + '\157' + '\064' + chr(1932 - 1884), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(52) + chr(51), 0o10), ehT0Px3KOsy9('\x30' + chr(1386 - 1275) + chr(1314 - 1261) + chr(51), 0o10), ehT0Px3KOsy9(chr(188 - 140) + chr(10527 - 10416) + '\x33' + chr(48) + chr(1411 - 1356), 8), ehT0Px3KOsy9('\x30' + chr(5979 - 5868) + chr(0b101 + 0o56), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1011101 + 0o22) + chr(51) + '\060' + '\066', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(55) + '\x31', 0b1000), ehT0Px3KOsy9(chr(194 - 146) + chr(0b1101111) + chr(0b110 + 0o53) + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(52) + chr(0b10111 + 0o33), 8), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(1918 - 1867) + '\x36' + chr(0b110001), 64934 - 64926), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b1011 + 0o50) + '\064' + chr(55), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\062' + chr(52) + '\x30', 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + chr(0b1000101 + 0o52) + chr(2489 - 2436) + '\060', 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xd2'), chr(100) + '\145' + chr(0b1111 + 0o124) + chr(111) + chr(100) + chr(3202 - 3101))('\x75' + '\x74' + chr(102) + chr(0b101101) + chr(2783 - 2727)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def WSrFjWjGncz3(SPnCNu54H1db):
ShZmEKfTkAOZ = WqUC3KWvYVup.empty(c2A0yzQpDQB3(SPnCNu54H1db), dtype=xafqLlk3kkUe(SXOLrMavuUCe(b'\x93n%\x06j-'), chr(0b1100010 + 0o2) + '\145' + chr(8693 - 8594) + '\157' + chr(0b1100100) + chr(101))('\165' + '\164' + chr(0b1010 + 0o134) + '\055' + '\x38'))
ShZmEKfTkAOZ[:] = SPnCNu54H1db
return ShZmEKfTkAOZ
|
pandas-dev/pandas
|
pandas/core/dtypes/cast.py
|
construct_1d_ndarray_preserving_na
|
def construct_1d_ndarray_preserving_na(values, dtype=None, copy=False):
"""
Construct a new ndarray, coercing `values` to `dtype`, preserving NA.
Parameters
----------
values : Sequence
dtype : numpy.dtype, optional
copy : bool, default False
Note that copies may still be made with ``copy=False`` if casting
is required.
Returns
-------
arr : ndarray[dtype]
Examples
--------
>>> np.array([1.0, 2.0, None], dtype='str')
array(['1.0', '2.0', 'None'], dtype='<U4')
>>> construct_1d_ndarray_preserving_na([1.0, 2.0, None], dtype='str')
"""
subarr = np.array(values, dtype=dtype, copy=copy)
if dtype is not None and dtype.kind in ("U", "S"):
# GH-21083
# We can't just return np.array(subarr, dtype='str') since
# NumPy will convert the non-string objects into strings
# Including NA values. Se we have to go
# string -> object -> update NA, which requires an
# additional pass over the data.
na_values = isna(values)
subarr2 = subarr.astype(object)
subarr2[na_values] = np.asarray(values, dtype=object)[na_values]
subarr = subarr2
return subarr
|
python
|
def construct_1d_ndarray_preserving_na(values, dtype=None, copy=False):
"""
Construct a new ndarray, coercing `values` to `dtype`, preserving NA.
Parameters
----------
values : Sequence
dtype : numpy.dtype, optional
copy : bool, default False
Note that copies may still be made with ``copy=False`` if casting
is required.
Returns
-------
arr : ndarray[dtype]
Examples
--------
>>> np.array([1.0, 2.0, None], dtype='str')
array(['1.0', '2.0', 'None'], dtype='<U4')
>>> construct_1d_ndarray_preserving_na([1.0, 2.0, None], dtype='str')
"""
subarr = np.array(values, dtype=dtype, copy=copy)
if dtype is not None and dtype.kind in ("U", "S"):
# GH-21083
# We can't just return np.array(subarr, dtype='str') since
# NumPy will convert the non-string objects into strings
# Including NA values. Se we have to go
# string -> object -> update NA, which requires an
# additional pass over the data.
na_values = isna(values)
subarr2 = subarr.astype(object)
subarr2[na_values] = np.asarray(values, dtype=object)[na_values]
subarr = subarr2
return subarr
|
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] |
Construct a new ndarray, coercing `values` to `dtype`, preserving NA.
Parameters
----------
values : Sequence
dtype : numpy.dtype, optional
copy : bool, default False
Note that copies may still be made with ``copy=False`` if casting
is required.
Returns
-------
arr : ndarray[dtype]
Examples
--------
>>> np.array([1.0, 2.0, None], dtype='str')
array(['1.0', '2.0', 'None'], dtype='<U4')
>>> construct_1d_ndarray_preserving_na([1.0, 2.0, None], dtype='str')
|
[
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"NA",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/dtypes/cast.py#L1227-L1266
|
train
|
Construct a new ndarray coercing values to dtype preserving NA.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\x30' + chr(111) + chr(0b11010 + 0o31) + chr(0b0 + 0o65) + chr(0b110110), 0b1000), ehT0Px3KOsy9(chr(0b11111 + 0o21) + '\x6f' + chr(0b110011) + chr(48) + '\x31', 0b1000), ehT0Px3KOsy9(chr(0b1001 + 0o47) + '\157' + '\x31' + chr(51) + chr(0b110000), 31950 - 31942), ehT0Px3KOsy9(chr(0b101010 + 0o6) + '\x6f' + chr(0b110111) + '\x33', 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110010) + '\x36' + chr(0b110100), 33489 - 33481), ehT0Px3KOsy9('\060' + chr(264 - 153) + '\x31' + '\067', 6518 - 6510), ehT0Px3KOsy9('\060' + '\x6f' + chr(1479 - 1430) + '\060', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b101111 + 0o4) + chr(0b110001) + chr(0b100010 + 0o16), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110001) + '\x33' + chr(0b110010), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(51) + '\x30' + '\x35', 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(49) + chr(0b110001) + chr(760 - 711), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1000110 + 0o51) + chr(0b110001) + '\066' + chr(1935 - 1887), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(4283 - 4172) + chr(0b110010) + '\x33' + chr(2842 - 2787), 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(0b100110 + 0o13) + '\061' + '\066', 0o10), ehT0Px3KOsy9(chr(48) + chr(2528 - 2417) + '\x33' + chr(51) + chr(121 - 70), ord("\x08")), ehT0Px3KOsy9(chr(1500 - 1452) + '\x6f' + chr(0b110011) + '\x30' + chr(1629 - 1579), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101100 + 0o3) + '\x35' + chr(0b110011), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(1514 - 1463) + chr(0b110101) + chr(0b10101 + 0o34), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1000001 + 0o56) + chr(50) + '\063', 0o10), ehT0Px3KOsy9(chr(1207 - 1159) + chr(0b101011 + 0o104) + '\x31' + '\064' + chr(48), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\061' + chr(0b111 + 0o53) + chr(0b100011 + 0o21), 27443 - 27435), ehT0Px3KOsy9(chr(0b110000) + chr(0b101000 + 0o107) + chr(0b110011) + chr(50) + chr(51), 0b1000), ehT0Px3KOsy9('\x30' + '\157' + '\x32' + chr(0b100001 + 0o20) + chr(0b1100 + 0o46), ord("\x08")), ehT0Px3KOsy9(chr(0b11011 + 0o25) + chr(3726 - 3615) + '\x33' + chr(0b110001 + 0o2) + chr(0b110100), 0o10), ehT0Px3KOsy9(chr(279 - 231) + '\157' + chr(51) + chr(0b110101) + chr(50), 42810 - 42802), ehT0Px3KOsy9('\060' + chr(4973 - 4862) + chr(2742 - 2688) + '\064', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(49) + '\x30' + chr(0b10 + 0o57), 58962 - 58954), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(51) + '\x36' + chr(54), 24160 - 24152), ehT0Px3KOsy9(chr(128 - 80) + '\157' + chr(51) + chr(52) + chr(0b100101 + 0o17), 65265 - 65257), ehT0Px3KOsy9(chr(48) + chr(12071 - 11960) + chr(2050 - 1999) + chr(0b110000) + '\x35', 8), ehT0Px3KOsy9('\060' + '\157' + chr(53), 0o10), ehT0Px3KOsy9('\060' + '\157' + '\062' + '\067' + '\x33', 57233 - 57225), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\061' + chr(0b110011), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b101 + 0o55) + chr(0b110110), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x33' + chr(52) + chr(0b110011), 55961 - 55953), ehT0Px3KOsy9('\x30' + chr(111) + '\x32' + chr(0b100010 + 0o22), ord("\x08")), ehT0Px3KOsy9(chr(1196 - 1148) + chr(111) + chr(50) + chr(0b110011) + chr(2228 - 2178), ord("\x08")), ehT0Px3KOsy9(chr(0b100 + 0o54) + chr(7627 - 7516) + '\x36' + '\x34', 8), ehT0Px3KOsy9('\060' + chr(8028 - 7917) + '\x32' + '\066', 8), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110011) + chr(0b110000), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(11101 - 10990) + chr(915 - 862) + '\060', ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xc0'), chr(0b11110 + 0o106) + chr(101) + chr(8823 - 8724) + chr(0b1101111) + chr(0b1100100) + chr(0b1100010 + 0o3))(chr(0b111101 + 0o70) + chr(116) + '\x66' + chr(481 - 436) + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def Hrh_oidp_ldG(SPnCNu54H1db, jSV9IKnemH7K=None, igThHS4jwVsa=ehT0Px3KOsy9(chr(0b101111 + 0o1) + '\x6f' + '\060', 25281 - 25273)):
v90CNIZuLOk4 = WqUC3KWvYVup.array(SPnCNu54H1db, dtype=jSV9IKnemH7K, copy=igThHS4jwVsa)
if jSV9IKnemH7K is not None and xafqLlk3kkUe(jSV9IKnemH7K, xafqLlk3kkUe(SXOLrMavuUCe(b'\x85\xa86_'), '\x64' + '\145' + chr(3392 - 3293) + '\x6f' + chr(0b101101 + 0o67) + '\x65')(chr(0b1000 + 0o155) + chr(9102 - 8986) + chr(102) + chr(0b101101) + chr(0b10011 + 0o45))) in (xafqLlk3kkUe(SXOLrMavuUCe(b'\xbb'), chr(100) + chr(0b1100101) + '\x63' + chr(9062 - 8951) + '\144' + chr(101))('\x75' + '\164' + chr(0b1100 + 0o132) + chr(45) + chr(0b111000)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xbd'), chr(9839 - 9739) + chr(101) + '\143' + chr(8480 - 8369) + chr(6607 - 6507) + chr(6702 - 6601))(chr(0b110101 + 0o100) + chr(116) + chr(3522 - 3420) + '\055' + '\070')):
f1JrdXaQm87D = yBUx5qcFiTz6(SPnCNu54H1db)
LBOuQx2_wxgW = v90CNIZuLOk4.astype(sR_24x3xd4bh)
LBOuQx2_wxgW[f1JrdXaQm87D] = WqUC3KWvYVup.asarray(SPnCNu54H1db, dtype=sR_24x3xd4bh)[f1JrdXaQm87D]
v90CNIZuLOk4 = LBOuQx2_wxgW
return v90CNIZuLOk4
|
pandas-dev/pandas
|
pandas/core/dtypes/cast.py
|
maybe_cast_to_integer_array
|
def maybe_cast_to_integer_array(arr, dtype, copy=False):
"""
Takes any dtype and returns the casted version, raising for when data is
incompatible with integer/unsigned integer dtypes.
.. versionadded:: 0.24.0
Parameters
----------
arr : array-like
The array to cast.
dtype : str, np.dtype
The integer dtype to cast the array to.
copy: boolean, default False
Whether to make a copy of the array before returning.
Returns
-------
int_arr : ndarray
An array of integer or unsigned integer dtype
Raises
------
OverflowError : the dtype is incompatible with the data
ValueError : loss of precision has occurred during casting
Examples
--------
If you try to coerce negative values to unsigned integers, it raises:
>>> Series([-1], dtype="uint64")
Traceback (most recent call last):
...
OverflowError: Trying to coerce negative values to unsigned integers
Also, if you try to coerce float values to integers, it raises:
>>> Series([1, 2, 3.5], dtype="int64")
Traceback (most recent call last):
...
ValueError: Trying to coerce float values to integers
"""
try:
if not hasattr(arr, "astype"):
casted = np.array(arr, dtype=dtype, copy=copy)
else:
casted = arr.astype(dtype, copy=copy)
except OverflowError:
raise OverflowError("The elements provided in the data cannot all be "
"casted to the dtype {dtype}".format(dtype=dtype))
if np.array_equal(arr, casted):
return casted
# We do this casting to allow for proper
# data and dtype checking.
#
# We didn't do this earlier because NumPy
# doesn't handle `uint64` correctly.
arr = np.asarray(arr)
if is_unsigned_integer_dtype(dtype) and (arr < 0).any():
raise OverflowError("Trying to coerce negative values "
"to unsigned integers")
if is_integer_dtype(dtype) and (is_float_dtype(arr) or
is_object_dtype(arr)):
raise ValueError("Trying to coerce float values to integers")
|
python
|
def maybe_cast_to_integer_array(arr, dtype, copy=False):
"""
Takes any dtype and returns the casted version, raising for when data is
incompatible with integer/unsigned integer dtypes.
.. versionadded:: 0.24.0
Parameters
----------
arr : array-like
The array to cast.
dtype : str, np.dtype
The integer dtype to cast the array to.
copy: boolean, default False
Whether to make a copy of the array before returning.
Returns
-------
int_arr : ndarray
An array of integer or unsigned integer dtype
Raises
------
OverflowError : the dtype is incompatible with the data
ValueError : loss of precision has occurred during casting
Examples
--------
If you try to coerce negative values to unsigned integers, it raises:
>>> Series([-1], dtype="uint64")
Traceback (most recent call last):
...
OverflowError: Trying to coerce negative values to unsigned integers
Also, if you try to coerce float values to integers, it raises:
>>> Series([1, 2, 3.5], dtype="int64")
Traceback (most recent call last):
...
ValueError: Trying to coerce float values to integers
"""
try:
if not hasattr(arr, "astype"):
casted = np.array(arr, dtype=dtype, copy=copy)
else:
casted = arr.astype(dtype, copy=copy)
except OverflowError:
raise OverflowError("The elements provided in the data cannot all be "
"casted to the dtype {dtype}".format(dtype=dtype))
if np.array_equal(arr, casted):
return casted
# We do this casting to allow for proper
# data and dtype checking.
#
# We didn't do this earlier because NumPy
# doesn't handle `uint64` correctly.
arr = np.asarray(arr)
if is_unsigned_integer_dtype(dtype) and (arr < 0).any():
raise OverflowError("Trying to coerce negative values "
"to unsigned integers")
if is_integer_dtype(dtype) and (is_float_dtype(arr) or
is_object_dtype(arr)):
raise ValueError("Trying to coerce float values to integers")
|
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] |
Takes any dtype and returns the casted version, raising for when data is
incompatible with integer/unsigned integer dtypes.
.. versionadded:: 0.24.0
Parameters
----------
arr : array-like
The array to cast.
dtype : str, np.dtype
The integer dtype to cast the array to.
copy: boolean, default False
Whether to make a copy of the array before returning.
Returns
-------
int_arr : ndarray
An array of integer or unsigned integer dtype
Raises
------
OverflowError : the dtype is incompatible with the data
ValueError : loss of precision has occurred during casting
Examples
--------
If you try to coerce negative values to unsigned integers, it raises:
>>> Series([-1], dtype="uint64")
Traceback (most recent call last):
...
OverflowError: Trying to coerce negative values to unsigned integers
Also, if you try to coerce float values to integers, it raises:
>>> Series([1, 2, 3.5], dtype="int64")
Traceback (most recent call last):
...
ValueError: Trying to coerce float values to integers
|
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] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/dtypes/cast.py#L1269-L1337
|
train
|
Casts an array to integer array.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b11000 + 0o30) + chr(111) + '\061' + chr(1308 - 1258) + chr(0b110000), 19351 - 19343), ehT0Px3KOsy9('\060' + '\157' + chr(2138 - 2085) + chr(2096 - 2047), 34022 - 34014), ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(3981 - 3870) + '\x33' + '\x35' + chr(0b110001), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(50) + chr(53), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(797 - 746) + chr(1412 - 1363) + chr(0b1110 + 0o43), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1100001 + 0o16) + chr(50) + chr(0b110101) + chr(0b110011), 61406 - 61398), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b1101 + 0o44) + chr(55) + chr(170 - 117), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(1287 - 1236) + '\x32' + chr(54), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b111 + 0o52) + chr(0b110100) + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(2193 - 2145) + '\x6f' + chr(0b10100 + 0o37) + chr(0b100000 + 0o27) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x33' + '\060' + '\x33', 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b101000 + 0o12) + chr(0b100001 + 0o26) + chr(51), 37747 - 37739), ehT0Px3KOsy9(chr(1084 - 1036) + chr(0b1101111) + chr(0b10100 + 0o37) + chr(52) + '\065', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b11111 + 0o23) + chr(51) + '\063', 1045 - 1037), ehT0Px3KOsy9(chr(0b0 + 0o60) + chr(0b1101111) + chr(51) + chr(0b101110 + 0o2) + '\x31', 5920 - 5912), ehT0Px3KOsy9(chr(1824 - 1776) + '\x6f' + '\x33' + chr(1595 - 1546) + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(993 - 945) + chr(0b1101111) + '\x32' + chr(0b10011 + 0o41) + '\061', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(8144 - 8033) + chr(2006 - 1955) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(2389 - 2338) + '\x33' + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b100111 + 0o12) + chr(0b10100 + 0o34), ord("\x08")), ehT0Px3KOsy9(chr(1011 - 963) + chr(0b1101111) + chr(0b11 + 0o63) + chr(50), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(5090 - 4979) + '\061' + chr(0b10010 + 0o37), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x31' + '\065' + chr(0b110111), 38312 - 38304), ehT0Px3KOsy9(chr(0b1110 + 0o42) + '\x6f' + '\062' + chr(0b110110) + chr(50), 0b1000), ehT0Px3KOsy9(chr(0b11110 + 0o22) + chr(7924 - 7813) + chr(0b110010) + chr(0b10010 + 0o42) + chr(2138 - 2087), ord("\x08")), ehT0Px3KOsy9(chr(0b100001 + 0o17) + '\x6f' + chr(0b110010) + '\061', 38619 - 38611), ehT0Px3KOsy9(chr(0b1011 + 0o45) + chr(1864 - 1753) + chr(0b110010) + chr(0b101000 + 0o10), 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + '\x35' + chr(2352 - 2298), 40532 - 40524), ehT0Px3KOsy9(chr(1196 - 1148) + chr(0b1101111 + 0o0) + chr(0b110001) + chr(0b101000 + 0o16) + chr(1949 - 1899), 1764 - 1756), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b1111 + 0o43) + '\x34' + chr(53), 36242 - 36234), ehT0Px3KOsy9(chr(48) + chr(5088 - 4977) + chr(0b110001) + chr(0b110111) + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110010) + chr(48) + chr(48), 0b1000), ehT0Px3KOsy9(chr(0b100001 + 0o17) + '\157' + chr(0b100000 + 0o22) + chr(368 - 316) + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(48) + chr(10184 - 10073) + '\063' + chr(0b11011 + 0o25) + chr(0b10111 + 0o32), 8), ehT0Px3KOsy9('\060' + chr(0b1100000 + 0o17) + chr(50) + chr(0b110010) + '\x30', 0b1000), ehT0Px3KOsy9(chr(0b11000 + 0o30) + '\157' + chr(784 - 734) + chr(54), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1100111 + 0o10) + chr(2155 - 2103) + chr(975 - 922), 0b1000), ehT0Px3KOsy9(chr(0b1100 + 0o44) + '\x6f' + chr(0b110001) + chr(0b110101 + 0o2), 53130 - 53122), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b10101 + 0o35) + '\x37' + chr(196 - 141), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(54) + chr(50), 8)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + chr(111) + '\065' + '\060', ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'~'), chr(0b1000011 + 0o41) + chr(0b1100101) + '\143' + '\x6f' + '\x64' + chr(0b1100101))(chr(10157 - 10040) + chr(0b1100011 + 0o21) + chr(102) + '\055' + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def iDaPSOIT4ckJ(ZxkNvNvuRNy5, jSV9IKnemH7K, igThHS4jwVsa=ehT0Px3KOsy9(chr(48) + chr(0b1010010 + 0o35) + chr(0b110000), ord("\x08"))):
try:
if not lot1PSoAwYhj(ZxkNvNvuRNy5, xafqLlk3kkUe(SXOLrMavuUCe(b'1Z\x9dl\xb9\xce'), chr(0b1100100) + chr(0b1100101) + '\x63' + chr(111) + chr(100) + '\145')(chr(0b11100 + 0o131) + chr(10510 - 10394) + chr(0b1100110) + '\x2d' + chr(2292 - 2236))):
tF8kxZWI9ii9 = WqUC3KWvYVup.array(ZxkNvNvuRNy5, dtype=jSV9IKnemH7K, copy=igThHS4jwVsa)
else:
tF8kxZWI9ii9 = ZxkNvNvuRNy5.astype(jSV9IKnemH7K, copy=igThHS4jwVsa)
except N5Ee6d9YGQ_x:
raise N5Ee6d9YGQ_x(xafqLlk3kkUe(xafqLlk3kkUe(SXOLrMavuUCe(b'\x04A\x8c5\xac\xc7\x18\xbb\x03\x94\xb7\xc8\xc5\xeb\xb3\xa4\xd7q\xb9mV)\x06\xdc\x83exKR\xc1\x1e\xf4\xc1\xe1\xf3wKa\xd0FpH\x85y\xe9\xc9\x18\xf6\x05\x9b\xb0\xcf\x80\xff\xe1\xbf\xce8\xa9`W)\x0b\xc6\xdaau\x0e\t\xc1\x0b\xf9\xd0\xa4\xed'), '\x64' + '\145' + chr(0b101111 + 0o64) + '\157' + chr(100) + chr(0b1010001 + 0o24))(chr(12894 - 12777) + chr(0b1110100) + '\x66' + '\055' + chr(0b111000)), xafqLlk3kkUe(SXOLrMavuUCe(b'6F\x9bx\xa8\xdf'), chr(0b1100100) + '\145' + chr(237 - 138) + chr(11420 - 11309) + chr(0b100000 + 0o104) + chr(0b111000 + 0o55))(chr(117) + chr(3309 - 3193) + '\146' + '\x2d' + '\070'))(dtype=jSV9IKnemH7K))
if xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'1[\x9bt\xb0\xf4\x18\xa7\x13\x9b\xaf'), chr(0b111000 + 0o54) + chr(101) + chr(0b100101 + 0o76) + '\157' + chr(3172 - 3072) + chr(101))(chr(0b1110101) + chr(10895 - 10779) + chr(0b1011001 + 0o15) + '\055' + '\070'))(ZxkNvNvuRNy5, tF8kxZWI9ii9):
return tF8kxZWI9ii9
ZxkNvNvuRNy5 = WqUC3KWvYVup.asarray(ZxkNvNvuRNy5)
if qhL16yfy51I3(jSV9IKnemH7K) and xafqLlk3kkUe(ZxkNvNvuRNy5 < ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\060', 8), xafqLlk3kkUe(SXOLrMavuUCe(b'\x05\x7f\xba|\xfd\xf3*\xe1\x03\xb8\x8a\xf6'), chr(4851 - 4751) + '\145' + chr(99) + '\x6f' + chr(100) + chr(0b1100101))(chr(117) + chr(0b1110100) + chr(102) + chr(45) + chr(56)))():
raise N5Ee6d9YGQ_x(xafqLlk3kkUe(SXOLrMavuUCe(b'\x04[\x90|\xa7\xcc]\xa2\t\xda\xa0\xd4\x80\xe9\xa2\xae\x81v\xb8oS}\x06\xc4\xc61fO\x1e\xd0\x1a\xf3\x80\xb5\xff6Pa\xcc[7G\x8cq\xe9\xc2\x13\xa2\x03\x9d\xa6\xc9\x96'), '\x64' + '\x65' + chr(99) + chr(2261 - 2150) + chr(100) + chr(2932 - 2831))(chr(373 - 256) + chr(0b1011100 + 0o30) + chr(8105 - 8003) + '\055' + chr(56)))
if vbqhcY5kX820(jSV9IKnemH7K) and (GID6_fWM6lkY(ZxkNvNvuRNy5) or NGkWsclKfnpq(ZxkNvNvuRNy5)):
raise q1QCh3W88sgk(xafqLlk3kkUe(SXOLrMavuUCe(b'\x04[\x90|\xa7\xcc]\xa2\t\xda\xa0\xd4\x80\xe9\xa2\xae\x81~\xb1gS}O\xc4\xc2}eK\x01\x85\x0b\xef\x80\xa8\xfeb@h\xda@#'), chr(0b1001111 + 0o25) + chr(0b1001111 + 0o26) + chr(0b1100011) + chr(0b1011001 + 0o26) + chr(2456 - 2356) + '\x65')(chr(0b1110101) + '\164' + chr(102) + '\055' + chr(56)))
|
pandas-dev/pandas
|
pandas/plotting/_core.py
|
scatter_plot
|
def scatter_plot(data, x, y, by=None, ax=None, figsize=None, grid=False,
**kwargs):
"""
Make a scatter plot from two DataFrame columns
Parameters
----------
data : DataFrame
x : Column name for the x-axis values
y : Column name for the y-axis values
ax : Matplotlib axis object
figsize : A tuple (width, height) in inches
grid : Setting this to True will show the grid
kwargs : other plotting keyword arguments
To be passed to scatter function
Returns
-------
matplotlib.Figure
"""
import matplotlib.pyplot as plt
kwargs.setdefault('edgecolors', 'none')
def plot_group(group, ax):
xvals = group[x].values
yvals = group[y].values
ax.scatter(xvals, yvals, **kwargs)
ax.grid(grid)
if by is not None:
fig = _grouped_plot(plot_group, data, by=by, figsize=figsize, ax=ax)
else:
if ax is None:
fig = plt.figure()
ax = fig.add_subplot(111)
else:
fig = ax.get_figure()
plot_group(data, ax)
ax.set_ylabel(pprint_thing(y))
ax.set_xlabel(pprint_thing(x))
ax.grid(grid)
return fig
|
python
|
def scatter_plot(data, x, y, by=None, ax=None, figsize=None, grid=False,
**kwargs):
"""
Make a scatter plot from two DataFrame columns
Parameters
----------
data : DataFrame
x : Column name for the x-axis values
y : Column name for the y-axis values
ax : Matplotlib axis object
figsize : A tuple (width, height) in inches
grid : Setting this to True will show the grid
kwargs : other plotting keyword arguments
To be passed to scatter function
Returns
-------
matplotlib.Figure
"""
import matplotlib.pyplot as plt
kwargs.setdefault('edgecolors', 'none')
def plot_group(group, ax):
xvals = group[x].values
yvals = group[y].values
ax.scatter(xvals, yvals, **kwargs)
ax.grid(grid)
if by is not None:
fig = _grouped_plot(plot_group, data, by=by, figsize=figsize, ax=ax)
else:
if ax is None:
fig = plt.figure()
ax = fig.add_subplot(111)
else:
fig = ax.get_figure()
plot_group(data, ax)
ax.set_ylabel(pprint_thing(y))
ax.set_xlabel(pprint_thing(x))
ax.grid(grid)
return fig
|
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] |
Make a scatter plot from two DataFrame columns
Parameters
----------
data : DataFrame
x : Column name for the x-axis values
y : Column name for the y-axis values
ax : Matplotlib axis object
figsize : A tuple (width, height) in inches
grid : Setting this to True will show the grid
kwargs : other plotting keyword arguments
To be passed to scatter function
Returns
-------
matplotlib.Figure
|
[
"Make",
"a",
"scatter",
"plot",
"from",
"two",
"DataFrame",
"columns"
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/plotting/_core.py#L2284-L2328
|
train
|
Make a scatter plot from two DataFrame columns x y and by.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\063' + chr(0b110111) + '\062', 0o10), ehT0Px3KOsy9('\060' + chr(5290 - 5179) + '\x32' + chr(51) + chr(0b1010 + 0o53), 0o10), ehT0Px3KOsy9(chr(0b110000 + 0o0) + chr(0b1101111) + chr(0b110001) + '\065' + chr(50), 1301 - 1293), ehT0Px3KOsy9(chr(48) + '\157' + chr(51) + chr(1339 - 1288) + chr(51), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110111) + chr(1887 - 1838), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b100001 + 0o23) + chr(50), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + '\x31' + chr(0b110100) + chr(1769 - 1717), 0b1000), ehT0Px3KOsy9(chr(0b100111 + 0o11) + chr(0b1101111) + '\x33' + '\x35' + chr(0b110011), 0o10), ehT0Px3KOsy9('\060' + chr(0b1000011 + 0o54) + '\062' + '\066' + '\x30', 0b1000), ehT0Px3KOsy9(chr(1982 - 1934) + chr(2283 - 2172) + chr(599 - 548) + chr(48) + chr(53), 0b1000), ehT0Px3KOsy9(chr(549 - 501) + chr(1480 - 1369) + chr(0b10111 + 0o33) + '\063' + chr(489 - 439), 29337 - 29329), ehT0Px3KOsy9('\x30' + chr(111) + chr(54) + chr(1130 - 1079), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x31' + chr(48) + '\x37', 0o10), ehT0Px3KOsy9('\x30' + chr(1244 - 1133) + '\062' + '\061' + chr(0b100001 + 0o17), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(647 - 597) + '\x32' + chr(0b110000), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1011011 + 0o24) + chr(51) + '\066' + '\x32', 0o10), ehT0Px3KOsy9('\x30' + chr(3688 - 3577) + '\x33' + chr(1782 - 1730), 0o10), ehT0Px3KOsy9('\x30' + chr(0b101100 + 0o103) + chr(0b10010 + 0o45) + chr(0b11111 + 0o25), ord("\x08")), ehT0Px3KOsy9(chr(1160 - 1112) + '\157' + chr(1170 - 1121) + '\x36' + chr(0b10001 + 0o42), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b100111 + 0o110) + chr(49) + chr(1986 - 1935) + chr(0b10001 + 0o40), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x33' + '\062' + chr(0b110100 + 0o1), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + '\x31' + chr(0b10110 + 0o37) + '\x30', 0o10), ehT0Px3KOsy9(chr(2295 - 2247) + chr(111) + chr(0b110010) + chr(0b110110) + chr(2018 - 1965), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(1180 - 1131), 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(0b101100 + 0o7), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\063' + chr(0b10100 + 0o36) + chr(51), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\061' + '\x32' + chr(2500 - 2447), 5550 - 5542), ehT0Px3KOsy9('\060' + '\157' + chr(1028 - 978) + chr(0b110100) + chr(192 - 138), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x33' + '\x34' + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(111) + chr(0b110011) + '\061' + '\061', 0b1000), ehT0Px3KOsy9(chr(1381 - 1333) + '\x6f' + chr(0b100000 + 0o23) + chr(524 - 476), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b10011 + 0o134) + '\x36' + chr(1384 - 1333), 8), ehT0Px3KOsy9(chr(891 - 843) + '\157' + chr(0b110001) + chr(0b10000 + 0o46) + chr(0b100100 + 0o20), 33483 - 33475), ehT0Px3KOsy9(chr(1950 - 1902) + chr(9343 - 9232) + '\061' + chr(2329 - 2275), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(4156 - 4045) + chr(2469 - 2418) + chr(0b100011 + 0o20) + chr(2072 - 2022), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b11101 + 0o122) + '\066' + chr(49), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(3384 - 3273) + '\063' + chr(55) + chr(0b11100 + 0o31), 16656 - 16648), ehT0Px3KOsy9(chr(1323 - 1275) + chr(0b1000000 + 0o57) + '\x31' + '\061' + chr(0b110010), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(3124 - 3013) + chr(0b11001 + 0o32) + chr(1411 - 1359), 8), ehT0Px3KOsy9(chr(0b110000) + chr(1891 - 1780) + '\062' + chr(0b110010) + '\062', 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + '\157' + chr(53) + chr(0b110000), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xd4'), chr(320 - 220) + chr(101) + chr(879 - 780) + chr(0b1101111) + chr(0b1100100 + 0o0) + '\x65')(chr(117) + chr(0b1110100) + chr(0b1100110) + chr(45) + chr(0b0 + 0o70)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def OzbeBliZLXk3(ULnjp6D6efFH, OeWW0F1dBPRQ, SqiSOtYOqOJH, KPtq2czfwPS6=None, UFCqCPYQEkxy=None, EOCd1WZj2r_S=None, HQlygFZjk_Ts=ehT0Px3KOsy9('\060' + '\x6f' + '\060', 0o10), **M8EIoTs2GJXE):
(eRubm8FH879n,) = (xafqLlk3kkUe(NPPHb59961Bv(xafqLlk3kkUe(SXOLrMavuUCe(b'\x97\xfc\x1e\xabUM\x10\x87\xd9\xa7\xb4C>\xf8\xfc\x9dh'), chr(100) + chr(4395 - 4294) + chr(2624 - 2525) + chr(0b1101111) + chr(0b1100100) + '\145')(chr(117) + chr(4217 - 4101) + chr(0b1100110) + '\055' + '\070'), xafqLlk3kkUe(SXOLrMavuUCe(b'\x8a\xe4\x1a\xb7VV'), chr(251 - 151) + '\x65' + '\x63' + '\157' + chr(0b1100100) + chr(101))('\165' + chr(116) + chr(6877 - 6775) + chr(1355 - 1310) + '\x38')), xafqLlk3kkUe(SXOLrMavuUCe(b'\x8a\xe4\x1a\xb7VV'), '\x64' + chr(0b1100101) + chr(0b1100011) + '\x6f' + '\144' + '\x65')(chr(0b100000 + 0o125) + chr(3893 - 3777) + chr(102) + chr(0b101001 + 0o4) + '\070')),)
xafqLlk3kkUe(M8EIoTs2GJXE, xafqLlk3kkUe(SXOLrMavuUCe(b'\x89\xf8\x1e\xbf\\D\x05\x9e\xdc\xb1'), '\x64' + chr(0b1000010 + 0o43) + chr(99) + chr(0b1101111) + chr(0b1111 + 0o125) + chr(0b101010 + 0o73))('\165' + '\x74' + chr(0b1100110) + '\055' + chr(0b111000)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x9f\xf9\r\xbeZM\x08\x84\xc2\xb6'), chr(0b100001 + 0o103) + '\x65' + chr(99) + chr(0b1101111) + chr(0b1001 + 0o133) + chr(0b1100101))(chr(9374 - 9257) + '\164' + chr(102) + chr(1418 - 1373) + chr(0b111000)), xafqLlk3kkUe(SXOLrMavuUCe(b'\x94\xf2\x04\xbe'), chr(0b1100100) + chr(0b1100101) + chr(99) + '\x6f' + chr(0b1100100) + chr(0b1100101))(chr(4096 - 3979) + chr(0b1110100) + chr(102) + chr(0b101101) + chr(2806 - 2750)))
def Bg_IDOb9VeQN(N9UnmYvaW1pO, UFCqCPYQEkxy):
MNxMise_IlMm = N9UnmYvaW1pO[OeWW0F1dBPRQ].SPnCNu54H1db
DhgkejRtBdRL = N9UnmYvaW1pO[SqiSOtYOqOJH].SPnCNu54H1db
xafqLlk3kkUe(UFCqCPYQEkxy, xafqLlk3kkUe(SXOLrMavuUCe(b'\x89\xfe\x0b\xafMG\x16'), chr(0b1100100) + '\145' + chr(9678 - 9579) + '\x6f' + chr(0b1100100) + chr(0b1010000 + 0o25))(chr(752 - 635) + '\x74' + chr(4993 - 4891) + chr(0b1 + 0o54) + chr(56)))(MNxMise_IlMm, DhgkejRtBdRL, **M8EIoTs2GJXE)
xafqLlk3kkUe(UFCqCPYQEkxy, xafqLlk3kkUe(SXOLrMavuUCe(b'\x9d\xef\x03\xbf'), chr(0b1100100) + chr(0b111011 + 0o52) + chr(99) + '\x6f' + chr(0b1001101 + 0o27) + chr(101))('\x75' + chr(10553 - 10437) + chr(0b1100110) + chr(0b10101 + 0o30) + '\x38'))(HQlygFZjk_Ts)
if KPtq2czfwPS6 is not None:
IPypcZ53eNRW = U0P5py7sbftJ(Bg_IDOb9VeQN, ULnjp6D6efFH, by=KPtq2czfwPS6, figsize=EOCd1WZj2r_S, ax=UFCqCPYQEkxy)
else:
if UFCqCPYQEkxy is None:
IPypcZ53eNRW = eRubm8FH879n.figure()
UFCqCPYQEkxy = IPypcZ53eNRW.add_subplot(ehT0Px3KOsy9('\060' + chr(0b101100 + 0o103) + '\061' + chr(0b110101) + '\x37', 15590 - 15582))
else:
IPypcZ53eNRW = UFCqCPYQEkxy.get_figure()
Bg_IDOb9VeQN(ULnjp6D6efFH, UFCqCPYQEkxy)
xafqLlk3kkUe(UFCqCPYQEkxy, xafqLlk3kkUe(SXOLrMavuUCe(b'\x89\xf8\x1e\x84@N\x05\x89\xd5\xa9'), chr(100) + chr(0b1100101) + chr(0b1100011) + '\x6f' + chr(7678 - 7578) + '\x65')('\x75' + '\164' + '\146' + chr(830 - 785) + '\x38'))(wXDH9bYGsgMR(SqiSOtYOqOJH))
xafqLlk3kkUe(UFCqCPYQEkxy, xafqLlk3kkUe(SXOLrMavuUCe(b'\x89\xf8\x1e\x84AN\x05\x89\xd5\xa9'), chr(0b1100100) + '\x65' + chr(0b11111 + 0o104) + chr(9570 - 9459) + chr(1129 - 1029) + chr(1444 - 1343))(chr(0b10110 + 0o137) + '\x74' + '\x66' + chr(1529 - 1484) + chr(0b10110 + 0o42)))(wXDH9bYGsgMR(OeWW0F1dBPRQ))
xafqLlk3kkUe(UFCqCPYQEkxy, xafqLlk3kkUe(SXOLrMavuUCe(b'\x9d\xef\x03\xbf'), chr(100) + '\145' + chr(0b1100011) + chr(1165 - 1054) + '\x64' + chr(0b111011 + 0o52))(chr(0b1110101) + chr(0b1110100) + chr(0b1100110) + chr(1792 - 1747) + chr(0b10111 + 0o41)))(HQlygFZjk_Ts)
return IPypcZ53eNRW
|
pandas-dev/pandas
|
pandas/plotting/_core.py
|
hist_frame
|
def hist_frame(data, column=None, by=None, grid=True, xlabelsize=None,
xrot=None, ylabelsize=None, yrot=None, ax=None, sharex=False,
sharey=False, figsize=None, layout=None, bins=10, **kwds):
"""
Make a histogram of the DataFrame's.
A `histogram`_ is a representation of the distribution of data.
This function calls :meth:`matplotlib.pyplot.hist`, on each series in
the DataFrame, resulting in one histogram per column.
.. _histogram: https://en.wikipedia.org/wiki/Histogram
Parameters
----------
data : DataFrame
The pandas object holding the data.
column : string or sequence
If passed, will be used to limit data to a subset of columns.
by : object, optional
If passed, then used to form histograms for separate groups.
grid : bool, default True
Whether to show axis grid lines.
xlabelsize : int, default None
If specified changes the x-axis label size.
xrot : float, default None
Rotation of x axis labels. For example, a value of 90 displays the
x labels rotated 90 degrees clockwise.
ylabelsize : int, default None
If specified changes the y-axis label size.
yrot : float, default None
Rotation of y axis labels. For example, a value of 90 displays the
y labels rotated 90 degrees clockwise.
ax : Matplotlib axes object, default None
The axes to plot the histogram on.
sharex : bool, default True if ax is None else False
In case subplots=True, share x axis and set some x axis labels to
invisible; defaults to True if ax is None otherwise False if an ax
is passed in.
Note that passing in both an ax and sharex=True will alter all x axis
labels for all subplots in a figure.
sharey : bool, default False
In case subplots=True, share y axis and set some y axis labels to
invisible.
figsize : tuple
The size in inches of the figure to create. Uses the value in
`matplotlib.rcParams` by default.
layout : tuple, optional
Tuple of (rows, columns) for the layout of the histograms.
bins : integer or sequence, default 10
Number of histogram bins to be used. If an integer is given, bins + 1
bin edges are calculated and returned. If bins is a sequence, gives
bin edges, including left edge of first bin and right edge of last
bin. In this case, bins is returned unmodified.
**kwds
All other plotting keyword arguments to be passed to
:meth:`matplotlib.pyplot.hist`.
Returns
-------
matplotlib.AxesSubplot or numpy.ndarray of them
See Also
--------
matplotlib.pyplot.hist : Plot a histogram using matplotlib.
Examples
--------
.. plot::
:context: close-figs
This example draws a histogram based on the length and width of
some animals, displayed in three bins
>>> df = pd.DataFrame({
... 'length': [1.5, 0.5, 1.2, 0.9, 3],
... 'width': [0.7, 0.2, 0.15, 0.2, 1.1]
... }, index= ['pig', 'rabbit', 'duck', 'chicken', 'horse'])
>>> hist = df.hist(bins=3)
"""
_raise_if_no_mpl()
_converter._WARN = False
if by is not None:
axes = grouped_hist(data, column=column, by=by, ax=ax, grid=grid,
figsize=figsize, sharex=sharex, sharey=sharey,
layout=layout, bins=bins, xlabelsize=xlabelsize,
xrot=xrot, ylabelsize=ylabelsize,
yrot=yrot, **kwds)
return axes
if column is not None:
if not isinstance(column, (list, np.ndarray, ABCIndexClass)):
column = [column]
data = data[column]
data = data._get_numeric_data()
naxes = len(data.columns)
fig, axes = _subplots(naxes=naxes, ax=ax, squeeze=False,
sharex=sharex, sharey=sharey, figsize=figsize,
layout=layout)
_axes = _flatten(axes)
for i, col in enumerate(com.try_sort(data.columns)):
ax = _axes[i]
ax.hist(data[col].dropna().values, bins=bins, **kwds)
ax.set_title(col)
ax.grid(grid)
_set_ticks_props(axes, xlabelsize=xlabelsize, xrot=xrot,
ylabelsize=ylabelsize, yrot=yrot)
fig.subplots_adjust(wspace=0.3, hspace=0.3)
return axes
|
python
|
def hist_frame(data, column=None, by=None, grid=True, xlabelsize=None,
xrot=None, ylabelsize=None, yrot=None, ax=None, sharex=False,
sharey=False, figsize=None, layout=None, bins=10, **kwds):
"""
Make a histogram of the DataFrame's.
A `histogram`_ is a representation of the distribution of data.
This function calls :meth:`matplotlib.pyplot.hist`, on each series in
the DataFrame, resulting in one histogram per column.
.. _histogram: https://en.wikipedia.org/wiki/Histogram
Parameters
----------
data : DataFrame
The pandas object holding the data.
column : string or sequence
If passed, will be used to limit data to a subset of columns.
by : object, optional
If passed, then used to form histograms for separate groups.
grid : bool, default True
Whether to show axis grid lines.
xlabelsize : int, default None
If specified changes the x-axis label size.
xrot : float, default None
Rotation of x axis labels. For example, a value of 90 displays the
x labels rotated 90 degrees clockwise.
ylabelsize : int, default None
If specified changes the y-axis label size.
yrot : float, default None
Rotation of y axis labels. For example, a value of 90 displays the
y labels rotated 90 degrees clockwise.
ax : Matplotlib axes object, default None
The axes to plot the histogram on.
sharex : bool, default True if ax is None else False
In case subplots=True, share x axis and set some x axis labels to
invisible; defaults to True if ax is None otherwise False if an ax
is passed in.
Note that passing in both an ax and sharex=True will alter all x axis
labels for all subplots in a figure.
sharey : bool, default False
In case subplots=True, share y axis and set some y axis labels to
invisible.
figsize : tuple
The size in inches of the figure to create. Uses the value in
`matplotlib.rcParams` by default.
layout : tuple, optional
Tuple of (rows, columns) for the layout of the histograms.
bins : integer or sequence, default 10
Number of histogram bins to be used. If an integer is given, bins + 1
bin edges are calculated and returned. If bins is a sequence, gives
bin edges, including left edge of first bin and right edge of last
bin. In this case, bins is returned unmodified.
**kwds
All other plotting keyword arguments to be passed to
:meth:`matplotlib.pyplot.hist`.
Returns
-------
matplotlib.AxesSubplot or numpy.ndarray of them
See Also
--------
matplotlib.pyplot.hist : Plot a histogram using matplotlib.
Examples
--------
.. plot::
:context: close-figs
This example draws a histogram based on the length and width of
some animals, displayed in three bins
>>> df = pd.DataFrame({
... 'length': [1.5, 0.5, 1.2, 0.9, 3],
... 'width': [0.7, 0.2, 0.15, 0.2, 1.1]
... }, index= ['pig', 'rabbit', 'duck', 'chicken', 'horse'])
>>> hist = df.hist(bins=3)
"""
_raise_if_no_mpl()
_converter._WARN = False
if by is not None:
axes = grouped_hist(data, column=column, by=by, ax=ax, grid=grid,
figsize=figsize, sharex=sharex, sharey=sharey,
layout=layout, bins=bins, xlabelsize=xlabelsize,
xrot=xrot, ylabelsize=ylabelsize,
yrot=yrot, **kwds)
return axes
if column is not None:
if not isinstance(column, (list, np.ndarray, ABCIndexClass)):
column = [column]
data = data[column]
data = data._get_numeric_data()
naxes = len(data.columns)
fig, axes = _subplots(naxes=naxes, ax=ax, squeeze=False,
sharex=sharex, sharey=sharey, figsize=figsize,
layout=layout)
_axes = _flatten(axes)
for i, col in enumerate(com.try_sort(data.columns)):
ax = _axes[i]
ax.hist(data[col].dropna().values, bins=bins, **kwds)
ax.set_title(col)
ax.grid(grid)
_set_ticks_props(axes, xlabelsize=xlabelsize, xrot=xrot,
ylabelsize=ylabelsize, yrot=yrot)
fig.subplots_adjust(wspace=0.3, hspace=0.3)
return axes
|
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Make a histogram of the DataFrame's.
A `histogram`_ is a representation of the distribution of data.
This function calls :meth:`matplotlib.pyplot.hist`, on each series in
the DataFrame, resulting in one histogram per column.
.. _histogram: https://en.wikipedia.org/wiki/Histogram
Parameters
----------
data : DataFrame
The pandas object holding the data.
column : string or sequence
If passed, will be used to limit data to a subset of columns.
by : object, optional
If passed, then used to form histograms for separate groups.
grid : bool, default True
Whether to show axis grid lines.
xlabelsize : int, default None
If specified changes the x-axis label size.
xrot : float, default None
Rotation of x axis labels. For example, a value of 90 displays the
x labels rotated 90 degrees clockwise.
ylabelsize : int, default None
If specified changes the y-axis label size.
yrot : float, default None
Rotation of y axis labels. For example, a value of 90 displays the
y labels rotated 90 degrees clockwise.
ax : Matplotlib axes object, default None
The axes to plot the histogram on.
sharex : bool, default True if ax is None else False
In case subplots=True, share x axis and set some x axis labels to
invisible; defaults to True if ax is None otherwise False if an ax
is passed in.
Note that passing in both an ax and sharex=True will alter all x axis
labels for all subplots in a figure.
sharey : bool, default False
In case subplots=True, share y axis and set some y axis labels to
invisible.
figsize : tuple
The size in inches of the figure to create. Uses the value in
`matplotlib.rcParams` by default.
layout : tuple, optional
Tuple of (rows, columns) for the layout of the histograms.
bins : integer or sequence, default 10
Number of histogram bins to be used. If an integer is given, bins + 1
bin edges are calculated and returned. If bins is a sequence, gives
bin edges, including left edge of first bin and right edge of last
bin. In this case, bins is returned unmodified.
**kwds
All other plotting keyword arguments to be passed to
:meth:`matplotlib.pyplot.hist`.
Returns
-------
matplotlib.AxesSubplot or numpy.ndarray of them
See Also
--------
matplotlib.pyplot.hist : Plot a histogram using matplotlib.
Examples
--------
.. plot::
:context: close-figs
This example draws a histogram based on the length and width of
some animals, displayed in three bins
>>> df = pd.DataFrame({
... 'length': [1.5, 0.5, 1.2, 0.9, 3],
... 'width': [0.7, 0.2, 0.15, 0.2, 1.1]
... }, index= ['pig', 'rabbit', 'duck', 'chicken', 'horse'])
>>> hist = df.hist(bins=3)
|
[
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"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/plotting/_core.py#L2331-L2443
|
train
|
This function creates a histogram of the data in a DataFrame.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b11101 + 0o23) + chr(0b111110 + 0o61) + chr(0b110001) + '\x31' + chr(55), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + '\062' + chr(0b110011) + chr(2707 - 2653), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101011 + 0o4) + chr(0b100110 + 0o13) + chr(1745 - 1691), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(50) + chr(0b11000 + 0o32) + chr(52), 0b1000), ehT0Px3KOsy9(chr(0b1001 + 0o47) + '\157' + chr(0b111 + 0o53) + chr(0b110011) + chr(0b110011 + 0o2), 0o10), ehT0Px3KOsy9(chr(0b1111 + 0o41) + '\x6f' + chr(0b101110 + 0o6) + '\x36', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1010101 + 0o32) + chr(0b111 + 0o53) + chr(0b100 + 0o60) + '\063', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(50) + chr(0b110110) + '\067', 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + '\062' + '\063' + chr(428 - 373), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(6997 - 6886) + chr(0b110001) + chr(1671 - 1621) + chr(52), 0o10), ehT0Px3KOsy9(chr(0b101100 + 0o4) + chr(8233 - 8122) + chr(51) + chr(1673 - 1624) + chr(0b111 + 0o51), 0b1000), ehT0Px3KOsy9(chr(0b1 + 0o57) + chr(0b1101111) + chr(0b110001) + '\066' + chr(2021 - 1972), 20875 - 20867), ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(1327 - 1216) + chr(0b10 + 0o61) + chr(75 - 27) + chr(0b10111 + 0o31), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110010) + '\062', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x32' + chr(52) + chr(0b100 + 0o60), 36149 - 36141), ehT0Px3KOsy9(chr(1022 - 974) + chr(0b11011 + 0o124) + chr(0b10010 + 0o40) + chr(2536 - 2481) + chr(0b101111 + 0o5), 0b1000), ehT0Px3KOsy9('\x30' + chr(2613 - 2502) + '\063' + '\062' + chr(0b100010 + 0o25), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1000111 + 0o50) + chr(0b1000 + 0o57) + chr(54), 20996 - 20988), ehT0Px3KOsy9('\x30' + chr(0b1001000 + 0o47) + chr(0b10110 + 0o34) + '\061' + '\066', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\063' + chr(54) + '\x36', 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(103 - 54) + '\062', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(1944 - 1833) + '\063' + chr(0b111 + 0o60) + chr(0b110000), 0o10), ehT0Px3KOsy9(chr(188 - 140) + '\157' + chr(0b110010) + chr(51) + chr(0b110000 + 0o3), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(51) + '\067' + chr(54), 0o10), ehT0Px3KOsy9('\060' + '\157' + '\x32' + chr(0b11001 + 0o31), 8), ehT0Px3KOsy9(chr(973 - 925) + '\x6f' + '\061' + chr(54) + chr(332 - 278), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b100101 + 0o16) + chr(0b110000 + 0o7) + '\x31', 0o10), ehT0Px3KOsy9('\060' + chr(111) + '\x35' + '\062', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x32' + chr(52) + chr(1304 - 1249), 3189 - 3181), ehT0Px3KOsy9(chr(1203 - 1155) + chr(0b101101 + 0o102) + '\x33' + chr(50) + chr(1272 - 1222), 0o10), ehT0Px3KOsy9(chr(0b11100 + 0o24) + chr(0b1100011 + 0o14) + chr(896 - 845) + '\067' + chr(50), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\063' + '\066' + chr(1003 - 953), ord("\x08")), ehT0Px3KOsy9(chr(0b11110 + 0o22) + '\x6f' + chr(50) + chr(52) + chr(0b10111 + 0o32), 39426 - 39418), ehT0Px3KOsy9(chr(0b0 + 0o60) + chr(0b1101100 + 0o3) + chr(0b100010 + 0o21) + '\x30' + chr(0b110001), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b111010 + 0o65) + chr(0b110011) + '\064' + chr(0b100111 + 0o17), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x33' + '\x32' + chr(1300 - 1247), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(498 - 447) + chr(54) + chr(0b0 + 0o64), 0b1000), ehT0Px3KOsy9('\x30' + chr(7627 - 7516) + '\x31' + chr(55) + '\064', 65187 - 65179), ehT0Px3KOsy9(chr(48) + chr(6744 - 6633) + chr(0b100110 + 0o15) + '\x36' + '\x37', 0b1000), ehT0Px3KOsy9(chr(360 - 312) + chr(0b1101111) + chr(2155 - 2106) + chr(671 - 622) + '\x36', 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + '\x6f' + chr(1472 - 1419) + chr(1845 - 1797), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'a'), chr(0b1100100) + chr(0b101000 + 0o75) + chr(0b1100011) + '\157' + '\144' + chr(101))(chr(117) + '\x74' + '\x66' + chr(1310 - 1265) + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def vPaS7UG5APlB(ULnjp6D6efFH, Pl0JgJDv0QqN=None, KPtq2czfwPS6=None, HQlygFZjk_Ts=ehT0Px3KOsy9('\060' + '\157' + chr(0b100000 + 0o21), 0b1000), O6IqtluwDsBM=None, EkdxULuB9H6Z=None, mpU8c8_lbVWZ=None, bE_fxV0mOBtM=None, UFCqCPYQEkxy=None, EXJVTwDkeUM0=ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110000), 29063 - 29055), MfpZhnWx798V=ehT0Px3KOsy9(chr(48) + chr(3528 - 3417) + chr(1174 - 1126), 8), EOCd1WZj2r_S=None, HDH7OEwZuDah=None, KQ4BDFoY4RVo=ehT0Px3KOsy9('\060' + '\x6f' + chr(49) + chr(0b11000 + 0o32), 8), **ClrkdavlbKME):
J0iiixqYX_fZ()
Kt4weVQLYz5A.mn5QZuyPrYP0 = ehT0Px3KOsy9('\060' + chr(0b111111 + 0o60) + chr(2065 - 2017), 8)
if KPtq2czfwPS6 is not None:
gJ3Tbhvvj8Ru = muROo5u_drt2(ULnjp6D6efFH, column=Pl0JgJDv0QqN, by=KPtq2czfwPS6, ax=UFCqCPYQEkxy, grid=HQlygFZjk_Ts, figsize=EOCd1WZj2r_S, sharex=EXJVTwDkeUM0, sharey=MfpZhnWx798V, layout=HDH7OEwZuDah, bins=KQ4BDFoY4RVo, xlabelsize=O6IqtluwDsBM, xrot=EkdxULuB9H6Z, ylabelsize=mpU8c8_lbVWZ, yrot=bE_fxV0mOBtM, **ClrkdavlbKME)
return gJ3Tbhvvj8Ru
if Pl0JgJDv0QqN is not None:
if not PlSM16l2KDPD(Pl0JgJDv0QqN, (YyaZ4tpXu4lf, xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'!\xfao\xe6\xefG\xda'), chr(100) + chr(0b1100101) + '\x63' + '\157' + chr(100) + '\145')(chr(0b1110101) + '\164' + chr(0b111100 + 0o52) + chr(0b101101) + chr(0b100000 + 0o30))), zLJfq2_IbJjZ)):
Pl0JgJDv0QqN = [Pl0JgJDv0QqN]
ULnjp6D6efFH = ULnjp6D6efFH[Pl0JgJDv0QqN]
ULnjp6D6efFH = ULnjp6D6efFH._get_numeric_data()
YLWhYbaD7hv4 = c2A0yzQpDQB3(ULnjp6D6efFH.qKlXBtn3PKy4)
(IPypcZ53eNRW, gJ3Tbhvvj8Ru) = NJ7UFoibKFcf(naxes=YLWhYbaD7hv4, ax=UFCqCPYQEkxy, squeeze=ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110000), 8), sharex=EXJVTwDkeUM0, sharey=MfpZhnWx798V, figsize=EOCd1WZj2r_S, layout=HDH7OEwZuDah)
JQRFi7acKdjR = rH_ZFwwirodI(gJ3Tbhvvj8Ru)
for (WVxHKyX45z_L, Qa2uSJqQPT3w) in YlkZvXL8qwsX(xafqLlk3kkUe(CDQ27PYjPxZQ, xafqLlk3kkUe(SXOLrMavuUCe(b';\xecw\xcb\xeeI\xd1\xc3'), chr(100) + chr(0b1000100 + 0o41) + chr(99) + '\x6f' + chr(0b1100100) + '\145')(chr(0b1000111 + 0o56) + '\164' + chr(3403 - 3301) + '\055' + chr(2331 - 2275)))(xafqLlk3kkUe(ULnjp6D6efFH, xafqLlk3kkUe(SXOLrMavuUCe(b'>\xd5b\xcc\xdfR\xcd\x84\xcf\x1f\xb1E'), chr(0b10001 + 0o123) + chr(0b1100101) + chr(99) + '\x6f' + chr(3029 - 2929) + chr(101))(chr(0b1110101) + chr(10086 - 9970) + chr(0b1000011 + 0o43) + '\x2d' + chr(0b111000 + 0o0))))):
UFCqCPYQEkxy = JQRFi7acKdjR[WVxHKyX45z_L]
xafqLlk3kkUe(UFCqCPYQEkxy, xafqLlk3kkUe(SXOLrMavuUCe(b"'\xf7}\xe0"), chr(100) + chr(0b1100100 + 0o1) + chr(9080 - 8981) + '\157' + '\144' + chr(0b1100101))('\x75' + chr(116) + chr(102) + '\x2d' + chr(56)))(xafqLlk3kkUe(ULnjp6D6efFH[Qa2uSJqQPT3w].dropna(), xafqLlk3kkUe(SXOLrMavuUCe(b'\x1c\xce`\xd7\xd3S\x96\x83\xd7e\xac\x13'), chr(0b1100100) + '\145' + chr(2547 - 2448) + '\x6f' + '\x64' + chr(0b1100101))('\x75' + chr(3462 - 3346) + '\146' + chr(1064 - 1019) + chr(1194 - 1138))), bins=KQ4BDFoY4RVo, **ClrkdavlbKME)
xafqLlk3kkUe(UFCqCPYQEkxy, xafqLlk3kkUe(SXOLrMavuUCe(b'<\xfbz\xcb\xe9O\xd7\xdb\xfa'), chr(0b111110 + 0o46) + chr(0b1100101) + '\x63' + chr(0b11110 + 0o121) + chr(100) + chr(101))(chr(117) + chr(0b1100111 + 0o15) + chr(0b1100110) + chr(414 - 369) + '\070'))(Qa2uSJqQPT3w)
xafqLlk3kkUe(UFCqCPYQEkxy, xafqLlk3kkUe(SXOLrMavuUCe(b'(\xecg\xf0'), chr(7285 - 7185) + chr(101) + chr(3711 - 3612) + chr(0b1101111) + chr(0b1100100) + chr(101))(chr(0b1110101) + chr(0b1110100) + chr(102) + '\x2d' + chr(56)))(HQlygFZjk_Ts)
Y8oTx2_Zkajn(gJ3Tbhvvj8Ru, xlabelsize=O6IqtluwDsBM, xrot=EkdxULuB9H6Z, ylabelsize=mpU8c8_lbVWZ, yrot=bE_fxV0mOBtM)
xafqLlk3kkUe(IPypcZ53eNRW, xafqLlk3kkUe(SXOLrMavuUCe(b'<\xebl\xe4\xf1I\xd7\xc4\xc05\xac\x1b\xb5a\xd0'), chr(0b1100100) + chr(0b1000101 + 0o40) + chr(99) + '\x6f' + chr(0b1100100) + chr(9381 - 9280))('\x75' + chr(0b1110100) + chr(0b1100110) + chr(45) + chr(0b111000)))(wspace=0.3, hspace=0.3)
return gJ3Tbhvvj8Ru
|
pandas-dev/pandas
|
pandas/plotting/_core.py
|
hist_series
|
def hist_series(self, by=None, ax=None, grid=True, xlabelsize=None,
xrot=None, ylabelsize=None, yrot=None, figsize=None,
bins=10, **kwds):
"""
Draw histogram of the input series using matplotlib.
Parameters
----------
by : object, optional
If passed, then used to form histograms for separate groups
ax : matplotlib axis object
If not passed, uses gca()
grid : bool, default True
Whether to show axis grid lines
xlabelsize : int, default None
If specified changes the x-axis label size
xrot : float, default None
rotation of x axis labels
ylabelsize : int, default None
If specified changes the y-axis label size
yrot : float, default None
rotation of y axis labels
figsize : tuple, default None
figure size in inches by default
bins : integer or sequence, default 10
Number of histogram bins to be used. If an integer is given, bins + 1
bin edges are calculated and returned. If bins is a sequence, gives
bin edges, including left edge of first bin and right edge of last
bin. In this case, bins is returned unmodified.
bins : integer, default 10
Number of histogram bins to be used
`**kwds` : keywords
To be passed to the actual plotting function
See Also
--------
matplotlib.axes.Axes.hist : Plot a histogram using matplotlib.
"""
import matplotlib.pyplot as plt
if by is None:
if kwds.get('layout', None) is not None:
raise ValueError("The 'layout' keyword is not supported when "
"'by' is None")
# hack until the plotting interface is a bit more unified
fig = kwds.pop('figure', plt.gcf() if plt.get_fignums() else
plt.figure(figsize=figsize))
if (figsize is not None and tuple(figsize) !=
tuple(fig.get_size_inches())):
fig.set_size_inches(*figsize, forward=True)
if ax is None:
ax = fig.gca()
elif ax.get_figure() != fig:
raise AssertionError('passed axis not bound to passed figure')
values = self.dropna().values
ax.hist(values, bins=bins, **kwds)
ax.grid(grid)
axes = np.array([ax])
_set_ticks_props(axes, xlabelsize=xlabelsize, xrot=xrot,
ylabelsize=ylabelsize, yrot=yrot)
else:
if 'figure' in kwds:
raise ValueError("Cannot pass 'figure' when using the "
"'by' argument, since a new 'Figure' instance "
"will be created")
axes = grouped_hist(self, by=by, ax=ax, grid=grid, figsize=figsize,
bins=bins, xlabelsize=xlabelsize, xrot=xrot,
ylabelsize=ylabelsize, yrot=yrot, **kwds)
if hasattr(axes, 'ndim'):
if axes.ndim == 1 and len(axes) == 1:
return axes[0]
return axes
|
python
|
def hist_series(self, by=None, ax=None, grid=True, xlabelsize=None,
xrot=None, ylabelsize=None, yrot=None, figsize=None,
bins=10, **kwds):
"""
Draw histogram of the input series using matplotlib.
Parameters
----------
by : object, optional
If passed, then used to form histograms for separate groups
ax : matplotlib axis object
If not passed, uses gca()
grid : bool, default True
Whether to show axis grid lines
xlabelsize : int, default None
If specified changes the x-axis label size
xrot : float, default None
rotation of x axis labels
ylabelsize : int, default None
If specified changes the y-axis label size
yrot : float, default None
rotation of y axis labels
figsize : tuple, default None
figure size in inches by default
bins : integer or sequence, default 10
Number of histogram bins to be used. If an integer is given, bins + 1
bin edges are calculated and returned. If bins is a sequence, gives
bin edges, including left edge of first bin and right edge of last
bin. In this case, bins is returned unmodified.
bins : integer, default 10
Number of histogram bins to be used
`**kwds` : keywords
To be passed to the actual plotting function
See Also
--------
matplotlib.axes.Axes.hist : Plot a histogram using matplotlib.
"""
import matplotlib.pyplot as plt
if by is None:
if kwds.get('layout', None) is not None:
raise ValueError("The 'layout' keyword is not supported when "
"'by' is None")
# hack until the plotting interface is a bit more unified
fig = kwds.pop('figure', plt.gcf() if plt.get_fignums() else
plt.figure(figsize=figsize))
if (figsize is not None and tuple(figsize) !=
tuple(fig.get_size_inches())):
fig.set_size_inches(*figsize, forward=True)
if ax is None:
ax = fig.gca()
elif ax.get_figure() != fig:
raise AssertionError('passed axis not bound to passed figure')
values = self.dropna().values
ax.hist(values, bins=bins, **kwds)
ax.grid(grid)
axes = np.array([ax])
_set_ticks_props(axes, xlabelsize=xlabelsize, xrot=xrot,
ylabelsize=ylabelsize, yrot=yrot)
else:
if 'figure' in kwds:
raise ValueError("Cannot pass 'figure' when using the "
"'by' argument, since a new 'Figure' instance "
"will be created")
axes = grouped_hist(self, by=by, ax=ax, grid=grid, figsize=figsize,
bins=bins, xlabelsize=xlabelsize, xrot=xrot,
ylabelsize=ylabelsize, yrot=yrot, **kwds)
if hasattr(axes, 'ndim'):
if axes.ndim == 1 and len(axes) == 1:
return axes[0]
return axes
|
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] |
Draw histogram of the input series using matplotlib.
Parameters
----------
by : object, optional
If passed, then used to form histograms for separate groups
ax : matplotlib axis object
If not passed, uses gca()
grid : bool, default True
Whether to show axis grid lines
xlabelsize : int, default None
If specified changes the x-axis label size
xrot : float, default None
rotation of x axis labels
ylabelsize : int, default None
If specified changes the y-axis label size
yrot : float, default None
rotation of y axis labels
figsize : tuple, default None
figure size in inches by default
bins : integer or sequence, default 10
Number of histogram bins to be used. If an integer is given, bins + 1
bin edges are calculated and returned. If bins is a sequence, gives
bin edges, including left edge of first bin and right edge of last
bin. In this case, bins is returned unmodified.
bins : integer, default 10
Number of histogram bins to be used
`**kwds` : keywords
To be passed to the actual plotting function
See Also
--------
matplotlib.axes.Axes.hist : Plot a histogram using matplotlib.
|
[
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"of",
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"series",
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"matplotlib",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/plotting/_core.py#L2446-L2521
|
train
|
Plots a histogram of the input series using matplotlib.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(1512 - 1464) + '\157' + chr(0b100100 + 0o23) + chr(0b101001 + 0o7), 3478 - 3470), ehT0Px3KOsy9('\x30' + chr(111) + '\061' + chr(1016 - 965) + chr(0b110111), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + '\x36' + chr(1093 - 1043), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + '\063' + '\060' + chr(0b110011), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(50) + chr(50) + '\x32', 9092 - 9084), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110011) + chr(0b110111), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(50) + chr(55) + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(228 - 179) + chr(2409 - 2359) + '\x36', 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110001) + '\x34' + chr(1304 - 1254), ord("\x08")), ehT0Px3KOsy9(chr(0b10010 + 0o36) + chr(2542 - 2431) + '\x31' + '\061' + '\064', 52188 - 52180), ehT0Px3KOsy9(chr(0b1101 + 0o43) + '\x6f' + chr(0b11 + 0o56) + chr(204 - 156) + chr(236 - 181), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b111 + 0o53) + chr(51) + '\067', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b100111 + 0o14) + chr(0b11110 + 0o26) + chr(2499 - 2445), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(9081 - 8970) + chr(1559 - 1508) + chr(516 - 464) + chr(54), 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b1011110 + 0o21) + chr(894 - 844) + '\x35' + '\066', 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(51) + chr(1275 - 1222) + chr(589 - 540), ord("\x08")), ehT0Px3KOsy9(chr(0b11 + 0o55) + '\x6f' + '\061' + chr(940 - 889) + '\x32', 37453 - 37445), ehT0Px3KOsy9(chr(1254 - 1206) + chr(0b101011 + 0o104) + chr(50) + chr(1901 - 1849) + chr(49), 0b1000), ehT0Px3KOsy9(chr(1464 - 1416) + chr(111) + '\062', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101001 + 0o6) + '\x36' + chr(48), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110110) + chr(54), 0b1000), ehT0Px3KOsy9(chr(323 - 275) + chr(0b1101111) + '\062' + '\x35', 0o10), ehT0Px3KOsy9(chr(48) + chr(6264 - 6153) + chr(1561 - 1507), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b100001 + 0o116) + '\061' + chr(53), 35068 - 35060), ehT0Px3KOsy9(chr(0b100000 + 0o20) + '\157' + chr(558 - 507) + '\066', ord("\x08")), ehT0Px3KOsy9(chr(1726 - 1678) + chr(9248 - 9137) + chr(0b1 + 0o62) + chr(0b110001) + '\x33', 0o10), ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(0b1001001 + 0o46) + '\062' + '\062' + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(48) + chr(11809 - 11698) + chr(49), 0b1000), ehT0Px3KOsy9(chr(1155 - 1107) + chr(0b1101111) + chr(0b11010 + 0o30) + chr(0b110101) + '\x31', 59651 - 59643), ehT0Px3KOsy9(chr(0b110000) + chr(780 - 669) + chr(2436 - 2386) + chr(1171 - 1121) + '\x36', ord("\x08")), ehT0Px3KOsy9(chr(1272 - 1224) + chr(10286 - 10175) + '\x31' + chr(834 - 782) + chr(460 - 405), 0o10), ehT0Px3KOsy9(chr(484 - 436) + chr(0b111010 + 0o65) + chr(0b1000 + 0o51) + chr(48), 0o10), ehT0Px3KOsy9(chr(0b11 + 0o55) + chr(5978 - 5867) + chr(0b110101) + '\x33', ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(2134 - 2084) + '\x35', 8), ehT0Px3KOsy9('\060' + '\157' + chr(0b1 + 0o61) + '\060' + chr(0b10111 + 0o37), 65490 - 65482), ehT0Px3KOsy9(chr(716 - 668) + '\x6f' + '\x37' + chr(53), 18642 - 18634), ehT0Px3KOsy9('\060' + chr(111) + chr(53) + chr(0b110011), 8), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110011) + '\061' + chr(0b110010), 0o10), ehT0Px3KOsy9('\x30' + chr(0b111001 + 0o66) + '\x32' + '\x33' + '\061', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\063' + chr(0b110001) + chr(0b110110), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + chr(8343 - 8232) + chr(2133 - 2080) + chr(1162 - 1114), 20723 - 20715)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x16'), '\x64' + '\x65' + chr(99) + chr(6178 - 6067) + chr(7627 - 7527) + chr(0b1010110 + 0o17))(chr(0b10000 + 0o145) + chr(0b1000000 + 0o64) + '\x66' + chr(0b1011 + 0o42) + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def fdjiVoHz9XcC(oVre8I6UXc3b, KPtq2czfwPS6=None, UFCqCPYQEkxy=None, HQlygFZjk_Ts=ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x31', 8), O6IqtluwDsBM=None, EkdxULuB9H6Z=None, mpU8c8_lbVWZ=None, bE_fxV0mOBtM=None, EOCd1WZj2r_S=None, KQ4BDFoY4RVo=ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(49) + chr(50), ord("\x08")), **ClrkdavlbKME):
(eRubm8FH879n,) = (xafqLlk3kkUe(NPPHb59961Bv(xafqLlk3kkUe(SXOLrMavuUCe(b'U>F\xb3\xfep\xca:\x0b.i\xef\x9f\x96\xc2\x86.'), chr(0b1100100) + chr(0b1100101) + chr(0b1100011) + '\157' + '\144' + chr(101))(chr(0b1110101) + '\164' + chr(196 - 94) + chr(0b101101) + chr(0b110100 + 0o4)), xafqLlk3kkUe(SXOLrMavuUCe(b'H&B\xaf\xfdk'), chr(100) + chr(0b1011011 + 0o12) + chr(0b11010 + 0o111) + chr(0b10110 + 0o131) + '\x64' + '\145')(chr(10160 - 10043) + '\x74' + chr(102) + chr(1981 - 1936) + '\x38')), xafqLlk3kkUe(SXOLrMavuUCe(b'H&B\xaf\xfdk'), chr(100) + chr(0b1101 + 0o130) + '\143' + chr(7518 - 7407) + chr(100) + chr(101))(chr(0b10101 + 0o140) + chr(0b1110100) + chr(102) + chr(45) + chr(0b110011 + 0o5))),)
if KPtq2czfwPS6 is None:
if xafqLlk3kkUe(ClrkdavlbKME, xafqLlk3kkUe(SXOLrMavuUCe(b'_:F'), chr(0b111110 + 0o46) + chr(101) + '\143' + '\x6f' + '\x64' + '\x65')(chr(0b1100011 + 0o22) + chr(10702 - 10586) + chr(0b1100110) + chr(45) + chr(477 - 421)))(xafqLlk3kkUe(SXOLrMavuUCe(b'T>K\xac\xe7k'), '\144' + '\145' + chr(2603 - 2504) + chr(0b1101111) + '\x64' + chr(0b1100011 + 0o2))(chr(0b1110101) + chr(116) + chr(102) + '\x2d' + chr(56)), None) is not None:
raise q1QCh3W88sgk(xafqLlk3kkUe(SXOLrMavuUCe(b'l7W\xe3\xb5s\xdf/\r93\xb8\xc6\x8d\xcb\x90-\xcepT\x16|u-p\xa4\xe3!\xda\xe3\x17xDg\xf2XO\xea\xee\xa6]1\x12\xe4\xf0f\x99v\x0b?g\xd1\x89\x88\xcb'), chr(1826 - 1726) + chr(0b110100 + 0o61) + chr(99) + chr(7772 - 7661) + chr(0b1100100) + chr(101))(chr(7828 - 7711) + '\164' + chr(0b1100110) + chr(0b101101) + '\070'))
IPypcZ53eNRW = ClrkdavlbKME.pop(xafqLlk3kkUe(SXOLrMavuUCe(b'^6U\xb6\xe0z'), chr(2986 - 2886) + chr(101) + chr(0b11010 + 0o111) + chr(0b1101111) + chr(0b1010100 + 0o20) + '\145')(chr(6423 - 6306) + chr(116) + chr(102) + chr(0b100011 + 0o12) + chr(0b100100 + 0o24)), eRubm8FH879n.gcf() if eRubm8FH879n.get_fignums() else eRubm8FH879n.figure(figsize=EOCd1WZj2r_S))
if EOCd1WZj2r_S is not None and KNyTy8rYcwji(EOCd1WZj2r_S) != KNyTy8rYcwji(xafqLlk3kkUe(IPypcZ53eNRW, xafqLlk3kkUe(SXOLrMavuUCe(b'_:F\x9c\xe1v\xc43=%)\xfc\x8e\x83\xdd'), '\x64' + chr(101) + '\x63' + chr(0b100100 + 0o113) + '\144' + chr(0b111000 + 0o55))('\165' + chr(116) + '\146' + '\x2d' + '\x38'))()):
xafqLlk3kkUe(IPypcZ53eNRW, xafqLlk3kkUe(SXOLrMavuUCe(b'K:F\x9c\xe1v\xc43=%)\xfc\x8e\x83\xdd'), chr(0b1000101 + 0o37) + chr(0b1100101) + chr(0b1100011) + chr(0b1101111) + chr(0b101 + 0o137) + '\145')(chr(536 - 419) + chr(0b1110100) + '\146' + '\055' + chr(0b11111 + 0o31)))(*EOCd1WZj2r_S, forward=ehT0Px3KOsy9(chr(0b101010 + 0o6) + chr(0b11110 + 0o121) + chr(0b11101 + 0o24), 8))
if UFCqCPYQEkxy is None:
UFCqCPYQEkxy = IPypcZ53eNRW.gca()
elif xafqLlk3kkUe(UFCqCPYQEkxy, xafqLlk3kkUe(SXOLrMavuUCe(b'_:F\x9c\xf4v\xd9#\x10)'), '\144' + chr(3979 - 3878) + chr(0b1011001 + 0o12) + '\157' + chr(0b1001010 + 0o32) + chr(4952 - 4851))('\x75' + chr(0b1110100) + chr(2244 - 2142) + '\x2d' + chr(0b100 + 0o64)))() != IPypcZ53eNRW:
raise vcEHXBQXuDuh(xafqLlk3kkUe(SXOLrMavuUCe(b'H>A\xb0\xf7{\x9e7\x1a%4\xbf\x88\x89\xda\xc98\xcew^R5rb>\xbb\xf6r\xda\xf3\x03(M|\xe1HY\xaf'), '\144' + chr(8733 - 8632) + '\143' + chr(111) + chr(0b1000111 + 0o35) + '\x65')(chr(5401 - 5284) + '\164' + '\146' + chr(0b101101) + chr(56)))
SPnCNu54H1db = oVre8I6UXc3b.dropna().SPnCNu54H1db
xafqLlk3kkUe(UFCqCPYQEkxy, xafqLlk3kkUe(SXOLrMavuUCe(b'P6A\xb7'), chr(0b1100100) + chr(1182 - 1081) + chr(0b1100011) + chr(111) + chr(0b1100100) + chr(7143 - 7042))(chr(0b1000110 + 0o57) + chr(5887 - 5771) + chr(102) + chr(45) + chr(56)))(SPnCNu54H1db, bins=KQ4BDFoY4RVo, **ClrkdavlbKME)
xafqLlk3kkUe(UFCqCPYQEkxy, xafqLlk3kkUe(SXOLrMavuUCe(b'_-[\xa7'), chr(100) + '\145' + chr(2708 - 2609) + '\x6f' + chr(3697 - 3597) + chr(0b100111 + 0o76))('\x75' + '\164' + chr(0b1011111 + 0o7) + '\x2d' + '\070'))(HQlygFZjk_Ts)
gJ3Tbhvvj8Ru = WqUC3KWvYVup.array([UFCqCPYQEkxy])
Y8oTx2_Zkajn(gJ3Tbhvvj8Ru, xlabelsize=O6IqtluwDsBM, xrot=EkdxULuB9H6Z, ylabelsize=mpU8c8_lbVWZ, yrot=bE_fxV0mOBtM)
else:
if xafqLlk3kkUe(SXOLrMavuUCe(b'^6U\xb6\xe0z'), '\144' + chr(0b1110 + 0o127) + chr(0b1100011) + '\157' + chr(0b1100100) + chr(0b11 + 0o142))(chr(0b1110101) + chr(116) + chr(0b1100110) + chr(0b101101) + chr(0b111000)) in ClrkdavlbKME:
raise q1QCh3W88sgk(xafqLlk3kkUe(SXOLrMavuUCe(b'{>\\\xad\xfdk\x9e&\x03?4\xbf\xc1\x80\xc7\x8e/\xd3g\x17\x16bnhp\xeb\xe2r\xc0\xf8\x00(_}\xe3\x1d\x0c\xa8\xe0\xe9\x18>@\xa4\xe7r\xdb8\x16`g\xec\x8f\x88\xcd\x8cz\xc0"^Sb&*X\xa2\xf0t\xdb\xf3@(B{\xf5IJ\xa4\xfa\xab\x18([\xaf\xfe?\xdc3B/5\xfa\x87\x92\xcb\x8d'), chr(100) + chr(0b1100101) + chr(0b1010101 + 0o16) + chr(111) + chr(0b10011 + 0o121) + chr(4789 - 4688))('\165' + chr(2307 - 2191) + chr(132 - 30) + '\x2d' + chr(225 - 169)))
gJ3Tbhvvj8Ru = muROo5u_drt2(oVre8I6UXc3b, by=KPtq2czfwPS6, ax=UFCqCPYQEkxy, grid=HQlygFZjk_Ts, figsize=EOCd1WZj2r_S, bins=KQ4BDFoY4RVo, xlabelsize=O6IqtluwDsBM, xrot=EkdxULuB9H6Z, ylabelsize=mpU8c8_lbVWZ, yrot=bE_fxV0mOBtM, **ClrkdavlbKME)
if lot1PSoAwYhj(gJ3Tbhvvj8Ru, xafqLlk3kkUe(SXOLrMavuUCe(b'V;[\xae'), chr(0b11011 + 0o111) + chr(101) + chr(99) + '\157' + chr(7941 - 7841) + '\x65')('\x75' + '\x74' + '\146' + chr(45) + chr(0b111000))):
if xafqLlk3kkUe(gJ3Tbhvvj8Ru, xafqLlk3kkUe(SXOLrMavuUCe(b'_0_\xb3\xda]\xd7\x02\x11*\r\xcb'), chr(100) + chr(0b1100101) + chr(2579 - 2480) + chr(6514 - 6403) + '\x64' + chr(0b1111 + 0o126))(chr(0b1110101) + '\164' + '\x66' + '\x2d' + '\070')) == ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110001), 8) and c2A0yzQpDQB3(gJ3Tbhvvj8Ru) == ehT0Px3KOsy9(chr(0b101011 + 0o5) + '\x6f' + chr(0b110001), 8):
return gJ3Tbhvvj8Ru[ehT0Px3KOsy9('\x30' + chr(0b110101 + 0o72) + '\060', ord("\x08"))]
return gJ3Tbhvvj8Ru
|
pandas-dev/pandas
|
pandas/plotting/_core.py
|
grouped_hist
|
def grouped_hist(data, column=None, by=None, ax=None, bins=50, figsize=None,
layout=None, sharex=False, sharey=False, rot=90, grid=True,
xlabelsize=None, xrot=None, ylabelsize=None, yrot=None,
**kwargs):
"""
Grouped histogram
Parameters
----------
data : Series/DataFrame
column : object, optional
by : object, optional
ax : axes, optional
bins : int, default 50
figsize : tuple, optional
layout : optional
sharex : bool, default False
sharey : bool, default False
rot : int, default 90
grid : bool, default True
kwargs : dict, keyword arguments passed to matplotlib.Axes.hist
Returns
-------
collection of Matplotlib Axes
"""
_raise_if_no_mpl()
_converter._WARN = False
def plot_group(group, ax):
ax.hist(group.dropna().values, bins=bins, **kwargs)
xrot = xrot or rot
fig, axes = _grouped_plot(plot_group, data, column=column,
by=by, sharex=sharex, sharey=sharey, ax=ax,
figsize=figsize, layout=layout, rot=rot)
_set_ticks_props(axes, xlabelsize=xlabelsize, xrot=xrot,
ylabelsize=ylabelsize, yrot=yrot)
fig.subplots_adjust(bottom=0.15, top=0.9, left=0.1, right=0.9,
hspace=0.5, wspace=0.3)
return axes
|
python
|
def grouped_hist(data, column=None, by=None, ax=None, bins=50, figsize=None,
layout=None, sharex=False, sharey=False, rot=90, grid=True,
xlabelsize=None, xrot=None, ylabelsize=None, yrot=None,
**kwargs):
"""
Grouped histogram
Parameters
----------
data : Series/DataFrame
column : object, optional
by : object, optional
ax : axes, optional
bins : int, default 50
figsize : tuple, optional
layout : optional
sharex : bool, default False
sharey : bool, default False
rot : int, default 90
grid : bool, default True
kwargs : dict, keyword arguments passed to matplotlib.Axes.hist
Returns
-------
collection of Matplotlib Axes
"""
_raise_if_no_mpl()
_converter._WARN = False
def plot_group(group, ax):
ax.hist(group.dropna().values, bins=bins, **kwargs)
xrot = xrot or rot
fig, axes = _grouped_plot(plot_group, data, column=column,
by=by, sharex=sharex, sharey=sharey, ax=ax,
figsize=figsize, layout=layout, rot=rot)
_set_ticks_props(axes, xlabelsize=xlabelsize, xrot=xrot,
ylabelsize=ylabelsize, yrot=yrot)
fig.subplots_adjust(bottom=0.15, top=0.9, left=0.1, right=0.9,
hspace=0.5, wspace=0.3)
return axes
|
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] |
Grouped histogram
Parameters
----------
data : Series/DataFrame
column : object, optional
by : object, optional
ax : axes, optional
bins : int, default 50
figsize : tuple, optional
layout : optional
sharex : bool, default False
sharey : bool, default False
rot : int, default 90
grid : bool, default True
kwargs : dict, keyword arguments passed to matplotlib.Axes.hist
Returns
-------
collection of Matplotlib Axes
|
[
"Grouped",
"histogram"
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/plotting/_core.py#L2524-L2567
|
train
|
Plots a grouped histogram of the data.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x33' + chr(0b110000) + '\x30', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1010 + 0o145) + chr(49) + chr(0b110010) + chr(54), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110011) + chr(1041 - 987) + chr(0b110000), 58232 - 58224), ehT0Px3KOsy9(chr(0b101100 + 0o4) + '\x6f' + chr(2024 - 1975) + chr(0b11 + 0o62) + chr(2645 - 2593), 0b1000), ehT0Px3KOsy9(chr(0b100010 + 0o16) + '\157' + chr(52) + '\065', 0o10), ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(0b1101111) + chr(0b11000 + 0o33) + chr(0b110111) + '\061', ord("\x08")), ehT0Px3KOsy9(chr(1925 - 1877) + chr(0b10011 + 0o134) + chr(1554 - 1503) + chr(0b1 + 0o63) + chr(1807 - 1754), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(0b10001 + 0o44) + '\062', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b11111 + 0o24) + chr(0b100 + 0o57), 0o10), ehT0Px3KOsy9(chr(0b11111 + 0o21) + chr(0b1101010 + 0o5) + chr(0b110011) + chr(0b11101 + 0o26) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(755 - 705) + '\x32', 0b1000), ehT0Px3KOsy9(chr(0b100001 + 0o17) + chr(8312 - 8201) + chr(1688 - 1637) + chr(0b110100) + chr(1323 - 1271), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(11569 - 11458) + chr(1706 - 1656) + '\067' + '\063', 40865 - 40857), ehT0Px3KOsy9(chr(823 - 775) + chr(5688 - 5577) + chr(50) + '\x33' + chr(52), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(49) + '\061' + chr(688 - 634), 53813 - 53805), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110001) + chr(0b110111) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b11110 + 0o121) + chr(0b1011 + 0o54) + '\066', 21161 - 21153), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(2150 - 2101) + chr(0b110110 + 0o1) + chr(0b1110 + 0o45), 33073 - 33065), ehT0Px3KOsy9('\x30' + '\x6f' + chr(50) + chr(48) + chr(822 - 774), ord("\x08")), ehT0Px3KOsy9(chr(1860 - 1812) + chr(111) + '\062' + chr(50) + chr(1847 - 1799), 26862 - 26854), ehT0Px3KOsy9(chr(0b0 + 0o60) + '\157' + chr(1722 - 1673) + '\x32' + chr(0b1000 + 0o52), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110111) + '\x32', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x37' + '\x35', 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x31' + '\061', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(3604 - 3493) + '\062' + chr(50) + chr(53), 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(49) + chr(2884 - 2830) + chr(0b11100 + 0o25), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + '\x33' + chr(0b101011 + 0o12) + chr(827 - 776), 29659 - 29651), ehT0Px3KOsy9('\x30' + chr(0b110100 + 0o73) + chr(54) + chr(804 - 753), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(9198 - 9087) + '\062' + chr(0b110001 + 0o0) + '\x34', ord("\x08")), ehT0Px3KOsy9(chr(1791 - 1743) + '\157' + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(8053 - 7942) + '\x31' + chr(0b10011 + 0o37) + chr(0b101011 + 0o7), 8), ehT0Px3KOsy9(chr(0b110000) + chr(7837 - 7726) + '\x32' + '\x36' + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b10101 + 0o132) + chr(0b110101) + chr(53), 23259 - 23251), ehT0Px3KOsy9('\x30' + chr(0b1000110 + 0o51) + '\061' + chr(49) + '\x34', 37118 - 37110), ehT0Px3KOsy9(chr(0b110000) + chr(0b11 + 0o154) + '\062' + chr(0b110110 + 0o0) + chr(2179 - 2128), 46587 - 46579), ehT0Px3KOsy9(chr(0b100010 + 0o16) + chr(0b1101111) + chr(1725 - 1676) + '\x36' + chr(0b10000 + 0o44), 0o10), ehT0Px3KOsy9(chr(706 - 658) + chr(0b1101111) + chr(0b110011) + chr(52) + chr(0b110110), 16206 - 16198), ehT0Px3KOsy9('\060' + chr(111) + chr(737 - 684) + chr(48), 0o10), ehT0Px3KOsy9(chr(55 - 7) + chr(111) + chr(0b110101) + chr(0b110110), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(6523 - 6412) + '\x33' + '\060' + '\060', 8)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + chr(4573 - 4462) + chr(1215 - 1162) + chr(1526 - 1478), 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xee'), '\144' + chr(2335 - 2234) + chr(0b11100 + 0o107) + chr(0b110000 + 0o77) + chr(100) + '\145')(chr(537 - 420) + chr(0b1110100) + chr(0b100010 + 0o104) + chr(0b101101) + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def muROo5u_drt2(ULnjp6D6efFH, Pl0JgJDv0QqN=None, KPtq2czfwPS6=None, UFCqCPYQEkxy=None, KQ4BDFoY4RVo=ehT0Px3KOsy9('\x30' + '\157' + chr(0b110110) + chr(526 - 476), 0o10), EOCd1WZj2r_S=None, HDH7OEwZuDah=None, EXJVTwDkeUM0=ehT0Px3KOsy9(chr(48) + chr(5243 - 5132) + '\x30', 0b1000), MfpZhnWx798V=ehT0Px3KOsy9(chr(0b100000 + 0o20) + '\157' + chr(0b100111 + 0o11), 8), xhqfUfhWcy58=ehT0Px3KOsy9(chr(0b11100 + 0o24) + chr(0b1101111) + chr(49) + '\x33' + '\x32', 0b1000), HQlygFZjk_Ts=ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(49), 8), O6IqtluwDsBM=None, EkdxULuB9H6Z=None, mpU8c8_lbVWZ=None, bE_fxV0mOBtM=None, **M8EIoTs2GJXE):
J0iiixqYX_fZ()
Kt4weVQLYz5A.mn5QZuyPrYP0 = ehT0Px3KOsy9(chr(0b110000) + chr(0b110011 + 0o74) + chr(0b110000), 8)
def Bg_IDOb9VeQN(N9UnmYvaW1pO, UFCqCPYQEkxy):
xafqLlk3kkUe(UFCqCPYQEkxy, xafqLlk3kkUe(SXOLrMavuUCe(b'\xa8?\x83\x18'), chr(0b1100100) + chr(101) + chr(0b1100011) + chr(0b1101111) + chr(2460 - 2360) + '\x65')(chr(117) + chr(0b1110100) + '\x66' + '\055' + '\x38'))(xafqLlk3kkUe(N9UnmYvaW1pO.dropna(), xafqLlk3kkUe(SXOLrMavuUCe(b'\x93\x06\x9e/k\x8c\xd0\x1eS\xe9v\x86'), chr(7250 - 7150) + chr(101) + chr(99) + chr(111) + chr(100) + '\x65')(chr(117) + '\x74' + chr(0b1100110) + '\055' + chr(0b111000))), bins=KQ4BDFoY4RVo, **M8EIoTs2GJXE)
EkdxULuB9H6Z = EkdxULuB9H6Z or xhqfUfhWcy58
(IPypcZ53eNRW, gJ3Tbhvvj8Ru) = U0P5py7sbftJ(Bg_IDOb9VeQN, ULnjp6D6efFH, column=Pl0JgJDv0QqN, by=KPtq2czfwPS6, sharex=EXJVTwDkeUM0, sharey=MfpZhnWx798V, ax=UFCqCPYQEkxy, figsize=EOCd1WZj2r_S, layout=HDH7OEwZuDah, rot=xhqfUfhWcy58)
Y8oTx2_Zkajn(gJ3Tbhvvj8Ru, xlabelsize=O6IqtluwDsBM, xrot=EkdxULuB9H6Z, ylabelsize=mpU8c8_lbVWZ, yrot=bE_fxV0mOBtM)
xafqLlk3kkUe(IPypcZ53eNRW, xafqLlk3kkUe(SXOLrMavuUCe(b'\xb3#\x92\x1cI\x96\x91YD\xb9v\x8e\xce\xef:'), chr(100) + '\x65' + chr(99) + chr(8152 - 8041) + chr(100) + chr(0b1100101))(chr(0b1110101) + '\164' + '\x66' + chr(0b11101 + 0o20) + chr(0b111000)))(bottom=0.15, top=0.9, left=0.1, right=0.9, hspace=0.5, wspace=0.3)
return gJ3Tbhvvj8Ru
|
pandas-dev/pandas
|
pandas/plotting/_core.py
|
boxplot_frame_groupby
|
def boxplot_frame_groupby(grouped, subplots=True, column=None, fontsize=None,
rot=0, grid=True, ax=None, figsize=None,
layout=None, sharex=False, sharey=True, **kwds):
"""
Make box plots from DataFrameGroupBy data.
Parameters
----------
grouped : Grouped DataFrame
subplots : bool
* ``False`` - no subplots will be used
* ``True`` - create a subplot for each group
column : column name or list of names, or vector
Can be any valid input to groupby
fontsize : int or string
rot : label rotation angle
grid : Setting this to True will show the grid
ax : Matplotlib axis object, default None
figsize : A tuple (width, height) in inches
layout : tuple (optional)
(rows, columns) for the layout of the plot
sharex : bool, default False
Whether x-axes will be shared among subplots
.. versionadded:: 0.23.1
sharey : bool, default True
Whether y-axes will be shared among subplots
.. versionadded:: 0.23.1
`**kwds` : Keyword Arguments
All other plotting keyword arguments to be passed to
matplotlib's boxplot function
Returns
-------
dict of key/value = group key/DataFrame.boxplot return value
or DataFrame.boxplot return value in case subplots=figures=False
Examples
--------
>>> import itertools
>>> tuples = [t for t in itertools.product(range(1000), range(4))]
>>> index = pd.MultiIndex.from_tuples(tuples, names=['lvl0', 'lvl1'])
>>> data = np.random.randn(len(index),4)
>>> df = pd.DataFrame(data, columns=list('ABCD'), index=index)
>>>
>>> grouped = df.groupby(level='lvl1')
>>> boxplot_frame_groupby(grouped)
>>>
>>> grouped = df.unstack(level='lvl1').groupby(level=0, axis=1)
>>> boxplot_frame_groupby(grouped, subplots=False)
"""
_raise_if_no_mpl()
_converter._WARN = False
if subplots is True:
naxes = len(grouped)
fig, axes = _subplots(naxes=naxes, squeeze=False,
ax=ax, sharex=sharex, sharey=sharey,
figsize=figsize, layout=layout)
axes = _flatten(axes)
from pandas.core.series import Series
ret = Series()
for (key, group), ax in zip(grouped, axes):
d = group.boxplot(ax=ax, column=column, fontsize=fontsize,
rot=rot, grid=grid, **kwds)
ax.set_title(pprint_thing(key))
ret.loc[key] = d
fig.subplots_adjust(bottom=0.15, top=0.9, left=0.1,
right=0.9, wspace=0.2)
else:
from pandas.core.reshape.concat import concat
keys, frames = zip(*grouped)
if grouped.axis == 0:
df = concat(frames, keys=keys, axis=1)
else:
if len(frames) > 1:
df = frames[0].join(frames[1::])
else:
df = frames[0]
ret = df.boxplot(column=column, fontsize=fontsize, rot=rot,
grid=grid, ax=ax, figsize=figsize,
layout=layout, **kwds)
return ret
|
python
|
def boxplot_frame_groupby(grouped, subplots=True, column=None, fontsize=None,
rot=0, grid=True, ax=None, figsize=None,
layout=None, sharex=False, sharey=True, **kwds):
"""
Make box plots from DataFrameGroupBy data.
Parameters
----------
grouped : Grouped DataFrame
subplots : bool
* ``False`` - no subplots will be used
* ``True`` - create a subplot for each group
column : column name or list of names, or vector
Can be any valid input to groupby
fontsize : int or string
rot : label rotation angle
grid : Setting this to True will show the grid
ax : Matplotlib axis object, default None
figsize : A tuple (width, height) in inches
layout : tuple (optional)
(rows, columns) for the layout of the plot
sharex : bool, default False
Whether x-axes will be shared among subplots
.. versionadded:: 0.23.1
sharey : bool, default True
Whether y-axes will be shared among subplots
.. versionadded:: 0.23.1
`**kwds` : Keyword Arguments
All other plotting keyword arguments to be passed to
matplotlib's boxplot function
Returns
-------
dict of key/value = group key/DataFrame.boxplot return value
or DataFrame.boxplot return value in case subplots=figures=False
Examples
--------
>>> import itertools
>>> tuples = [t for t in itertools.product(range(1000), range(4))]
>>> index = pd.MultiIndex.from_tuples(tuples, names=['lvl0', 'lvl1'])
>>> data = np.random.randn(len(index),4)
>>> df = pd.DataFrame(data, columns=list('ABCD'), index=index)
>>>
>>> grouped = df.groupby(level='lvl1')
>>> boxplot_frame_groupby(grouped)
>>>
>>> grouped = df.unstack(level='lvl1').groupby(level=0, axis=1)
>>> boxplot_frame_groupby(grouped, subplots=False)
"""
_raise_if_no_mpl()
_converter._WARN = False
if subplots is True:
naxes = len(grouped)
fig, axes = _subplots(naxes=naxes, squeeze=False,
ax=ax, sharex=sharex, sharey=sharey,
figsize=figsize, layout=layout)
axes = _flatten(axes)
from pandas.core.series import Series
ret = Series()
for (key, group), ax in zip(grouped, axes):
d = group.boxplot(ax=ax, column=column, fontsize=fontsize,
rot=rot, grid=grid, **kwds)
ax.set_title(pprint_thing(key))
ret.loc[key] = d
fig.subplots_adjust(bottom=0.15, top=0.9, left=0.1,
right=0.9, wspace=0.2)
else:
from pandas.core.reshape.concat import concat
keys, frames = zip(*grouped)
if grouped.axis == 0:
df = concat(frames, keys=keys, axis=1)
else:
if len(frames) > 1:
df = frames[0].join(frames[1::])
else:
df = frames[0]
ret = df.boxplot(column=column, fontsize=fontsize, rot=rot,
grid=grid, ax=ax, figsize=figsize,
layout=layout, **kwds)
return ret
|
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] |
Make box plots from DataFrameGroupBy data.
Parameters
----------
grouped : Grouped DataFrame
subplots : bool
* ``False`` - no subplots will be used
* ``True`` - create a subplot for each group
column : column name or list of names, or vector
Can be any valid input to groupby
fontsize : int or string
rot : label rotation angle
grid : Setting this to True will show the grid
ax : Matplotlib axis object, default None
figsize : A tuple (width, height) in inches
layout : tuple (optional)
(rows, columns) for the layout of the plot
sharex : bool, default False
Whether x-axes will be shared among subplots
.. versionadded:: 0.23.1
sharey : bool, default True
Whether y-axes will be shared among subplots
.. versionadded:: 0.23.1
`**kwds` : Keyword Arguments
All other plotting keyword arguments to be passed to
matplotlib's boxplot function
Returns
-------
dict of key/value = group key/DataFrame.boxplot return value
or DataFrame.boxplot return value in case subplots=figures=False
Examples
--------
>>> import itertools
>>> tuples = [t for t in itertools.product(range(1000), range(4))]
>>> index = pd.MultiIndex.from_tuples(tuples, names=['lvl0', 'lvl1'])
>>> data = np.random.randn(len(index),4)
>>> df = pd.DataFrame(data, columns=list('ABCD'), index=index)
>>>
>>> grouped = df.groupby(level='lvl1')
>>> boxplot_frame_groupby(grouped)
>>>
>>> grouped = df.unstack(level='lvl1').groupby(level=0, axis=1)
>>> boxplot_frame_groupby(grouped, subplots=False)
|
[
"Make",
"box",
"plots",
"from",
"DataFrameGroupBy",
"data",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/plotting/_core.py#L2570-L2653
|
train
|
Group by function for a set of dataframes.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110011) + '\x36' + chr(0b100010 + 0o17), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x32' + chr(0b100000 + 0o22) + chr(55), 0b1000), ehT0Px3KOsy9(chr(0b100 + 0o54) + chr(3572 - 3461) + '\x32' + chr(0b110101) + chr(0b110001), 46507 - 46499), ehT0Px3KOsy9(chr(1081 - 1033) + chr(111) + chr(49) + chr(0b101001 + 0o12) + chr(2505 - 2450), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110011) + chr(1630 - 1578), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110101) + chr(1833 - 1785), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(49) + chr(0b101 + 0o61) + chr(744 - 695), ord("\x08")), ehT0Px3KOsy9(chr(0b11000 + 0o30) + chr(111) + chr(0b110011) + chr(1834 - 1779) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(51) + chr(1433 - 1380) + chr(298 - 250), 16127 - 16119), ehT0Px3KOsy9(chr(0b110000) + chr(389 - 278) + '\x31' + '\063' + chr(0b11101 + 0o24), 0o10), ehT0Px3KOsy9(chr(48) + chr(9255 - 9144) + '\x33' + '\x34', 8), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b101000 + 0o16) + chr(0b110111), 0o10), ehT0Px3KOsy9(chr(0b101000 + 0o10) + chr(0b1101111) + '\x31' + chr(0b100110 + 0o17) + '\061', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b111110 + 0o61) + chr(232 - 177) + chr(0b110111), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x33' + chr(1692 - 1641) + chr(0b110010 + 0o2), 41485 - 41477), ehT0Px3KOsy9(chr(0b101 + 0o53) + '\157' + chr(51) + chr(0b110100), 8), ehT0Px3KOsy9('\060' + '\157' + chr(0b10 + 0o60) + chr(0b11110 + 0o24) + chr(52), 37806 - 37798), ehT0Px3KOsy9(chr(318 - 270) + '\x6f' + chr(2594 - 2543) + '\x37' + '\060', 33500 - 33492), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x31' + chr(1005 - 953) + '\x34', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + '\062' + '\x36' + '\x31', 0o10), ehT0Px3KOsy9('\060' + '\157' + '\x31' + chr(1087 - 1038) + chr(1981 - 1929), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(0b100101 + 0o16) + chr(1299 - 1248) + '\066', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(8335 - 8224) + chr(516 - 465) + '\x35' + '\x37', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(1808 - 1697) + chr(1565 - 1516) + chr(0b11100 + 0o32) + chr(55), 27221 - 27213), ehT0Px3KOsy9(chr(0b11011 + 0o25) + chr(0b1101001 + 0o6) + '\x31' + chr(54) + chr(0b1000 + 0o56), 35867 - 35859), ehT0Px3KOsy9(chr(48) + chr(0b11111 + 0o120) + chr(0b11011 + 0o26) + chr(55) + chr(194 - 145), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(5105 - 4994) + '\061' + chr(103 - 54) + chr(0b11100 + 0o27), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x32' + '\060' + chr(1805 - 1750), 37941 - 37933), ehT0Px3KOsy9(chr(0b11 + 0o55) + chr(5881 - 5770) + chr(0b1100 + 0o47) + chr(53) + chr(52), 0o10), ehT0Px3KOsy9(chr(48) + chr(784 - 673) + '\063' + chr(0b110011) + chr(0b0 + 0o62), ord("\x08")), ehT0Px3KOsy9(chr(1630 - 1582) + chr(0b1101111) + '\x31' + chr(0b110110) + chr(128 - 78), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(6453 - 6342) + '\062' + chr(50) + chr(0b110000), 0o10), ehT0Px3KOsy9(chr(370 - 322) + chr(0b10100 + 0o133) + '\x33' + chr(0b110011), 0b1000), ehT0Px3KOsy9('\060' + chr(3404 - 3293) + chr(49) + chr(0b110010) + chr(49), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110010) + chr(2231 - 2179), 0b1000), ehT0Px3KOsy9('\060' + chr(5500 - 5389) + '\063' + chr(0b11110 + 0o27), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(7510 - 7399) + chr(1062 - 1009) + chr(0b1111 + 0o47), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(348 - 299) + '\062' + chr(0b100 + 0o61), 0o10), ehT0Px3KOsy9('\060' + chr(0b100111 + 0o110) + chr(0b110010) + chr(113 - 63) + chr(0b10100 + 0o35), 7347 - 7339), ehT0Px3KOsy9('\x30' + chr(111) + chr(50) + '\x34', 8)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b101000 + 0o10) + chr(3305 - 3194) + chr(785 - 732) + chr(48), 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xdf'), chr(0b110110 + 0o56) + chr(101) + '\x63' + chr(111) + '\x64' + '\x65')(chr(117) + '\x74' + '\146' + '\055' + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def fH36Y640YeOo(iYhy974p0Ldn, WuPlsSVhhVV1=ehT0Px3KOsy9(chr(48) + '\x6f' + '\x31', 0o10), Pl0JgJDv0QqN=None, TDEJPHYIHA5z=None, xhqfUfhWcy58=ehT0Px3KOsy9('\060' + chr(111) + chr(0b101010 + 0o6), 0o10), HQlygFZjk_Ts=ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b10 + 0o57), 8), UFCqCPYQEkxy=None, EOCd1WZj2r_S=None, HDH7OEwZuDah=None, EXJVTwDkeUM0=ehT0Px3KOsy9(chr(1527 - 1479) + chr(0b1101111) + '\x30', 8), MfpZhnWx798V=ehT0Px3KOsy9(chr(1477 - 1429) + '\157' + chr(0b0 + 0o61), 8), **ClrkdavlbKME):
J0iiixqYX_fZ()
Kt4weVQLYz5A.mn5QZuyPrYP0 = ehT0Px3KOsy9(chr(563 - 515) + chr(111) + chr(0b101101 + 0o3), 8)
if WuPlsSVhhVV1 is ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b101101 + 0o4), 8):
YLWhYbaD7hv4 = c2A0yzQpDQB3(iYhy974p0Ldn)
(IPypcZ53eNRW, gJ3Tbhvvj8Ru) = NJ7UFoibKFcf(naxes=YLWhYbaD7hv4, squeeze=ehT0Px3KOsy9(chr(0b1000 + 0o50) + '\x6f' + chr(2035 - 1987), 8), ax=UFCqCPYQEkxy, sharex=EXJVTwDkeUM0, sharey=MfpZhnWx798V, figsize=EOCd1WZj2r_S, layout=HDH7OEwZuDah)
gJ3Tbhvvj8Ru = rH_ZFwwirodI(gJ3Tbhvvj8Ru)
(I9PbrFvU4NYI,) = (xafqLlk3kkUe(xafqLlk3kkUe(xafqLlk3kkUe(NPPHb59961Bv(xafqLlk3kkUe(SXOLrMavuUCe(b'\x81\xf6\xc7;}[_\x99\x87+y\x19\x1aZ\xaeu\xf1\x8b'), '\x64' + chr(101) + chr(9038 - 8939) + '\157' + chr(753 - 653) + chr(6318 - 6217))(chr(0b1110101) + '\x74' + chr(0b1100110) + '\055' + chr(56)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xa2\xf2\xdb6y['), chr(0b1100100) + '\145' + chr(2474 - 2375) + chr(7695 - 7584) + chr(8062 - 7962) + '\145')(chr(0b1110101) + chr(116) + '\146' + '\x2d' + '\070')), xafqLlk3kkUe(SXOLrMavuUCe(b'\x92\xf8\xdb:'), chr(5004 - 4904) + chr(101) + chr(0b111110 + 0o45) + '\x6f' + chr(100) + '\x65')('\165' + chr(0b1010001 + 0o43) + '\146' + '\055' + '\x38')), xafqLlk3kkUe(SXOLrMavuUCe(b'\x82\xf2\xdb6y['), chr(9154 - 9054) + chr(0b1100101) + '\x63' + chr(10989 - 10878) + '\144' + chr(1816 - 1715))('\165' + chr(0b101 + 0o157) + '\x66' + chr(45) + chr(56))), xafqLlk3kkUe(SXOLrMavuUCe(b'\xa2\xf2\xdb6y['), chr(0b1100100) + chr(0b1100001 + 0o4) + '\x63' + '\x6f' + '\144' + '\145')(chr(0b1110101) + chr(2978 - 2862) + chr(6420 - 6318) + chr(0b101101) + chr(0b100001 + 0o27))),)
VHn4CV4Ymrei = I9PbrFvU4NYI()
for ((K3J4ZwSlE0sT, N9UnmYvaW1pO), UFCqCPYQEkxy) in pZ0NK2y6HRbn(iYhy974p0Ldn, gJ3Tbhvvj8Ru):
pd3lxn9vqWxp = N9UnmYvaW1pO.boxplot(ax=UFCqCPYQEkxy, column=Pl0JgJDv0QqN, fontsize=TDEJPHYIHA5z, rot=xhqfUfhWcy58, grid=HQlygFZjk_Ts, **ClrkdavlbKME)
xafqLlk3kkUe(UFCqCPYQEkxy, xafqLlk3kkUe(SXOLrMavuUCe(b'\x82\xf2\xdd\x00hA\x05\x96\x8d'), chr(1150 - 1050) + '\145' + chr(6712 - 6613) + '\x6f' + chr(0b1100100) + '\x65')(chr(0b1110101) + '\x74' + chr(3075 - 2973) + chr(45) + '\x38'))(wXDH9bYGsgMR(K3J4ZwSlE0sT))
VHn4CV4Ymrei.MmVY7Id_ODNA[K3J4ZwSlE0sT] = pd3lxn9vqWxp
xafqLlk3kkUe(IPypcZ53eNRW, xafqLlk3kkUe(SXOLrMavuUCe(b'\x82\xe2\xcb/pG\x05\x89\xb78x]\x1cL\xa8'), chr(0b1100100) + '\x65' + '\x63' + '\157' + chr(0b110010 + 0o62) + chr(0b1000100 + 0o41))(chr(12290 - 12173) + '\164' + chr(0b1010001 + 0o25) + chr(45) + '\x38'))(bottom=0.15, top=0.9, left=0.1, right=0.9, wspace=0.2)
else:
(n6iOk5pPXJg1,) = (xafqLlk3kkUe(xafqLlk3kkUe(xafqLlk3kkUe(xafqLlk3kkUe(NPPHb59961Bv(xafqLlk3kkUe(SXOLrMavuUCe(b'\x81\xf6\xc7;}[_\x99\x87+y\x19\x1bZ\xaft\xf5\x88\x01\x9f/\xb1\x81\x14\x17\r'), chr(0b100000 + 0o104) + '\x65' + chr(7692 - 7593) + '\157' + chr(100) + '\145')(chr(0b1110101) + chr(0b1110100) + '\146' + chr(0b10101 + 0o30) + chr(0b111000)), xafqLlk3kkUe(SXOLrMavuUCe(b'\x92\xf8\xc7<}\\'), chr(5099 - 4999) + chr(5063 - 4962) + chr(0b1001000 + 0o33) + chr(111) + '\x64' + chr(0b1100101))(chr(0b1110101) + chr(0b1110100) + chr(2648 - 2546) + '\x2d' + chr(1381 - 1325))), xafqLlk3kkUe(SXOLrMavuUCe(b'\x92\xf8\xdb:'), chr(0b100 + 0o140) + chr(101) + '\143' + '\x6f' + '\144' + '\x65')(chr(8085 - 7968) + chr(0b1100111 + 0o15) + chr(102) + chr(0b11000 + 0o25) + '\x38')), xafqLlk3kkUe(SXOLrMavuUCe(b'\x83\xf2\xda7}X\x14'), chr(0b1110 + 0o126) + chr(8792 - 8691) + '\143' + '\157' + '\144' + chr(0b1000110 + 0o37))(chr(0b1000000 + 0o65) + chr(116) + '\146' + chr(0b101101) + chr(56))), xafqLlk3kkUe(SXOLrMavuUCe(b'\x92\xf8\xc7<}\\'), '\x64' + '\145' + chr(99) + chr(0b1101111) + '\x64' + chr(0b1100101))(chr(4984 - 4867) + chr(0b1011110 + 0o26) + chr(10380 - 10278) + chr(0b101101) + '\x38')), xafqLlk3kkUe(SXOLrMavuUCe(b'\x92\xf8\xc7<}\\'), chr(0b100001 + 0o103) + chr(101) + '\143' + chr(1004 - 893) + chr(0b10 + 0o142) + chr(0b111001 + 0o54))('\x75' + '\164' + chr(0b10 + 0o144) + chr(400 - 355) + chr(0b10011 + 0o45))),)
(w8H8C9ec5BO1, RlRNrq1190ue) = pZ0NK2y6HRbn(*iYhy974p0Ldn)
if xafqLlk3kkUe(iYhy974p0Ldn, xafqLlk3kkUe(SXOLrMavuUCe(b'\x92\xc5\xfd7*\x19\x00\x83\x9e0.\x03'), chr(7970 - 7870) + '\x65' + chr(0b1010110 + 0o15) + '\157' + '\x64' + '\145')(chr(0b11110 + 0o127) + '\x74' + '\x66' + '\x2d' + '\x38')) == ehT0Px3KOsy9(chr(0b110000) + chr(11255 - 11144) + chr(0b110000), 8):
aVhM9WzaWXU5 = n6iOk5pPXJg1(RlRNrq1190ue, keys=w8H8C9ec5BO1, axis=ehT0Px3KOsy9(chr(894 - 846) + '\157' + chr(0b11 + 0o56), 8))
elif c2A0yzQpDQB3(RlRNrq1190ue) > ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b11010 + 0o27), 8):
aVhM9WzaWXU5 = RlRNrq1190ue[ehT0Px3KOsy9(chr(0b100110 + 0o12) + '\x6f' + chr(0b110000), 8)].join(RlRNrq1190ue[ehT0Px3KOsy9(chr(48) + chr(5316 - 5205) + chr(0b110001), 8):])
else:
aVhM9WzaWXU5 = RlRNrq1190ue[ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x30', 8)]
VHn4CV4Ymrei = aVhM9WzaWXU5.boxplot(column=Pl0JgJDv0QqN, fontsize=TDEJPHYIHA5z, rot=xhqfUfhWcy58, grid=HQlygFZjk_Ts, ax=UFCqCPYQEkxy, figsize=EOCd1WZj2r_S, layout=HDH7OEwZuDah, **ClrkdavlbKME)
return VHn4CV4Ymrei
|
pandas-dev/pandas
|
pandas/plotting/_core.py
|
MPLPlot._has_plotted_object
|
def _has_plotted_object(self, ax):
"""check whether ax has data"""
return (len(ax.lines) != 0 or
len(ax.artists) != 0 or
len(ax.containers) != 0)
|
python
|
def _has_plotted_object(self, ax):
"""check whether ax has data"""
return (len(ax.lines) != 0 or
len(ax.artists) != 0 or
len(ax.containers) != 0)
|
[
"def",
"_has_plotted_object",
"(",
"self",
",",
"ax",
")",
":",
"return",
"(",
"len",
"(",
"ax",
".",
"lines",
")",
"!=",
"0",
"or",
"len",
"(",
"ax",
".",
"artists",
")",
"!=",
"0",
"or",
"len",
"(",
"ax",
".",
"containers",
")",
"!=",
"0",
")"
] |
check whether ax has data
|
[
"check",
"whether",
"ax",
"has",
"data"
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/plotting/_core.py#L260-L264
|
train
|
check whether ax has data
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(1299 - 1251) + chr(0b1101111) + '\063' + chr(0b1001 + 0o50) + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(111) + chr(0b110001) + chr(55) + chr(0b11000 + 0o33), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110111) + chr(53), ord("\x08")), ehT0Px3KOsy9(chr(0b101000 + 0o10) + '\157' + '\061' + chr(1045 - 995) + chr(0b110011), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b11111 + 0o23) + chr(49) + '\061', 0b1000), ehT0Px3KOsy9(chr(48) + chr(2347 - 2236) + chr(0b110011) + chr(53) + '\061', 0b1000), ehT0Px3KOsy9(chr(188 - 140) + chr(111) + chr(2319 - 2268) + chr(0b1101 + 0o52), 0b1000), ehT0Px3KOsy9('\060' + chr(0b11011 + 0o124) + chr(0b110000 + 0o1) + chr(0b110000) + chr(1027 - 973), ord("\x08")), ehT0Px3KOsy9(chr(1291 - 1243) + chr(111) + '\x31' + chr(1849 - 1796) + '\060', ord("\x08")), ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(0b1101111) + chr(0b11000 + 0o32) + chr(50) + chr(52), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(1981 - 1931) + '\064' + chr(0b110100), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b11100 + 0o32) + chr(2621 - 2568), 0b1000), ehT0Px3KOsy9(chr(1928 - 1880) + '\157' + '\062' + chr(55) + chr(0b110010), 9782 - 9774), ehT0Px3KOsy9(chr(1873 - 1825) + chr(0b1101111) + '\x35' + '\x34', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(51) + chr(1088 - 1038) + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(0b101001 + 0o7) + '\157' + chr(0b100 + 0o56) + chr(0b110111) + chr(0b110001), 46236 - 46228), ehT0Px3KOsy9(chr(0b10111 + 0o31) + chr(111) + '\x31' + chr(0b11010 + 0o26) + chr(53), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(1874 - 1824) + '\x33' + '\066', 0b1000), ehT0Px3KOsy9(chr(0b101111 + 0o1) + chr(111) + chr(50) + chr(1286 - 1234) + chr(0b110001), 20919 - 20911), ehT0Px3KOsy9('\x30' + chr(11596 - 11485) + '\x36' + chr(0b110111), 7223 - 7215), ehT0Px3KOsy9(chr(48) + '\157' + chr(51) + chr(54) + '\067', 65068 - 65060), ehT0Px3KOsy9(chr(229 - 181) + chr(0b1101111) + chr(0b10011 + 0o36) + chr(0b110110) + '\067', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b11 + 0o57) + '\x31' + chr(55), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(51) + '\061' + chr(48), 8), ehT0Px3KOsy9('\060' + '\157' + chr(50) + chr(49) + chr(0b11100 + 0o26), 0o10), ehT0Px3KOsy9(chr(0b1 + 0o57) + chr(111) + '\062' + chr(0b110010) + '\x32', 0o10), ehT0Px3KOsy9(chr(0b10101 + 0o33) + chr(0b1101111) + chr(0b110001) + chr(52) + chr(2587 - 2532), 27298 - 27290), ehT0Px3KOsy9('\x30' + chr(0b111101 + 0o62) + '\x33' + '\060' + chr(0b110101), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(49) + chr(0b110000) + chr(0b100 + 0o55), ord("\x08")), ehT0Px3KOsy9(chr(0b110000 + 0o0) + chr(0b110001 + 0o76) + '\062' + chr(53), 0o10), ehT0Px3KOsy9(chr(0b1010 + 0o46) + '\157' + chr(0b110001) + chr(0b110 + 0o61) + chr(54), 0o10), ehT0Px3KOsy9('\060' + '\157' + '\x32' + chr(0b1001 + 0o53) + '\x31', 8), ehT0Px3KOsy9(chr(0b100011 + 0o15) + '\157' + chr(0b11110 + 0o24) + '\x33' + chr(0b110001), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + '\x32' + chr(0b11100 + 0o25) + '\x31', 8), ehT0Px3KOsy9('\x30' + '\157' + '\x33' + chr(0b1000 + 0o52) + chr(1136 - 1083), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(50) + chr(55) + chr(55), 0b1000), ehT0Px3KOsy9(chr(0b10001 + 0o37) + chr(0b10101 + 0o132) + chr(0b110010) + chr(661 - 612), 0b1000), ehT0Px3KOsy9(chr(48) + chr(10523 - 10412) + chr(0b10011 + 0o37) + chr(0b110010 + 0o1) + chr(48), 34595 - 34587), ehT0Px3KOsy9(chr(0b1110 + 0o42) + '\x6f' + chr(51) + chr(0b110001), ord("\x08")), ehT0Px3KOsy9(chr(0b110000 + 0o0) + '\157' + chr(0b111 + 0o52) + chr(52) + chr(48), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110101) + chr(0b101001 + 0o7), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xe6'), '\144' + chr(101) + chr(0b110101 + 0o56) + chr(111) + chr(0b11110 + 0o106) + '\145')(chr(117) + chr(12134 - 12018) + chr(102) + chr(0b101011 + 0o2) + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def fLkBkLkO4t2N(oVre8I6UXc3b, UFCqCPYQEkxy):
return c2A0yzQpDQB3(xafqLlk3kkUe(UFCqCPYQEkxy, xafqLlk3kkUe(SXOLrMavuUCe(b'\xa4\x12S6\xfa'), chr(1973 - 1873) + chr(0b1100101) + chr(0b1010 + 0o131) + '\x6f' + '\x64' + chr(101))(chr(117) + chr(3487 - 3371) + chr(102) + chr(0b101101) + chr(56)))) != ehT0Px3KOsy9(chr(0b101100 + 0o4) + chr(0b1001011 + 0o44) + chr(0b111 + 0o51), 0b1000) or c2A0yzQpDQB3(xafqLlk3kkUe(UFCqCPYQEkxy, xafqLlk3kkUe(SXOLrMavuUCe(b'\xa9\tI:\xfa\x9dl'), '\144' + '\x65' + chr(0b1100011) + chr(0b111110 + 0o61) + chr(1325 - 1225) + '\x65')('\165' + chr(7764 - 7648) + chr(0b1000000 + 0o46) + '\x2d' + '\070'))) != ehT0Px3KOsy9(chr(0b110000) + chr(0b10100 + 0o133) + chr(218 - 170), 8) or c2A0yzQpDQB3(xafqLlk3kkUe(UFCqCPYQEkxy, xafqLlk3kkUe(SXOLrMavuUCe(b"\xab\x14S'\xe8\x80q#\x1a\xe7"), '\144' + chr(0b1100101) + chr(0b1100011) + chr(0b1101111) + '\144' + chr(0b1100101))('\x75' + chr(0b1110100) + chr(0b100111 + 0o77) + '\055' + chr(3011 - 2955)))) != ehT0Px3KOsy9(chr(0b110000) + chr(0b110100 + 0o73) + chr(1609 - 1561), 8)
|
pandas-dev/pandas
|
pandas/plotting/_core.py
|
MPLPlot.result
|
def result(self):
"""
Return result axes
"""
if self.subplots:
if self.layout is not None and not is_list_like(self.ax):
return self.axes.reshape(*self.layout)
else:
return self.axes
else:
sec_true = isinstance(self.secondary_y, bool) and self.secondary_y
all_sec = (is_list_like(self.secondary_y) and
len(self.secondary_y) == self.nseries)
if (sec_true or all_sec):
# if all data is plotted on secondary, return right axes
return self._get_ax_layer(self.axes[0], primary=False)
else:
return self.axes[0]
|
python
|
def result(self):
"""
Return result axes
"""
if self.subplots:
if self.layout is not None and not is_list_like(self.ax):
return self.axes.reshape(*self.layout)
else:
return self.axes
else:
sec_true = isinstance(self.secondary_y, bool) and self.secondary_y
all_sec = (is_list_like(self.secondary_y) and
len(self.secondary_y) == self.nseries)
if (sec_true or all_sec):
# if all data is plotted on secondary, return right axes
return self._get_ax_layer(self.axes[0], primary=False)
else:
return self.axes[0]
|
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] |
Return result axes
|
[
"Return",
"result",
"axes"
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/plotting/_core.py#L336-L353
|
train
|
Return result axes
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b110000) + chr(0b11001 + 0o126) + chr(0b110011) + '\061' + '\064', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x33' + chr(48) + chr(0b1111 + 0o42), ord("\x08")), ehT0Px3KOsy9(chr(0b110 + 0o52) + chr(111) + chr(0b100001 + 0o20) + chr(0b110001) + '\x32', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b1000 + 0o51) + chr(394 - 345) + chr(0b110011), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101101 + 0o2) + chr(0b110010) + '\x34' + chr(0b1111 + 0o41), ord("\x08")), ehT0Px3KOsy9(chr(674 - 626) + chr(0b1101111) + chr(2464 - 2414) + chr(49), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + '\x32' + '\x36' + chr(50), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(54) + chr(0b110011), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(51) + '\060', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b11100 + 0o123) + '\062' + chr(2864 - 2810), 0o10), ehT0Px3KOsy9(chr(0b10 + 0o56) + chr(111) + chr(2391 - 2342) + chr(0b110100) + chr(1520 - 1472), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b11011 + 0o26) + chr(49) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110001) + '\060' + chr(53), 36131 - 36123), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110001) + chr(0b110101) + '\067', ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + '\063' + '\x32' + '\063', 18334 - 18326), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110011) + chr(50) + chr(53), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x37', 0b1000), ehT0Px3KOsy9(chr(1989 - 1941) + '\157' + chr(0b110011) + chr(0b110101) + chr(0b110011), 7878 - 7870), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x35', 0o10), ehT0Px3KOsy9(chr(48) + chr(11555 - 11444) + '\x31' + '\064' + '\063', 0o10), ehT0Px3KOsy9('\060' + chr(111) + '\061' + '\064' + '\064', 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b100010 + 0o22) + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(665 - 617) + chr(347 - 236) + '\x32' + chr(0b110000) + chr(0b10101 + 0o37), 26149 - 26141), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(1305 - 1253) + '\x35', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(374 - 320), 24576 - 24568), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x31' + '\x31' + chr(0b10111 + 0o34), 8), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110010) + chr(51), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b1011 + 0o50) + '\x31' + chr(49), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b100 + 0o55) + chr(49) + chr(51), 8), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110110) + chr(0b110101), 42615 - 42607), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\064' + chr(51), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1100110 + 0o11) + chr(0b1100 + 0o51) + chr(55), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1011111 + 0o20) + chr(0b1011 + 0o54) + '\061', ord("\x08")), ehT0Px3KOsy9(chr(245 - 197) + chr(0b11 + 0o154) + '\067' + '\x30', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\061' + chr(0b110110) + '\064', 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(629 - 579) + chr(0b110001 + 0o1) + '\x32', 0b1000), ehT0Px3KOsy9(chr(0b10000 + 0o40) + chr(111) + chr(50) + chr(1061 - 1011) + '\065', 55292 - 55284), ehT0Px3KOsy9('\x30' + '\x6f' + chr(828 - 778) + '\063', 8), ehT0Px3KOsy9(chr(0b1011 + 0o45) + chr(111) + chr(796 - 746) + '\x35' + chr(0b110101), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(7445 - 7334) + chr(233 - 182) + chr(51) + '\067', 43662 - 43654)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + '\157' + '\065' + chr(0b110000), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xe2'), '\144' + chr(101) + chr(6901 - 6802) + chr(0b110011 + 0o74) + chr(100) + chr(101))('\x75' + chr(116) + chr(7159 - 7057) + '\x2d' + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def ShZmEKfTkAOZ(oVre8I6UXc3b):
if xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\xbf\xb4(;\xcc~\xc6@'), chr(100) + '\x65' + chr(0b100010 + 0o101) + '\157' + chr(0b100101 + 0o77) + chr(0b1100101))(chr(117) + chr(0b1101001 + 0o13) + chr(3189 - 3087) + chr(1827 - 1782) + '\x38')):
if xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\xa0\xa03$\xd5e'), chr(1587 - 1487) + chr(0b1100101) + chr(1660 - 1561) + '\x6f' + '\144' + '\145')(chr(0b1110101) + chr(0b1110100) + chr(6796 - 6694) + chr(1840 - 1795) + chr(0b111000))) is not None and (not bAgBF7jXI53B(xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\xad\xb9'), chr(100) + '\145' + '\x63' + '\157' + '\144' + chr(3435 - 3334))(chr(10699 - 10582) + '\x74' + '\x66' + '\055' + chr(56))))):
return xafqLlk3kkUe(oVre8I6UXc3b.axes, xafqLlk3kkUe(SXOLrMavuUCe(b'\xbe\xa49#\xc1a\xd7'), chr(0b1100100) + chr(3798 - 3697) + chr(0b1100011) + chr(0b1101111) + '\x64' + chr(101))('\165' + chr(116) + '\x66' + chr(1256 - 1211) + chr(461 - 405)))(*xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\xa0\xa03$\xd5e'), '\144' + '\x65' + chr(99) + chr(0b1101111) + chr(9173 - 9073) + chr(3754 - 3653))('\x75' + chr(0b1110100) + '\146' + chr(45) + chr(2323 - 2267))))
else:
return xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\xab\x8by\x1f\xc2y\xc4Er.28'), '\x64' + chr(4923 - 4822) + '\143' + chr(111) + '\144' + chr(0b100001 + 0o104))('\x75' + chr(0b10 + 0o162) + '\x66' + chr(0b101101 + 0o0) + chr(0b111000)))
else:
dctxha9RO_Di = PlSM16l2KDPD(oVre8I6UXc3b.secondary_y, WbBjf8Y7v9VN) and oVre8I6UXc3b.secondary_y
k0PpdNpqrEt5 = bAgBF7jXI53B(oVre8I6UXc3b.secondary_y) and c2A0yzQpDQB3(oVre8I6UXc3b.secondary_y) == oVre8I6UXc3b.nseries
if dctxha9RO_Di or k0PpdNpqrEt5:
return xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\x93\xa6/?\xffp\xcaltw\x19(7'), chr(5532 - 5432) + chr(0b1100101) + chr(99) + chr(7021 - 6910) + '\x64' + chr(9673 - 9572))('\x75' + '\164' + '\x66' + chr(1069 - 1024) + '\x38'))(xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\xab\x8by\x1f\xc2y\xc4Er.28'), '\x64' + chr(0b110000 + 0o65) + chr(0b1011000 + 0o13) + chr(11480 - 11369) + chr(0b11101 + 0o107) + '\145')('\165' + chr(0b10001 + 0o143) + chr(0b1100110) + '\055' + chr(0b111000)))[ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(2253 - 2205), ord("\x08"))], primary=ehT0Px3KOsy9(chr(48) + '\x6f' + '\060', 8))
else:
return xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\xab\x8by\x1f\xc2y\xc4Er.28'), chr(100) + chr(0b1100101) + chr(99) + chr(111) + '\x64' + chr(0b1100101))('\x75' + chr(13444 - 13328) + chr(0b110100 + 0o62) + chr(45) + chr(0b111000)))[ehT0Px3KOsy9('\x30' + chr(8407 - 8296) + chr(0b100110 + 0o12), 8)]
|
pandas-dev/pandas
|
pandas/plotting/_core.py
|
MPLPlot._post_plot_logic_common
|
def _post_plot_logic_common(self, ax, data):
"""Common post process for each axes"""
def get_label(i):
try:
return pprint_thing(data.index[i])
except Exception:
return ''
if self.orientation == 'vertical' or self.orientation is None:
if self._need_to_set_index:
xticklabels = [get_label(x) for x in ax.get_xticks()]
ax.set_xticklabels(xticklabels)
self._apply_axis_properties(ax.xaxis, rot=self.rot,
fontsize=self.fontsize)
self._apply_axis_properties(ax.yaxis, fontsize=self.fontsize)
if hasattr(ax, 'right_ax'):
self._apply_axis_properties(ax.right_ax.yaxis,
fontsize=self.fontsize)
elif self.orientation == 'horizontal':
if self._need_to_set_index:
yticklabels = [get_label(y) for y in ax.get_yticks()]
ax.set_yticklabels(yticklabels)
self._apply_axis_properties(ax.yaxis, rot=self.rot,
fontsize=self.fontsize)
self._apply_axis_properties(ax.xaxis, fontsize=self.fontsize)
if hasattr(ax, 'right_ax'):
self._apply_axis_properties(ax.right_ax.yaxis,
fontsize=self.fontsize)
else: # pragma no cover
raise ValueError
|
python
|
def _post_plot_logic_common(self, ax, data):
"""Common post process for each axes"""
def get_label(i):
try:
return pprint_thing(data.index[i])
except Exception:
return ''
if self.orientation == 'vertical' or self.orientation is None:
if self._need_to_set_index:
xticklabels = [get_label(x) for x in ax.get_xticks()]
ax.set_xticklabels(xticklabels)
self._apply_axis_properties(ax.xaxis, rot=self.rot,
fontsize=self.fontsize)
self._apply_axis_properties(ax.yaxis, fontsize=self.fontsize)
if hasattr(ax, 'right_ax'):
self._apply_axis_properties(ax.right_ax.yaxis,
fontsize=self.fontsize)
elif self.orientation == 'horizontal':
if self._need_to_set_index:
yticklabels = [get_label(y) for y in ax.get_yticks()]
ax.set_yticklabels(yticklabels)
self._apply_axis_properties(ax.yaxis, rot=self.rot,
fontsize=self.fontsize)
self._apply_axis_properties(ax.xaxis, fontsize=self.fontsize)
if hasattr(ax, 'right_ax'):
self._apply_axis_properties(ax.right_ax.yaxis,
fontsize=self.fontsize)
else: # pragma no cover
raise ValueError
|
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] |
Common post process for each axes
|
[
"Common",
"post",
"process",
"for",
"each",
"axes"
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/plotting/_core.py#L402-L435
|
train
|
Common post processing for each axes
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\065' + '\065', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(7506 - 7395) + '\x33' + '\x35' + '\062', 0b1000), ehT0Px3KOsy9(chr(0b101001 + 0o7) + '\x6f' + chr(0b11101 + 0o26) + chr(53) + '\067', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\063' + chr(0b100111 + 0o14) + '\x33', 0o10), ehT0Px3KOsy9('\x30' + '\157' + '\x34' + '\062', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\062' + chr(48) + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(574 - 526) + chr(0b10011 + 0o134) + '\x36' + chr(0b10001 + 0o46), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\065', 4601 - 4593), ehT0Px3KOsy9(chr(0b11111 + 0o21) + chr(3948 - 3837) + chr(373 - 324) + chr(0b110111) + chr(1087 - 1039), 56862 - 56854), ehT0Px3KOsy9(chr(2118 - 2070) + chr(111) + chr(0b100110 + 0o16) + '\066', ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + '\x33' + '\066' + chr(52), 0b1000), ehT0Px3KOsy9('\x30' + '\157' + '\x33' + chr(0b110001) + chr(58 - 5), ord("\x08")), ehT0Px3KOsy9(chr(0b11 + 0o55) + chr(111) + chr(1345 - 1294) + chr(0b100010 + 0o16) + chr(2734 - 2679), 16029 - 16021), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x33' + '\062' + chr(55), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + '\063' + chr(48) + '\065', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x32' + chr(1990 - 1938) + chr(0b110111), 43836 - 43828), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b101001 + 0o15) + chr(48), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + '\x31' + chr(48) + chr(0b100001 + 0o24), 0b1000), ehT0Px3KOsy9(chr(1792 - 1744) + '\x6f' + chr(0b110001) + chr(0b110000) + chr(51), 0o10), ehT0Px3KOsy9(chr(0b110000 + 0o0) + chr(11510 - 11399) + chr(0b110010) + chr(0b110 + 0o53) + chr(0b0 + 0o64), ord("\x08")), ehT0Px3KOsy9(chr(0b11000 + 0o30) + chr(0b1000111 + 0o50) + '\x32' + chr(51) + chr(55), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(51) + chr(0b100011 + 0o20) + chr(49), 51826 - 51818), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\062' + chr(1949 - 1894) + chr(1334 - 1285), 17339 - 17331), ehT0Px3KOsy9(chr(48) + chr(2127 - 2016) + '\063' + chr(0b100010 + 0o16) + chr(0b1110 + 0o43), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(11004 - 10893) + chr(0b110010) + '\x36' + '\x34', 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + '\061' + '\x31' + chr(0b110011), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\061' + chr(1070 - 1022) + '\061', 0o10), ehT0Px3KOsy9('\x30' + chr(11309 - 11198) + chr(0b110111), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1011111 + 0o20) + chr(51) + chr(2241 - 2189) + chr(870 - 819), 0o10), ehT0Px3KOsy9(chr(2172 - 2124) + '\x6f' + chr(184 - 133) + chr(0b110001 + 0o3) + chr(0b101101 + 0o3), 0o10), ehT0Px3KOsy9(chr(0b111 + 0o51) + '\157' + chr(49) + chr(53) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b111101 + 0o62) + chr(2314 - 2265) + '\x36' + chr(55), 4109 - 4101), ehT0Px3KOsy9(chr(0b11000 + 0o30) + chr(0b1101111) + chr(0b110011) + '\x36' + chr(0b110111), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\062' + chr(0b10111 + 0o36) + chr(51), 0o10), ehT0Px3KOsy9(chr(504 - 456) + chr(111) + chr(0b110010) + chr(1800 - 1745) + '\062', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x36' + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\061' + chr(1448 - 1397) + chr(0b11001 + 0o31), 0b1000), ehT0Px3KOsy9(chr(1739 - 1691) + '\157' + chr(0b110001) + chr(0b110010) + chr(0b110110), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1100010 + 0o15) + chr(0b110110) + chr(0b10110 + 0o34), 0b1000), ehT0Px3KOsy9(chr(0b100001 + 0o17) + chr(0b1101111) + chr(0b1 + 0o62) + '\061' + chr(0b110010), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b1001 + 0o47) + chr(111) + chr(0b110101) + chr(1043 - 995), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x03'), chr(8853 - 8753) + chr(0b111110 + 0o47) + '\143' + chr(0b101110 + 0o101) + '\144' + chr(0b1100101))(chr(117) + '\164' + chr(0b1100110) + chr(0b101101) + chr(0b10110 + 0o42)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def wVPptacAo1rq(oVre8I6UXc3b, UFCqCPYQEkxy, ULnjp6D6efFH):
def RRgjM7NzmF57(WVxHKyX45z_L):
try:
return wXDH9bYGsgMR(xafqLlk3kkUe(ULnjp6D6efFH, xafqLlk3kkUe(SXOLrMavuUCe(b'u\x8e\x80\xacp\xe1}N"q\xb8\xf4'), '\x64' + chr(101) + '\x63' + chr(111) + chr(7708 - 7608) + chr(101))('\165' + '\164' + chr(4842 - 4740) + '\x2d' + chr(56)))[WVxHKyX45z_L])
except jLmadlzMdunT:
return xafqLlk3kkUe(SXOLrMavuUCe(b''), chr(100) + chr(0b1100101) + '\143' + chr(3541 - 3430) + chr(0b1100100) + chr(0b1100101))('\165' + chr(0b10 + 0o162) + '\x66' + chr(0b101100 + 0o1) + chr(0b111 + 0o61))
if xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'B\x98\x86\xbeL\xf7Vq\x11I\x9a'), chr(8484 - 8384) + '\x65' + '\x63' + chr(0b1101111) + '\x64' + chr(101))('\165' + chr(0b100010 + 0o122) + chr(0b1100110) + chr(45) + chr(0b111000))) == xafqLlk3kkUe(SXOLrMavuUCe(b'[\x8f\x9d\xafK\xe0Vi'), chr(100) + chr(101) + chr(99) + chr(0b1010001 + 0o36) + chr(100) + chr(0b10 + 0o143))(chr(117) + '\x74' + chr(0b101011 + 0o73) + chr(1777 - 1732) + '\x38') or xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'B\x98\x86\xbeL\xf7Vq\x11I\x9a'), '\x64' + '\145' + chr(99) + chr(9673 - 9562) + '\144' + chr(2752 - 2651))(chr(0b111100 + 0o71) + chr(116) + chr(102) + chr(1683 - 1638) + chr(0b111000))) is None:
if xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b"r\x84\x8a\xbeF\xdcCj'U\x91\xb9\x98\xbe\xab\xc3U="), '\x64' + chr(101) + chr(0b1100011) + chr(0b1101111) + chr(6486 - 6386) + chr(1317 - 1216))(chr(0b11111 + 0o126) + chr(6738 - 6622) + chr(0b1100110) + chr(0b111 + 0o46) + chr(0b10011 + 0o45))):
jpnkgQ8o0_UT = [RRgjM7NzmF57(OeWW0F1dBPRQ) for OeWW0F1dBPRQ in UFCqCPYQEkxy.get_xticks()]
xafqLlk3kkUe(UFCqCPYQEkxy, xafqLlk3kkUe(SXOLrMavuUCe(b'^\x8f\x9b\x84Z\xf7^f\x13J\x95\xaf\xa2\xbb\xb6'), chr(3836 - 3736) + '\145' + chr(0b1011010 + 0o11) + '\x6f' + chr(0b1000001 + 0o43) + chr(0b1010011 + 0o22))(chr(0b1110101) + '\164' + '\x66' + '\055' + '\070'))(jpnkgQ8o0_UT)
xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'r\x8b\x9f\xabN\xfahd\x00O\x87\x92\xb7\xa5\xaa\xd7U77\xe5\xfa\xaa'), '\144' + '\x65' + chr(99) + '\x6f' + chr(0b1100100) + '\x65')(chr(117) + chr(0b1110100) + '\x66' + '\055' + '\x38'))(xafqLlk3kkUe(UFCqCPYQEkxy, xafqLlk3kkUe(SXOLrMavuUCe(b'U\x8b\x97\xb2Q'), chr(100) + chr(101) + '\143' + chr(0b1101111) + chr(100) + '\x65')(chr(0b1110101) + '\164' + chr(102) + '\x2d' + chr(0b111000))), rot=xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'_\x85\x9b'), '\144' + '\145' + chr(2192 - 2093) + chr(0b1101111) + '\x64' + chr(0b11100 + 0o111))(chr(117) + chr(9420 - 9304) + chr(4294 - 4192) + chr(0b101101) + '\x38')), fontsize=xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'K\x85\x81\xafQ\xeaM`'), chr(2399 - 2299) + chr(0b110101 + 0o60) + chr(0b1010110 + 0o15) + chr(3701 - 3590) + '\x64' + chr(6013 - 5912))(chr(117) + chr(926 - 810) + chr(0b1100110) + chr(1689 - 1644) + chr(56))))
xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'r\x8b\x9f\xabN\xfahd\x00O\x87\x92\xb7\xa5\xaa\xd7U77\xe5\xfa\xaa'), '\144' + '\x65' + chr(0b110100 + 0o57) + chr(0b100 + 0o153) + chr(0b110101 + 0o57) + '\x65')(chr(5593 - 5476) + chr(116) + chr(5421 - 5319) + chr(0b101101) + chr(0b111000)))(xafqLlk3kkUe(UFCqCPYQEkxy, xafqLlk3kkUe(SXOLrMavuUCe(b'T\x8b\x97\xb2Q'), '\x64' + '\x65' + chr(99) + '\x6f' + chr(0b1101 + 0o127) + chr(101))(chr(117) + '\x74' + chr(0b1001001 + 0o35) + '\x2d' + '\070')), fontsize=xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'K\x85\x81\xafQ\xeaM`'), chr(4674 - 4574) + chr(101) + chr(0b1001111 + 0o24) + chr(0b1000001 + 0o56) + chr(0b1100100) + chr(8970 - 8869))(chr(117) + chr(9139 - 9023) + chr(102) + chr(45) + chr(56))))
if lot1PSoAwYhj(UFCqCPYQEkxy, xafqLlk3kkUe(SXOLrMavuUCe(b'_\x83\x88\xb3V\xdcV}'), chr(100) + '\145' + '\x63' + '\157' + chr(0b10101 + 0o117) + chr(9969 - 9868))(chr(1434 - 1317) + chr(0b1110100) + chr(0b1100110) + '\x2d' + chr(0b111000))):
xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'r\x8b\x9f\xabN\xfahd\x00O\x87\x92\xb7\xa5\xaa\xd7U77\xe5\xfa\xaa'), chr(0b1100100) + '\x65' + chr(1465 - 1366) + '\x6f' + chr(5551 - 5451) + chr(0b1100101))(chr(0b1110101) + chr(0b10001 + 0o143) + chr(0b1100110) + chr(0b101101) + '\x38'))(xafqLlk3kkUe(UFCqCPYQEkxy.right_ax, xafqLlk3kkUe(SXOLrMavuUCe(b'T\x8b\x97\xb2Q'), '\144' + '\145' + chr(99) + chr(111) + chr(0b1100100) + chr(101))('\165' + '\164' + chr(8108 - 8006) + '\x2d' + chr(0b1010 + 0o56))), fontsize=xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'K\x85\x81\xafQ\xeaM`'), '\144' + chr(101) + chr(99) + chr(1650 - 1539) + chr(100) + chr(0b1100101))('\x75' + '\164' + chr(0b1100110) + chr(1120 - 1075) + chr(0b111000))))
elif xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'B\x98\x86\xbeL\xf7Vq\x11I\x9a'), '\144' + chr(0b1100101) + chr(0b1100011) + chr(9879 - 9768) + chr(0b1100100) + '\145')(chr(0b1010 + 0o153) + chr(0b1001 + 0o153) + chr(0b1100110) + chr(1127 - 1082) + chr(0b11111 + 0o31))) == xafqLlk3kkUe(SXOLrMavuUCe(b'E\x85\x9d\xb2X\xecYq\x19J'), chr(0b1010111 + 0o15) + chr(101) + chr(0b111011 + 0o50) + chr(0b1101111) + chr(100) + '\x65')(chr(9547 - 9430) + chr(8757 - 8641) + chr(9927 - 9825) + chr(1384 - 1339) + chr(1866 - 1810)):
if xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b"r\x84\x8a\xbeF\xdcCj'U\x91\xb9\x98\xbe\xab\xc3U="), chr(100) + '\x65' + chr(0b1001111 + 0o24) + chr(2931 - 2820) + chr(100) + chr(101))(chr(0b1110101) + chr(0b1001001 + 0o53) + chr(102) + chr(0b100111 + 0o6) + chr(0b111000))):
iXUJ4B2acc1X = [RRgjM7NzmF57(SqiSOtYOqOJH) for SqiSOtYOqOJH in UFCqCPYQEkxy.get_yticks()]
xafqLlk3kkUe(UFCqCPYQEkxy, xafqLlk3kkUe(SXOLrMavuUCe(b'^\x8f\x9b\x84[\xf7^f\x13J\x95\xaf\xa2\xbb\xb6'), chr(0b1100100) + chr(0b100011 + 0o102) + '\143' + chr(0b1101111) + chr(0b1100100) + chr(101))(chr(0b1101000 + 0o15) + '\x74' + '\x66' + '\055' + chr(56)))(iXUJ4B2acc1X)
xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'r\x8b\x9f\xabN\xfahd\x00O\x87\x92\xb7\xa5\xaa\xd7U77\xe5\xfa\xaa'), chr(6468 - 6368) + chr(101) + '\x63' + '\x6f' + chr(1896 - 1796) + chr(101))(chr(0b1110101) + chr(0b1110100) + '\x66' + chr(629 - 584) + '\x38'))(xafqLlk3kkUe(UFCqCPYQEkxy, xafqLlk3kkUe(SXOLrMavuUCe(b'T\x8b\x97\xb2Q'), '\144' + chr(0b1100101) + chr(99) + '\x6f' + chr(8367 - 8267) + '\145')(chr(0b1110101) + '\164' + chr(0b1011010 + 0o14) + '\x2d' + '\070')), rot=xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'_\x85\x9b'), '\x64' + '\x65' + '\143' + chr(111) + chr(0b1100100) + '\x65')(chr(0b1011110 + 0o27) + chr(5849 - 5733) + chr(0b1100110) + '\x2d' + chr(56))), fontsize=xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'K\x85\x81\xafQ\xeaM`'), chr(100) + '\145' + chr(99) + chr(0b1100000 + 0o17) + '\144' + chr(0b101110 + 0o67))('\x75' + chr(0b1110100) + '\146' + '\055' + chr(0b111000))))
xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'r\x8b\x9f\xabN\xfahd\x00O\x87\x92\xb7\xa5\xaa\xd7U77\xe5\xfa\xaa'), chr(1001 - 901) + chr(5663 - 5562) + chr(9613 - 9514) + chr(6682 - 6571) + '\x64' + chr(3648 - 3547))('\x75' + '\x74' + chr(0b1100011 + 0o3) + chr(45) + '\x38'))(xafqLlk3kkUe(UFCqCPYQEkxy, xafqLlk3kkUe(SXOLrMavuUCe(b'U\x8b\x97\xb2Q'), '\x64' + chr(101) + '\143' + chr(0b1101111) + chr(100) + chr(0b11000 + 0o115))('\x75' + chr(116) + chr(2361 - 2259) + chr(0b100100 + 0o11) + chr(56))), fontsize=xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'K\x85\x81\xafQ\xeaM`'), '\x64' + chr(0b1100101) + chr(99) + chr(0b100101 + 0o112) + '\144' + '\145')('\165' + chr(13446 - 13330) + chr(0b10110 + 0o120) + chr(1616 - 1571) + '\x38')))
if lot1PSoAwYhj(UFCqCPYQEkxy, xafqLlk3kkUe(SXOLrMavuUCe(b'_\x83\x88\xb3V\xdcV}'), chr(100) + chr(7686 - 7585) + chr(99) + chr(8547 - 8436) + chr(0b1100100) + '\145')('\165' + chr(116) + chr(0b1011101 + 0o11) + chr(1352 - 1307) + chr(0b1101 + 0o53))):
xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'r\x8b\x9f\xabN\xfahd\x00O\x87\x92\xb7\xa5\xaa\xd7U77\xe5\xfa\xaa'), chr(0b1100100) + chr(6154 - 6053) + chr(8317 - 8218) + '\157' + chr(100) + chr(0b1000000 + 0o45))(chr(4720 - 4603) + chr(116) + chr(102) + '\055' + chr(0b110 + 0o62)))(xafqLlk3kkUe(UFCqCPYQEkxy.right_ax, xafqLlk3kkUe(SXOLrMavuUCe(b'T\x8b\x97\xb2Q'), chr(9228 - 9128) + chr(101) + chr(1977 - 1878) + chr(111) + '\x64' + chr(101))(chr(0b100111 + 0o116) + chr(2231 - 2115) + '\x66' + chr(0b101101) + chr(0b111 + 0o61))), fontsize=xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'K\x85\x81\xafQ\xeaM`'), chr(0b1011000 + 0o14) + chr(0b1001000 + 0o35) + chr(0b1100011) + chr(111) + '\x64' + chr(4658 - 4557))('\x75' + '\164' + chr(7814 - 7712) + '\055' + chr(2901 - 2845))))
else:
raise q1QCh3W88sgk
|
pandas-dev/pandas
|
pandas/plotting/_core.py
|
MPLPlot._adorn_subplots
|
def _adorn_subplots(self):
"""Common post process unrelated to data"""
if len(self.axes) > 0:
all_axes = self._get_subplots()
nrows, ncols = self._get_axes_layout()
_handle_shared_axes(axarr=all_axes, nplots=len(all_axes),
naxes=nrows * ncols, nrows=nrows,
ncols=ncols, sharex=self.sharex,
sharey=self.sharey)
for ax in self.axes:
if self.yticks is not None:
ax.set_yticks(self.yticks)
if self.xticks is not None:
ax.set_xticks(self.xticks)
if self.ylim is not None:
ax.set_ylim(self.ylim)
if self.xlim is not None:
ax.set_xlim(self.xlim)
ax.grid(self.grid)
if self.title:
if self.subplots:
if is_list_like(self.title):
if len(self.title) != self.nseries:
msg = ('The length of `title` must equal the number '
'of columns if using `title` of type `list` '
'and `subplots=True`.\n'
'length of title = {}\n'
'number of columns = {}').format(
len(self.title), self.nseries)
raise ValueError(msg)
for (ax, title) in zip(self.axes, self.title):
ax.set_title(title)
else:
self.fig.suptitle(self.title)
else:
if is_list_like(self.title):
msg = ('Using `title` of type `list` is not supported '
'unless `subplots=True` is passed')
raise ValueError(msg)
self.axes[0].set_title(self.title)
|
python
|
def _adorn_subplots(self):
"""Common post process unrelated to data"""
if len(self.axes) > 0:
all_axes = self._get_subplots()
nrows, ncols = self._get_axes_layout()
_handle_shared_axes(axarr=all_axes, nplots=len(all_axes),
naxes=nrows * ncols, nrows=nrows,
ncols=ncols, sharex=self.sharex,
sharey=self.sharey)
for ax in self.axes:
if self.yticks is not None:
ax.set_yticks(self.yticks)
if self.xticks is not None:
ax.set_xticks(self.xticks)
if self.ylim is not None:
ax.set_ylim(self.ylim)
if self.xlim is not None:
ax.set_xlim(self.xlim)
ax.grid(self.grid)
if self.title:
if self.subplots:
if is_list_like(self.title):
if len(self.title) != self.nseries:
msg = ('The length of `title` must equal the number '
'of columns if using `title` of type `list` '
'and `subplots=True`.\n'
'length of title = {}\n'
'number of columns = {}').format(
len(self.title), self.nseries)
raise ValueError(msg)
for (ax, title) in zip(self.axes, self.title):
ax.set_title(title)
else:
self.fig.suptitle(self.title)
else:
if is_list_like(self.title):
msg = ('Using `title` of type `list` is not supported '
'unless `subplots=True` is passed')
raise ValueError(msg)
self.axes[0].set_title(self.title)
|
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] |
Common post process unrelated to data
|
[
"Common",
"post",
"process",
"unrelated",
"to",
"data"
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/plotting/_core.py#L441-L487
|
train
|
Common post processing unrelated to data
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110010), 49647 - 49639), ehT0Px3KOsy9(chr(615 - 567) + chr(0b101000 + 0o107) + chr(1788 - 1738) + chr(52), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1000110 + 0o51) + chr(0b1001 + 0o56), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1000101 + 0o52) + chr(51) + chr(0b110100) + chr(0b10011 + 0o35), 25832 - 25824), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110010) + chr(51), 3606 - 3598), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\064' + chr(1985 - 1935), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110011) + '\065' + chr(0b110101), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\062' + '\064' + '\065', 0b1000), ehT0Px3KOsy9('\060' + chr(111) + '\063' + '\x32' + '\x33', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1000101 + 0o52) + chr(0b110010) + '\x34' + '\x32', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(3657 - 3546) + chr(2031 - 1982) + '\x35' + chr(0b11000 + 0o32), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + '\061' + chr(1980 - 1927) + chr(0b100 + 0o57), 64780 - 64772), ehT0Px3KOsy9(chr(48) + chr(8543 - 8432) + chr(50) + '\x37' + chr(0b10000 + 0o47), 0o10), ehT0Px3KOsy9('\x30' + chr(1151 - 1040) + chr(0b101000 + 0o17) + chr(1529 - 1481), 11189 - 11181), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110001) + '\x36' + chr(0b110101), 22155 - 22147), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b1010 + 0o47) + '\067' + chr(50), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(55) + '\062', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(1893 - 1845) + chr(0b111001 + 0o66) + chr(687 - 638) + chr(49) + chr(972 - 921), 0o10), ehT0Px3KOsy9(chr(1727 - 1679) + '\157' + chr(53) + '\x31', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b111 + 0o52) + '\063' + '\066', ord("\x08")), ehT0Px3KOsy9(chr(1072 - 1024) + chr(111) + chr(0b110010) + '\x34' + chr(2280 - 2227), 8), ehT0Px3KOsy9('\060' + '\157' + chr(0b11000 + 0o32) + '\x31' + chr(0b110011), 0o10), ehT0Px3KOsy9(chr(0b101100 + 0o4) + chr(0b100001 + 0o116) + chr(0b110001) + chr(0b11010 + 0o26) + chr(1571 - 1522), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(770 - 659) + chr(0b110011) + chr(55) + chr(0b100001 + 0o24), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x32' + chr(1378 - 1323) + chr(49), 21432 - 21424), ehT0Px3KOsy9(chr(1621 - 1573) + chr(111) + chr(0b110010) + '\066' + chr(0b110111), ord("\x08")), ehT0Px3KOsy9(chr(444 - 396) + chr(0b1001 + 0o146) + '\x32' + '\066', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(51) + '\062' + chr(1510 - 1458), 0b1000), ehT0Px3KOsy9(chr(2046 - 1998) + chr(5532 - 5421) + chr(0b111 + 0o54) + '\x35' + chr(0b110110), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(1295 - 1245) + '\x34' + chr(0b1100 + 0o47), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x32' + '\063' + '\062', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1000100 + 0o53) + '\062' + chr(50) + chr(2612 - 2559), 11947 - 11939), ehT0Px3KOsy9('\x30' + chr(0b10011 + 0o134) + chr(0b110011) + '\067' + chr(50), 0o10), ehT0Px3KOsy9('\x30' + chr(3669 - 3558) + chr(629 - 579) + '\x35' + chr(210 - 162), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1010101 + 0o32) + chr(1790 - 1738) + chr(0b110010), 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b111111 + 0o60) + chr(2337 - 2287) + chr(2897 - 2843) + chr(0b110100), 25009 - 25001), ehT0Px3KOsy9('\060' + '\157' + '\062' + chr(54) + '\060', 30232 - 30224), ehT0Px3KOsy9(chr(48) + chr(9234 - 9123) + '\x33' + chr(52) + chr(1908 - 1857), 0o10), ehT0Px3KOsy9(chr(1477 - 1429) + chr(111) + chr(50) + chr(2487 - 2433) + chr(0b110011), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + '\x6f' + chr(53) + chr(0b110000), 31727 - 31719)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b','), '\x64' + '\145' + chr(0b11000 + 0o113) + chr(0b1101111) + chr(9383 - 9283) + '\x65')(chr(117) + '\164' + chr(102) + chr(0b100110 + 0o7) + chr(0b100 + 0o64)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def rpI5J3rogJbL(oVre8I6UXc3b):
if c2A0yzQpDQB3(xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'e^4\xb4qJ\x9b\xd3\xb9\x9a8\x1e'), chr(0b1000010 + 0o42) + chr(8316 - 8215) + '\x63' + chr(111) + '\144' + '\145')(chr(0b1000010 + 0o63) + chr(0b1110100) + '\x66' + '\055' + '\070'))) > ehT0Px3KOsy9('\060' + chr(5607 - 5496) + chr(1902 - 1854), 8):
hl77AErxYlk5 = oVre8I6UXc3b._get_subplots()
(MKYawqggLZfj, rv1R1vv7yV64) = oVre8I6UXc3b._get_axes_layout()
dwaasw4Cnuks(axarr=hl77AErxYlk5, nplots=c2A0yzQpDQB3(hl77AErxYlk5), naxes=MKYawqggLZfj * rv1R1vv7yV64, nrows=MKYawqggLZfj, ncols=rv1R1vv7yV64, sharex=xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'q|f\x92vZ'), chr(0b1100100) + '\145' + chr(0b1100011) + '\157' + chr(100) + '\145')(chr(117) + chr(8878 - 8762) + '\x66' + chr(0b1110 + 0o37) + chr(0b111000))), sharey=xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'q|f\x92v['), chr(3824 - 3724) + chr(0b1100101) + chr(0b111011 + 0o50) + chr(111) + chr(3063 - 2963) + chr(101))(chr(117) + chr(0b111001 + 0o73) + chr(0b1000110 + 0o40) + chr(0b101101) + '\070')))
for UFCqCPYQEkxy in xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'e^4\xb4qJ\x9b\xd3\xb9\x9a8\x1e'), chr(100) + chr(8781 - 8680) + '\x63' + '\x6f' + chr(0b1100100) + chr(0b10010 + 0o123))(chr(2679 - 2562) + chr(0b11001 + 0o133) + chr(6436 - 6334) + '\x2d' + '\x38')):
if xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'{`n\x83xQ'), chr(3961 - 3861) + '\145' + chr(245 - 146) + '\x6f' + chr(0b10110 + 0o116) + '\145')(chr(0b1110101) + chr(116) + chr(0b111 + 0o137) + '\055' + chr(2307 - 2251))) is not None:
xafqLlk3kkUe(UFCqCPYQEkxy, xafqLlk3kkUe(SXOLrMavuUCe(b'qqs\xbfjV\x84\xc6\xb8\xd1'), chr(100) + chr(0b11001 + 0o114) + chr(0b1100011) + chr(0b100111 + 0o110) + chr(5709 - 5609) + '\x65')(chr(0b110110 + 0o77) + chr(0b1000110 + 0o56) + chr(0b1100110) + '\055' + chr(56)))(xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'{`n\x83xQ'), chr(0b1100100) + chr(128 - 27) + chr(3801 - 3702) + chr(0b1101111) + chr(4276 - 4176) + '\x65')('\x75' + chr(0b101 + 0o157) + '\146' + chr(45) + '\x38')))
if xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'z`n\x83xQ'), '\144' + chr(101) + chr(0b100 + 0o137) + '\x6f' + chr(0b1100100) + '\145')(chr(117) + chr(5699 - 5583) + '\146' + chr(0b101000 + 0o5) + chr(56))) is not None:
xafqLlk3kkUe(UFCqCPYQEkxy, xafqLlk3kkUe(SXOLrMavuUCe(b'qqs\xbfkV\x84\xc6\xb8\xd1'), chr(6957 - 6857) + '\x65' + chr(1494 - 1395) + chr(111) + chr(3690 - 3590) + chr(0b0 + 0o145))(chr(5127 - 5010) + chr(0b1110100) + '\x66' + '\x2d' + '\070'))(xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'z`n\x83xQ'), chr(0b1100100) + chr(0b1100101) + chr(6328 - 6229) + chr(9397 - 9286) + chr(0b101 + 0o137) + '\145')('\165' + chr(116) + '\x66' + chr(45) + chr(0b111000))))
if xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'{xn\x8d'), chr(100) + chr(6354 - 6253) + '\x63' + chr(0b1101111) + chr(100) + chr(9017 - 8916))(chr(0b1110101) + chr(0b1110100) + chr(0b1100110) + '\x2d' + chr(1852 - 1796))) is not None:
xafqLlk3kkUe(UFCqCPYQEkxy, xafqLlk3kkUe(SXOLrMavuUCe(b'qqs\xbfjN\x84\xc8'), chr(0b101100 + 0o70) + chr(0b1100101) + '\143' + chr(0b1011111 + 0o20) + chr(7251 - 7151) + chr(101))(chr(117) + chr(7192 - 7076) + chr(0b1100011 + 0o3) + chr(0b101101) + chr(56)))(xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'{xn\x8d'), '\144' + '\145' + chr(1227 - 1128) + '\x6f' + '\x64' + '\145')(chr(0b1110100 + 0o1) + chr(116) + '\x66' + chr(45) + '\070')))
if xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'zxn\x8d'), '\x64' + chr(5349 - 5248) + chr(3283 - 3184) + '\157' + chr(0b10011 + 0o121) + chr(101))(chr(0b10111 + 0o136) + '\164' + chr(0b1011110 + 0o10) + '\x2d' + chr(0b11001 + 0o37))) is not None:
xafqLlk3kkUe(UFCqCPYQEkxy, xafqLlk3kkUe(SXOLrMavuUCe(b'qqs\xbfkN\x84\xc8'), chr(3901 - 3801) + chr(9058 - 8957) + chr(99) + '\157' + '\x64' + chr(9334 - 9233))(chr(0b1010101 + 0o40) + '\x74' + '\x66' + chr(1383 - 1338) + chr(0b111000)))(xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'zxn\x8d'), '\144' + chr(0b111 + 0o136) + '\x63' + '\x6f' + chr(0b1100100) + chr(0b1100101))(chr(0b1110101) + chr(0b11101 + 0o127) + chr(102) + '\055' + chr(798 - 742))))
xafqLlk3kkUe(UFCqCPYQEkxy, xafqLlk3kkUe(SXOLrMavuUCe(b'efn\x84'), chr(100) + chr(101) + '\x63' + '\x6f' + chr(0b1011111 + 0o5) + chr(0b1011101 + 0o10))('\165' + '\x74' + chr(0b111101 + 0o51) + chr(1603 - 1558) + '\x38'))(xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'efn\x84'), chr(0b1100100) + '\145' + chr(0b1100011) + chr(6356 - 6245) + chr(9835 - 9735) + chr(0b101100 + 0o71))('\165' + '\x74' + chr(102) + chr(0b101 + 0o50) + chr(0b111000))))
if xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'v}s\x8cv'), '\x64' + chr(3367 - 3266) + chr(0b1011110 + 0o5) + chr(111) + chr(0b1100100) + '\145')('\165' + '\164' + chr(102) + '\x2d' + chr(0b1000 + 0o60))):
if xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'qae\x90\x7fM\x99\xd6'), chr(0b1100100) + chr(2662 - 2561) + chr(0b1100011) + chr(111) + '\x64' + chr(101))(chr(0b1101010 + 0o13) + chr(0b1110100) + chr(0b1100110) + chr(0b101101) + '\x38')):
if bAgBF7jXI53B(xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'v}s\x8cv'), '\144' + chr(101) + '\143' + chr(0b1101111) + '\x64' + chr(0b100101 + 0o100))(chr(0b1101111 + 0o6) + chr(0b111 + 0o155) + chr(102) + '\055' + '\070'))):
if c2A0yzQpDQB3(xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'v}s\x8cv'), '\144' + chr(0b1100101) + chr(99) + chr(111) + '\144' + '\145')(chr(0b1100000 + 0o25) + chr(12891 - 12775) + '\146' + chr(0b101100 + 0o1) + '\070'))) != xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'lgb\x92zG\x9e'), chr(100) + chr(0b1100101) + chr(99) + chr(8611 - 8500) + chr(899 - 799) + chr(0b1100101))(chr(8257 - 8140) + chr(6311 - 6195) + '\146' + '\055' + chr(2385 - 2329))):
jtbovtaIYjRB = xafqLlk3kkUe(SXOLrMavuUCe(b"V|b\xc0\x7fG\x83\xc2\xa7\xcaJ\x04\xd9\x18\x15\x0eSt'L>\x85\xe64\x8e\xcd\x97s\xa5\x9b\xc2\xf6\xb5\x8e\xc0G\x94\xde\x96\xde`qu\xc0|D\xcd\xc6\xbc\xce\x1f\x06\xd1KU\x13\\ >Z7\xcb\xeca\x9d\xcd\xdeb\xb8\x8b\xc3\xba\xfa\x9c\x88V\xcd\xc0\x86\x93bxn\x93gB\xcd\xc4\xbd\xc6J\x0b\xccM\x17\nVo?Zc\xf1\xf94\x98\xd9\x99\x1c\xb8\x8b\xcd\xfd\xe1\x92\x88M\xd2\x90\x97\xdavxb\xc0.\x02\x96\xd8\xd9\xcc\x1f\x06\xdd]\x07ZUfkJ1\xc9\xfe,\x93\xca\x97+\xf4\x95\xde"), chr(0b1100100) + '\x65' + chr(6706 - 6607) + chr(0b1000011 + 0o54) + chr(100) + chr(0b111000 + 0o55))(chr(9183 - 9066) + chr(2388 - 2272) + chr(0b100100 + 0o102) + chr(455 - 410) + chr(0b101101 + 0o13)).format(c2A0yzQpDQB3(oVre8I6UXc3b.title), oVre8I6UXc3b.nseries)
raise q1QCh3W88sgk(jtbovtaIYjRB)
for (UFCqCPYQEkxy, IkttdaI0bGlA) in pZ0NK2y6HRbn(xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'e^4\xb4qJ\x9b\xd3\xb9\x9a8\x1e'), chr(100) + chr(0b1100101) + chr(5300 - 5201) + chr(0b1000101 + 0o52) + '\x64' + chr(0b11111 + 0o106))('\165' + '\164' + chr(0b1001 + 0o135) + chr(1995 - 1950) + chr(0b11 + 0o65))), xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'v}s\x8cv'), chr(100) + chr(0b1011110 + 0o7) + '\143' + chr(0b1101111) + '\x64' + chr(101))(chr(0b1100111 + 0o16) + chr(0b1110100) + '\x66' + '\055' + chr(0b111000)))):
xafqLlk3kkUe(UFCqCPYQEkxy, xafqLlk3kkUe(SXOLrMavuUCe(b'qqs\xbfgK\x99\xc9\xb6'), '\x64' + chr(101) + chr(99) + chr(0b1101111) + chr(100) + chr(8317 - 8216))(chr(8188 - 8071) + chr(0b101100 + 0o110) + '\x66' + chr(1777 - 1732) + chr(1997 - 1941)))(IkttdaI0bGlA)
else:
xafqLlk3kkUe(oVre8I6UXc3b.fig, xafqLlk3kkUe(SXOLrMavuUCe(b'qaw\x94zV\x81\xc0'), chr(100) + chr(0b10000 + 0o125) + chr(6967 - 6868) + chr(0b100110 + 0o111) + chr(0b1100100) + '\145')(chr(8579 - 8462) + '\164' + chr(7434 - 7332) + chr(0b101001 + 0o4) + chr(0b100 + 0o64)))(xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'v}s\x8cv'), chr(1330 - 1230) + chr(0b1100101) + chr(0b1100011) + chr(11966 - 11855) + chr(1652 - 1552) + '\x65')(chr(5111 - 4994) + chr(9929 - 9813) + '\x66' + chr(1201 - 1156) + chr(2356 - 2300))))
else:
if bAgBF7jXI53B(xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'v}s\x8cv'), chr(871 - 771) + '\x65' + chr(99) + chr(0b110110 + 0o71) + chr(100) + chr(8363 - 8262))('\x75' + '\x74' + '\146' + chr(0b1000 + 0o45) + '\070'))):
jtbovtaIYjRB = xafqLlk3kkUe(SXOLrMavuUCe(b"Wgn\x8et\x02\x8d\xd1\xba\xd6\x06\x0e\xdf\x18\x1a\x1c\x1at2Y;\x85\xeb-\x94\xca\xc3v\xf4\x87\xd0\xba\xfb\x95\xdc\x02\xc7\xc5\x93\xc3mfs\x85w\x02\x98\xcb\xbf\xc7\x19\x18\x9fX\x06\x0fXp'F*\xd6\xb6\x15\x8f\xcc\xd2v\xf4\x87\xd0\xba\xe5\x9b\xdbQ\xd1\xd4"), chr(100) + '\x65' + chr(99) + chr(111) + chr(5272 - 5172) + chr(8578 - 8477))(chr(0b1011011 + 0o32) + chr(8999 - 8883) + chr(102) + '\055' + chr(1501 - 1445))
raise q1QCh3W88sgk(jtbovtaIYjRB)
xafqLlk3kkUe(oVre8I6UXc3b.axes[ehT0Px3KOsy9(chr(0b10100 + 0o34) + chr(0b1101111) + chr(602 - 554), 8)], xafqLlk3kkUe(SXOLrMavuUCe(b'qqs\xbfgK\x99\xc9\xb6'), '\144' + chr(101) + chr(0b100111 + 0o74) + '\157' + '\x64' + chr(0b1010001 + 0o24))(chr(0b1110101) + chr(0b1110100) + '\146' + '\x2d' + chr(1693 - 1637)))(xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'v}s\x8cv'), chr(6025 - 5925) + chr(0b101111 + 0o66) + chr(99) + chr(111) + chr(0b101100 + 0o70) + chr(1013 - 912))(chr(0b10000 + 0o145) + '\164' + chr(0b1000111 + 0o37) + '\055' + chr(0b101110 + 0o12))))
|
pandas-dev/pandas
|
pandas/plotting/_core.py
|
MPLPlot._apply_axis_properties
|
def _apply_axis_properties(self, axis, rot=None, fontsize=None):
""" Tick creation within matplotlib is reasonably expensive and is
internally deferred until accessed as Ticks are created/destroyed
multiple times per draw. It's therefore beneficial for us to avoid
accessing unless we will act on the Tick.
"""
if rot is not None or fontsize is not None:
# rot=0 is a valid setting, hence the explicit None check
labels = axis.get_majorticklabels() + axis.get_minorticklabels()
for label in labels:
if rot is not None:
label.set_rotation(rot)
if fontsize is not None:
label.set_fontsize(fontsize)
|
python
|
def _apply_axis_properties(self, axis, rot=None, fontsize=None):
""" Tick creation within matplotlib is reasonably expensive and is
internally deferred until accessed as Ticks are created/destroyed
multiple times per draw. It's therefore beneficial for us to avoid
accessing unless we will act on the Tick.
"""
if rot is not None or fontsize is not None:
# rot=0 is a valid setting, hence the explicit None check
labels = axis.get_majorticklabels() + axis.get_minorticklabels()
for label in labels:
if rot is not None:
label.set_rotation(rot)
if fontsize is not None:
label.set_fontsize(fontsize)
|
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",",
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",",
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"None",
")",
":",
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"labels",
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")",
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"is",
"not",
"None",
":",
"label",
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"set_fontsize",
"(",
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")"
] |
Tick creation within matplotlib is reasonably expensive and is
internally deferred until accessed as Ticks are created/destroyed
multiple times per draw. It's therefore beneficial for us to avoid
accessing unless we will act on the Tick.
|
[
"Tick",
"creation",
"within",
"matplotlib",
"is",
"reasonably",
"expensive",
"and",
"is",
"internally",
"deferred",
"until",
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"are",
"created",
"/",
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"draw",
".",
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"s",
"therefore",
"beneficial",
"for",
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"accessing",
"unless",
"we",
"will",
"act",
"on",
"the",
"Tick",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/plotting/_core.py#L489-L503
|
train
|
Applies the axis properties to the internal data structures.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b11110 + 0o22) + '\157' + chr(51) + '\061' + chr(0b100100 + 0o17), 0b1000), ehT0Px3KOsy9('\x30' + chr(9307 - 9196) + chr(0b110101) + chr(51), 20118 - 20110), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(612 - 561) + chr(0b100111 + 0o11) + chr(1132 - 1081), 0b1000), ehT0Px3KOsy9(chr(1571 - 1523) + chr(0b1101111) + chr(1436 - 1386) + '\062' + chr(55), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(2546 - 2495) + chr(0b110101), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110011) + '\060' + chr(50), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b10010 + 0o41) + '\x31' + chr(54), 39930 - 39922), ehT0Px3KOsy9(chr(0b1 + 0o57) + '\x6f' + chr(49) + chr(0b110110) + chr(52), 26697 - 26689), ehT0Px3KOsy9(chr(48) + chr(0b1100011 + 0o14) + chr(2360 - 2311) + chr(0b110011) + chr(50), 29011 - 29003), ehT0Px3KOsy9(chr(0b110000 + 0o0) + '\x6f' + chr(50) + chr(2066 - 2015), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(2816 - 2705) + chr(0b10010 + 0o41) + chr(55) + chr(0b110001), 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(50) + chr(48) + '\x35', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b10111 + 0o130) + '\x32' + chr(0b110001 + 0o2) + '\x32', 54894 - 54886), ehT0Px3KOsy9(chr(1520 - 1472) + chr(0b1101011 + 0o4) + chr(49) + chr(49) + chr(883 - 833), 58367 - 58359), ehT0Px3KOsy9(chr(1713 - 1665) + chr(10577 - 10466) + '\x33' + chr(0b110101) + '\x36', 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(50) + chr(0b110010) + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(745 - 697) + chr(0b1110 + 0o141) + chr(51) + chr(0b1010 + 0o55) + chr(53), 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(49) + chr(48) + chr(821 - 770), 47568 - 47560), ehT0Px3KOsy9('\060' + chr(0b1101001 + 0o6) + '\x37' + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(584 - 536) + chr(994 - 883) + '\061' + chr(0b100110 + 0o17) + '\067', 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(49) + '\x31' + '\x37', 0o10), ehT0Px3KOsy9(chr(725 - 677) + chr(10320 - 10209) + '\x33' + '\061' + '\x30', 6746 - 6738), ehT0Px3KOsy9('\x30' + chr(11264 - 11153) + '\x32' + chr(220 - 166), 0o10), ehT0Px3KOsy9('\060' + chr(0b1 + 0o156) + '\x31' + chr(488 - 438) + chr(49), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110001) + '\061', 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\062' + chr(0b110001) + chr(0b110110), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(0b110010) + chr(0b1111 + 0o44) + '\x33', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(395 - 344) + '\061' + '\x32', 44360 - 44352), ehT0Px3KOsy9(chr(48) + chr(0b110101 + 0o72) + chr(0b110111) + chr(51), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(54) + chr(0b1000 + 0o50), ord("\x08")), ehT0Px3KOsy9(chr(0b101010 + 0o6) + '\157' + chr(0b100011 + 0o16) + '\066' + chr(209 - 160), ord("\x08")), ehT0Px3KOsy9(chr(0b101010 + 0o6) + chr(0b110101 + 0o72) + chr(0b110100) + chr(52), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(2327 - 2277) + chr(0b110111) + chr(50), 54116 - 54108), ehT0Px3KOsy9(chr(1746 - 1698) + '\157' + '\x33' + chr(0b110101) + chr(48), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1100111 + 0o10) + chr(50) + '\x30' + chr(49), 0o10), ehT0Px3KOsy9(chr(1781 - 1733) + chr(0b1010010 + 0o35) + '\063' + chr(54) + chr(0b1110 + 0o47), 13976 - 13968), ehT0Px3KOsy9(chr(201 - 153) + '\157' + '\x34' + chr(49), 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(2081 - 2031) + '\062' + chr(1935 - 1887), 0b1000), ehT0Px3KOsy9('\060' + chr(0b100 + 0o153) + chr(0b11100 + 0o26) + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(0b1011 + 0o45) + chr(111) + '\063' + '\x34' + chr(0b110000), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110101) + '\x30', 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xe5'), chr(3828 - 3728) + chr(101) + chr(0b1100011) + '\157' + '\x64' + '\145')('\165' + '\x74' + chr(102) + chr(0b11000 + 0o25) + chr(0b110101 + 0o3)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def p9MGLZP7NbaT(oVre8I6UXc3b, cRTh61qyvi24, xhqfUfhWcy58=None, TDEJPHYIHA5z=None):
if xhqfUfhWcy58 is not None or TDEJPHYIHA5z is not None:
uXMK81tmdpTM = cRTh61qyvi24.get_majorticklabels() + cRTh61qyvi24.get_minorticklabels()
for TRUOLFLuD08x in uXMK81tmdpTM:
if xhqfUfhWcy58 is not None:
xafqLlk3kkUe(TRUOLFLuD08x, xafqLlk3kkUe(SXOLrMavuUCe(b'\xb8N\xb7\xc8o\xad\xba\x15.z\x96\xeb'), chr(100) + chr(101) + chr(0b1100011) + chr(111) + chr(0b1100100) + chr(101))(chr(0b1110101) + '\164' + '\146' + '\055' + '\070'))(xhqfUfhWcy58)
if TDEJPHYIHA5z is not None:
xafqLlk3kkUe(TRUOLFLuD08x, xafqLlk3kkUe(SXOLrMavuUCe(b'\xb8N\xb7\xc8{\xad\xa0\x00)z\x83\xe0'), chr(961 - 861) + chr(3617 - 3516) + '\x63' + '\157' + chr(0b1100100) + chr(5006 - 4905))(chr(0b1110101) + '\164' + '\x66' + chr(45) + chr(56)))(TDEJPHYIHA5z)
|
pandas-dev/pandas
|
pandas/plotting/_core.py
|
MPLPlot._get_ax_layer
|
def _get_ax_layer(cls, ax, primary=True):
"""get left (primary) or right (secondary) axes"""
if primary:
return getattr(ax, 'left_ax', ax)
else:
return getattr(ax, 'right_ax', ax)
|
python
|
def _get_ax_layer(cls, ax, primary=True):
"""get left (primary) or right (secondary) axes"""
if primary:
return getattr(ax, 'left_ax', ax)
else:
return getattr(ax, 'right_ax', ax)
|
[
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"ax",
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"=",
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")",
"else",
":",
"return",
"getattr",
"(",
"ax",
",",
"'right_ax'",
",",
"ax",
")"
] |
get left (primary) or right (secondary) axes
|
[
"get",
"left",
"(",
"primary",
")",
"or",
"right",
"(",
"secondary",
")",
"axes"
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/plotting/_core.py#L644-L649
|
train
|
get the layer of the specified axes
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + chr(0b1001110 + 0o41) + chr(0b110011) + chr(0b10100 + 0o40) + chr(0b100100 + 0o15), 5852 - 5844), ehT0Px3KOsy9('\060' + chr(111) + '\x32' + chr(51) + chr(0b10000 + 0o42), 63299 - 63291), ehT0Px3KOsy9(chr(0b110000) + chr(1356 - 1245) + '\065' + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110111) + '\066', 65108 - 65100), ehT0Px3KOsy9('\060' + chr(0b1011100 + 0o23) + '\x33' + chr(0b1010 + 0o53) + chr(436 - 382), 65024 - 65016), ehT0Px3KOsy9(chr(0b11101 + 0o23) + '\157' + '\x33' + '\x32' + chr(1831 - 1782), 0o10), ehT0Px3KOsy9(chr(1457 - 1409) + chr(0b1011010 + 0o25) + chr(0b110101) + chr(0b101101 + 0o6), 8), ehT0Px3KOsy9(chr(48) + chr(111) + '\x31' + '\x30' + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(893 - 845) + '\x6f' + chr(1007 - 958) + chr(202 - 149) + chr(0b1001 + 0o52), ord("\x08")), ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(497 - 386) + chr(0b100 + 0o56) + '\065' + chr(0b10000 + 0o45), 21860 - 21852), ehT0Px3KOsy9(chr(2109 - 2061) + '\157' + '\x36' + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + '\061' + chr(0b110000) + '\x31', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1011100 + 0o23) + chr(0b110010) + '\061' + chr(49), 0o10), ehT0Px3KOsy9(chr(902 - 854) + chr(111) + chr(316 - 266) + chr(48) + '\067', ord("\x08")), ehT0Px3KOsy9(chr(0b11011 + 0o25) + chr(0b1101111) + '\062' + '\067', 63706 - 63698), ehT0Px3KOsy9(chr(1360 - 1312) + chr(0b1101111) + chr(2280 - 2229) + '\x36' + chr(0b11011 + 0o31), 0b1000), ehT0Px3KOsy9(chr(495 - 447) + '\157' + chr(0b1001 + 0o52) + chr(0b110001) + '\061', 31452 - 31444), ehT0Px3KOsy9(chr(689 - 641) + chr(111) + '\063' + '\x37', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b100000 + 0o21) + chr(0b101 + 0o61) + '\060', ord("\x08")), ehT0Px3KOsy9(chr(0b11 + 0o55) + chr(11828 - 11717) + '\063' + '\067', 8), ehT0Px3KOsy9(chr(0b100011 + 0o15) + chr(111) + '\x31' + chr(0b100001 + 0o20), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b100010 + 0o17) + chr(48) + chr(53), 50422 - 50414), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(50) + '\064' + chr(2119 - 2069), 22279 - 22271), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x33' + chr(48) + '\064', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101000 + 0o7) + chr(747 - 693) + chr(0b110100), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x32' + '\x32' + '\x36', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x34' + chr(1265 - 1216), 0o10), ehT0Px3KOsy9(chr(0b11011 + 0o25) + chr(5458 - 5347) + '\x33' + '\062' + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(0b1101 + 0o43) + '\157' + chr(49) + '\x31', 8), ehT0Px3KOsy9(chr(48) + '\157' + chr(49) + '\x37' + chr(0b11011 + 0o25), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\062' + '\062', ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(0b110001) + chr(0b11 + 0o55), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(157 - 105), 29448 - 29440), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(54) + chr(0b110111), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(1377 - 1326) + '\x31' + '\065', 23127 - 23119), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110011) + '\067' + chr(443 - 392), 0o10), ehT0Px3KOsy9(chr(1622 - 1574) + '\157' + chr(0b1111 + 0o44) + chr(50) + chr(0b110001), 8), ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(111) + chr(0b110001) + chr(53) + chr(0b110011), 8), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b10001 + 0o41) + chr(2002 - 1948) + '\060', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(51) + chr(650 - 601) + '\067', 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + '\x6f' + '\065' + chr(651 - 603), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xcf'), '\x64' + '\x65' + chr(0b1100011) + chr(0b1101111) + '\144' + chr(0b1100101))(chr(0b1110101) + chr(0b1110100) + '\x66' + chr(45) + chr(0b10111 + 0o41)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def an_VdGcgrZ_0(NSstowUUZlxS, UFCqCPYQEkxy, YPGtlr8Jlk0w=ehT0Px3KOsy9('\060' + chr(111) + chr(311 - 262), 0b1000)):
if YPGtlr8Jlk0w:
return xafqLlk3kkUe(UFCqCPYQEkxy, xafqLlk3kkUe(SXOLrMavuUCe(b'\x8d\xffMJ\xb1\xb0S'), chr(0b1100100) + chr(5529 - 5428) + chr(99) + '\x6f' + chr(0b10 + 0o142) + chr(0b110011 + 0o62))(chr(117) + '\164' + chr(0b1100110) + chr(872 - 827) + chr(395 - 339)), UFCqCPYQEkxy)
else:
return xafqLlk3kkUe(UFCqCPYQEkxy, xafqLlk3kkUe(SXOLrMavuUCe(b'\x93\xf3LV\x9a\x8eJ>'), chr(0b110000 + 0o64) + chr(101) + chr(0b1000110 + 0o35) + chr(11617 - 11506) + chr(0b1011011 + 0o11) + chr(0b1010010 + 0o23))('\x75' + chr(0b111111 + 0o65) + '\146' + '\x2d' + chr(1077 - 1021)), UFCqCPYQEkxy)
|
pandas-dev/pandas
|
pandas/plotting/_core.py
|
MPLPlot._apply_style_colors
|
def _apply_style_colors(self, colors, kwds, col_num, label):
"""
Manage style and color based on column number and its label.
Returns tuple of appropriate style and kwds which "color" may be added.
"""
style = None
if self.style is not None:
if isinstance(self.style, list):
try:
style = self.style[col_num]
except IndexError:
pass
elif isinstance(self.style, dict):
style = self.style.get(label, style)
else:
style = self.style
has_color = 'color' in kwds or self.colormap is not None
nocolor_style = style is None or re.match('[a-z]+', style) is None
if (has_color or self.subplots) and nocolor_style:
kwds['color'] = colors[col_num % len(colors)]
return style, kwds
|
python
|
def _apply_style_colors(self, colors, kwds, col_num, label):
"""
Manage style and color based on column number and its label.
Returns tuple of appropriate style and kwds which "color" may be added.
"""
style = None
if self.style is not None:
if isinstance(self.style, list):
try:
style = self.style[col_num]
except IndexError:
pass
elif isinstance(self.style, dict):
style = self.style.get(label, style)
else:
style = self.style
has_color = 'color' in kwds or self.colormap is not None
nocolor_style = style is None or re.match('[a-z]+', style) is None
if (has_color or self.subplots) and nocolor_style:
kwds['color'] = colors[col_num % len(colors)]
return style, kwds
|
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] |
Manage style and color based on column number and its label.
Returns tuple of appropriate style and kwds which "color" may be added.
|
[
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"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/plotting/_core.py#L672-L693
|
train
|
Applies color to the style and kwds.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + chr(0b1101111) + '\062' + chr(1399 - 1348) + '\x32', 7311 - 7303), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(2084 - 2034) + chr(1543 - 1493) + chr(963 - 910), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(50) + chr(0b110111) + chr(55), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1001100 + 0o43) + '\061' + chr(0b101111 + 0o3) + '\x30', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x32' + '\x37', ord("\x08")), ehT0Px3KOsy9(chr(1504 - 1456) + chr(111) + '\x33' + chr(689 - 641) + chr(0b11111 + 0o25), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + '\061' + chr(1692 - 1640) + '\066', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(50) + chr(51) + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(1284 - 1236) + '\157' + '\x33' + chr(1308 - 1255) + chr(527 - 476), 42732 - 42724), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(2297 - 2247) + chr(0b110010) + '\x34', 0b1000), ehT0Px3KOsy9(chr(0b101 + 0o53) + chr(7706 - 7595) + '\x31' + '\x35' + '\062', ord("\x08")), ehT0Px3KOsy9(chr(2238 - 2190) + chr(4891 - 4780) + chr(0b110111) + chr(734 - 686), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110100 + 0o3) + chr(0b10001 + 0o40), 0o10), ehT0Px3KOsy9('\x30' + chr(2663 - 2552) + '\x31' + '\067' + chr(0b11001 + 0o34), 50000 - 49992), ehT0Px3KOsy9(chr(1095 - 1047) + chr(9027 - 8916) + chr(0b110001) + chr(1933 - 1885) + '\061', ord("\x08")), ehT0Px3KOsy9(chr(0b101111 + 0o1) + chr(0b1011 + 0o144) + chr(51) + chr(1320 - 1271) + chr(1300 - 1245), ord("\x08")), ehT0Px3KOsy9('\060' + chr(9311 - 9200) + chr(0b110011) + chr(0b10100 + 0o34), 44480 - 44472), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110010) + chr(0b110010) + chr(50), 0o10), ehT0Px3KOsy9(chr(0b11110 + 0o22) + chr(0b100011 + 0o114) + '\066' + chr(518 - 464), 48319 - 48311), ehT0Px3KOsy9(chr(0b110000) + chr(0b100001 + 0o116) + '\x31' + chr(0b110001) + chr(49), 0b1000), ehT0Px3KOsy9(chr(645 - 597) + chr(10000 - 9889) + chr(0b110010) + chr(0b101100 + 0o7) + '\061', 0o10), ehT0Px3KOsy9('\060' + chr(0b110001 + 0o76) + '\x35' + chr(55), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + '\062' + '\065' + '\x35', 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110001) + chr(0b11011 + 0o34) + chr(51), 35201 - 35193), ehT0Px3KOsy9('\060' + '\157' + '\062' + chr(0b110111) + chr(49), 42430 - 42422), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110100 + 0o0) + chr(1471 - 1417), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b10100 + 0o133) + chr(49) + chr(0b11101 + 0o32) + chr(0b110100), 0o10), ehT0Px3KOsy9('\060' + chr(0b111001 + 0o66) + chr(49) + chr(1116 - 1068) + chr(0b11111 + 0o23), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(3451 - 3340) + '\x32' + chr(0b110100) + '\062', ord("\x08")), ehT0Px3KOsy9(chr(1895 - 1847) + chr(0b1101001 + 0o6) + '\x32' + chr(0b10101 + 0o34) + '\061', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\064' + chr(89 - 41), ord("\x08")), ehT0Px3KOsy9(chr(1444 - 1396) + '\x6f' + '\062' + '\x34' + chr(50), 8), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110011) + chr(0b110000 + 0o1) + chr(0b110010 + 0o1), 0o10), ehT0Px3KOsy9('\x30' + chr(10933 - 10822) + chr(1071 - 1020) + '\x31' + '\x36', 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(6804 - 6693) + chr(50) + chr(53) + chr(756 - 702), 10704 - 10696), ehT0Px3KOsy9('\060' + '\157' + '\x31' + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b11000 + 0o127) + chr(0b101011 + 0o13) + '\065', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(11742 - 11631) + '\062' + chr(0b110011) + chr(53), 8), ehT0Px3KOsy9('\x30' + chr(5995 - 5884) + chr(1415 - 1361) + chr(53), 8)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + chr(111) + chr(0b1110 + 0o47) + chr(48), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xb4'), '\144' + '\x65' + chr(0b1100011) + chr(0b1101101 + 0o2) + '\x64' + '\x65')(chr(0b1110101) + '\x74' + '\146' + chr(0b101101) + chr(912 - 856)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def X6fw8B_hbL6w(oVre8I6UXc3b, bVKMf_d5jJzc, ClrkdavlbKME, hc42BvV92j3e, TRUOLFLuD08x):
Y9SJzuHoKULU = None
if xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\xe9\xe1\xc6<r'), chr(9963 - 9863) + '\145' + chr(0b1100011) + chr(111) + chr(0b101100 + 0o70) + chr(101))('\165' + chr(0b1110100) + '\x66' + chr(0b1100 + 0o41) + '\x38')) is not None:
if PlSM16l2KDPD(xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\xe9\xe1\xc6<r'), chr(0b110011 + 0o61) + chr(0b100100 + 0o101) + '\143' + chr(0b1100 + 0o143) + '\x64' + '\145')(chr(117) + '\164' + chr(0b1001011 + 0o33) + chr(45) + chr(0b111000))), YyaZ4tpXu4lf):
try:
Y9SJzuHoKULU = oVre8I6UXc3b.style[hc42BvV92j3e]
except _fsda0v2_OKU:
pass
elif PlSM16l2KDPD(xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\xe9\xe1\xc6<r'), '\x64' + '\x65' + '\143' + '\157' + '\x64' + chr(0b1100101))('\x75' + '\x74' + '\146' + chr(1603 - 1558) + chr(0b101111 + 0o11))), wLqBDw8l0eIm):
Y9SJzuHoKULU = oVre8I6UXc3b.style.get(TRUOLFLuD08x, Y9SJzuHoKULU)
else:
Y9SJzuHoKULU = oVre8I6UXc3b.style
tHmf3jXZW3tw = xafqLlk3kkUe(SXOLrMavuUCe(b'\xf9\xfa\xd3?e'), chr(0b1100100) + '\145' + '\143' + chr(0b11100 + 0o123) + chr(8650 - 8550) + chr(101))('\x75' + chr(0b1110100) + '\x66' + chr(0b101101) + chr(0b110100 + 0o4)) in ClrkdavlbKME or oVre8I6UXc3b.colormap is not None
H6uMmvowi0uH = Y9SJzuHoKULU is None or _7u55U49WwX2.match(xafqLlk3kkUe(SXOLrMavuUCe(b'\xc1\xf4\x92*J\xef'), chr(4209 - 4109) + '\x65' + chr(0b110011 + 0o60) + chr(111) + chr(100) + chr(5702 - 5601))('\x75' + '\164' + '\146' + '\x2d' + chr(734 - 678)), Y9SJzuHoKULU) is None
if (tHmf3jXZW3tw or xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\xe9\xe0\xdd {\xab\x12\xee'), '\x64' + chr(101) + '\x63' + '\x6f' + chr(0b1100100) + chr(0b1100101 + 0o0))(chr(0b1001100 + 0o51) + chr(0b1101001 + 0o13) + chr(0b1100110) + chr(0b100111 + 0o6) + chr(0b10111 + 0o41)))) and H6uMmvowi0uH:
ClrkdavlbKME[xafqLlk3kkUe(SXOLrMavuUCe(b'\xf9\xfa\xd3?e'), '\144' + chr(9025 - 8924) + chr(0b1011111 + 0o4) + chr(11458 - 11347) + chr(4948 - 4848) + '\145')('\165' + chr(1686 - 1570) + '\x66' + chr(0b101101) + chr(1481 - 1425))] = bVKMf_d5jJzc[hc42BvV92j3e % c2A0yzQpDQB3(bVKMf_d5jJzc)]
return (Y9SJzuHoKULU, ClrkdavlbKME)
|
pandas-dev/pandas
|
pandas/plotting/_core.py
|
MPLPlot._parse_errorbars
|
def _parse_errorbars(self, label, err):
"""
Look for error keyword arguments and return the actual errorbar data
or return the error DataFrame/dict
Error bars can be specified in several ways:
Series: the user provides a pandas.Series object of the same
length as the data
ndarray: provides a np.ndarray of the same length as the data
DataFrame/dict: error values are paired with keys matching the
key in the plotted DataFrame
str: the name of the column within the plotted DataFrame
"""
if err is None:
return None
def match_labels(data, e):
e = e.reindex(data.index)
return e
# key-matched DataFrame
if isinstance(err, ABCDataFrame):
err = match_labels(self.data, err)
# key-matched dict
elif isinstance(err, dict):
pass
# Series of error values
elif isinstance(err, ABCSeries):
# broadcast error series across data
err = match_labels(self.data, err)
err = np.atleast_2d(err)
err = np.tile(err, (self.nseries, 1))
# errors are a column in the dataframe
elif isinstance(err, str):
evalues = self.data[err].values
self.data = self.data[self.data.columns.drop(err)]
err = np.atleast_2d(evalues)
err = np.tile(err, (self.nseries, 1))
elif is_list_like(err):
if is_iterator(err):
err = np.atleast_2d(list(err))
else:
# raw error values
err = np.atleast_2d(err)
err_shape = err.shape
# asymmetrical error bars
if err.ndim == 3:
if (err_shape[0] != self.nseries) or \
(err_shape[1] != 2) or \
(err_shape[2] != len(self.data)):
msg = "Asymmetrical error bars should be provided " + \
"with the shape (%u, 2, %u)" % \
(self.nseries, len(self.data))
raise ValueError(msg)
# broadcast errors to each data series
if len(err) == 1:
err = np.tile(err, (self.nseries, 1))
elif is_number(err):
err = np.tile([err], (self.nseries, len(self.data)))
else:
msg = "No valid {label} detected".format(label=label)
raise ValueError(msg)
return err
|
python
|
def _parse_errorbars(self, label, err):
"""
Look for error keyword arguments and return the actual errorbar data
or return the error DataFrame/dict
Error bars can be specified in several ways:
Series: the user provides a pandas.Series object of the same
length as the data
ndarray: provides a np.ndarray of the same length as the data
DataFrame/dict: error values are paired with keys matching the
key in the plotted DataFrame
str: the name of the column within the plotted DataFrame
"""
if err is None:
return None
def match_labels(data, e):
e = e.reindex(data.index)
return e
# key-matched DataFrame
if isinstance(err, ABCDataFrame):
err = match_labels(self.data, err)
# key-matched dict
elif isinstance(err, dict):
pass
# Series of error values
elif isinstance(err, ABCSeries):
# broadcast error series across data
err = match_labels(self.data, err)
err = np.atleast_2d(err)
err = np.tile(err, (self.nseries, 1))
# errors are a column in the dataframe
elif isinstance(err, str):
evalues = self.data[err].values
self.data = self.data[self.data.columns.drop(err)]
err = np.atleast_2d(evalues)
err = np.tile(err, (self.nseries, 1))
elif is_list_like(err):
if is_iterator(err):
err = np.atleast_2d(list(err))
else:
# raw error values
err = np.atleast_2d(err)
err_shape = err.shape
# asymmetrical error bars
if err.ndim == 3:
if (err_shape[0] != self.nseries) or \
(err_shape[1] != 2) or \
(err_shape[2] != len(self.data)):
msg = "Asymmetrical error bars should be provided " + \
"with the shape (%u, 2, %u)" % \
(self.nseries, len(self.data))
raise ValueError(msg)
# broadcast errors to each data series
if len(err) == 1:
err = np.tile(err, (self.nseries, 1))
elif is_number(err):
err = np.tile([err], (self.nseries, len(self.data)))
else:
msg = "No valid {label} detected".format(label=label)
raise ValueError(msg)
return err
|
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] |
Look for error keyword arguments and return the actual errorbar data
or return the error DataFrame/dict
Error bars can be specified in several ways:
Series: the user provides a pandas.Series object of the same
length as the data
ndarray: provides a np.ndarray of the same length as the data
DataFrame/dict: error values are paired with keys matching the
key in the plotted DataFrame
str: the name of the column within the plotted DataFrame
|
[
"Look",
"for",
"error",
"keyword",
"arguments",
"and",
"return",
"the",
"actual",
"errorbar",
"data",
"or",
"return",
"the",
"error",
"DataFrame",
"/",
"dict"
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/plotting/_core.py#L703-L776
|
train
|
Parse error bars and return the actual errorbar data.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x33' + chr(1852 - 1803), 0o10), ehT0Px3KOsy9('\x30' + chr(8528 - 8417) + chr(0b110001) + chr(0b10101 + 0o35) + chr(53), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + '\x32' + '\x33' + chr(0b111 + 0o51), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(4720 - 4609) + chr(1396 - 1345) + chr(0b110101) + chr(0b1 + 0o66), 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(0b1111 + 0o42) + chr(121 - 72) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x33' + '\x37' + '\060', 13125 - 13117), ehT0Px3KOsy9(chr(0b11110 + 0o22) + chr(111) + chr(0b100 + 0o61) + chr(0b110110), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110010) + '\063' + chr(0b11010 + 0o35), 0o10), ehT0Px3KOsy9(chr(592 - 544) + chr(0b1001001 + 0o46) + '\x37', 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + '\060', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1011000 + 0o27) + chr(0b110001) + '\067' + chr(48), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110001) + chr(0b11 + 0o61) + chr(50), 0o10), ehT0Px3KOsy9('\060' + chr(5803 - 5692) + '\065' + chr(627 - 573), 8), ehT0Px3KOsy9('\060' + chr(5920 - 5809) + chr(1480 - 1431) + chr(0b110000) + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + '\065' + chr(0b110001 + 0o0), 64195 - 64187), ehT0Px3KOsy9(chr(0b110000) + chr(0b101 + 0o152) + chr(0b110001) + '\064' + '\x32', 8), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110001) + chr(426 - 376) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(0b101111 + 0o1) + chr(0b101011 + 0o104) + chr(0b110011) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(2194 - 2146) + '\x6f' + '\063' + '\064' + chr(54), 3735 - 3727), ehT0Px3KOsy9('\x30' + chr(10983 - 10872) + '\x31' + chr(0b101100 + 0o12) + '\067', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1011 + 0o144) + '\063' + '\x32' + '\x32', 1111 - 1103), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110011) + chr(0b100010 + 0o17) + chr(52), 0o10), ehT0Px3KOsy9(chr(48) + chr(7649 - 7538) + chr(2341 - 2292) + chr(0b110000) + chr(2084 - 2033), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x33' + '\x30' + chr(51), 0b1000), ehT0Px3KOsy9('\x30' + chr(6092 - 5981) + chr(0b110011) + '\064' + chr(50), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1001000 + 0o47) + '\x31' + chr(51) + chr(0b110001), 28901 - 28893), ehT0Px3KOsy9(chr(1776 - 1728) + chr(6048 - 5937) + chr(2300 - 2249) + chr(53) + '\061', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b110110 + 0o71) + chr(0b100100 + 0o16) + chr(1387 - 1339) + chr(1318 - 1263), 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(51) + chr(0b100101 + 0o21) + chr(1313 - 1263), 64975 - 64967), ehT0Px3KOsy9(chr(226 - 178) + '\157' + '\061' + '\063', 40654 - 40646), ehT0Px3KOsy9(chr(0b110000) + chr(0b10 + 0o155) + chr(757 - 709), 8), ehT0Px3KOsy9('\x30' + chr(0b1110 + 0o141) + '\x32' + chr(0b110000) + chr(1483 - 1428), 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101001 + 0o6) + chr(1059 - 1009) + chr(2184 - 2131) + chr(0b10111 + 0o40), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110111) + chr(52), 34173 - 34165), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x32' + '\x36' + chr(50), 19880 - 19872), ehT0Px3KOsy9(chr(48) + chr(1063 - 952) + chr(708 - 658) + chr(1512 - 1464) + chr(683 - 635), 0o10), ehT0Px3KOsy9('\x30' + chr(0b100111 + 0o110) + chr(0b110001) + '\060' + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(0b11110 + 0o22) + chr(0b110010 + 0o75) + '\062' + chr(111 - 60) + '\061', 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + '\x32' + chr(2305 - 2252) + '\060', 0b1000), ehT0Px3KOsy9(chr(778 - 730) + '\157' + '\x32' + '\065' + '\x30', 8)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b1 + 0o57) + chr(0b1101000 + 0o7) + '\065' + chr(0b110000), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'7'), '\x64' + chr(0b101101 + 0o70) + chr(99) + '\x6f' + chr(100) + chr(101))('\165' + chr(0b110101 + 0o77) + '\146' + chr(0b101101) + chr(2616 - 2560)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def Yn2Zt4O_Mclu(oVre8I6UXc3b, TRUOLFLuD08x, n8HlHl2rqNTp):
if n8HlHl2rqNTp is None:
return None
def U1fCT4p4K1oL(ULnjp6D6efFH, GlnVAPeT6CUe):
GlnVAPeT6CUe = GlnVAPeT6CUe.reindex(ULnjp6D6efFH.XdowRbJKZWL9)
return GlnVAPeT6CUe
if PlSM16l2KDPD(n8HlHl2rqNTp, PfLVfTFho5T0):
n8HlHl2rqNTp = U1fCT4p4K1oL(oVre8I6UXc3b.ULnjp6D6efFH, n8HlHl2rqNTp)
elif PlSM16l2KDPD(n8HlHl2rqNTp, wLqBDw8l0eIm):
pass
elif PlSM16l2KDPD(n8HlHl2rqNTp, essMXh4s9f1w):
n8HlHl2rqNTp = U1fCT4p4K1oL(oVre8I6UXc3b.ULnjp6D6efFH, n8HlHl2rqNTp)
n8HlHl2rqNTp = WqUC3KWvYVup.atleast_2d(n8HlHl2rqNTp)
n8HlHl2rqNTp = WqUC3KWvYVup.tile(n8HlHl2rqNTp, (oVre8I6UXc3b.nseries, ehT0Px3KOsy9('\x30' + chr(1470 - 1359) + chr(0b110001), 0b1000)))
elif PlSM16l2KDPD(n8HlHl2rqNTp, M8_cKLkHVB2V):
zg6pi5B9cTbJ = oVre8I6UXc3b.data[n8HlHl2rqNTp].SPnCNu54H1db
oVre8I6UXc3b.ULnjp6D6efFH = oVre8I6UXc3b.ULnjp6D6efFH[oVre8I6UXc3b.data.columns.drop(n8HlHl2rqNTp)]
n8HlHl2rqNTp = WqUC3KWvYVup.atleast_2d(zg6pi5B9cTbJ)
n8HlHl2rqNTp = WqUC3KWvYVup.tile(n8HlHl2rqNTp, (oVre8I6UXc3b.nseries, ehT0Px3KOsy9('\060' + chr(111) + chr(0b110001), 8)))
elif bAgBF7jXI53B(n8HlHl2rqNTp):
if K1eAFuc8YyNU(n8HlHl2rqNTp):
n8HlHl2rqNTp = WqUC3KWvYVup.atleast_2d(YyaZ4tpXu4lf(n8HlHl2rqNTp))
else:
n8HlHl2rqNTp = WqUC3KWvYVup.atleast_2d(n8HlHl2rqNTp)
_jHiN4Dh3IBd = n8HlHl2rqNTp.shape
if xafqLlk3kkUe(n8HlHl2rqNTp, xafqLlk3kkUe(SXOLrMavuUCe(b'~:\xf5\x9f\x00\xbaG\xcbtf26'), '\x64' + chr(101) + chr(0b11010 + 0o111) + chr(0b110001 + 0o76) + chr(0b1100100) + '\x65')(chr(8224 - 8107) + chr(9201 - 9085) + chr(0b1100011 + 0o3) + '\x2d' + '\070')) == ehT0Px3KOsy9(chr(1765 - 1717) + chr(0b1011110 + 0o21) + '\063', 0b1000):
if _jHiN4Dh3IBd[ehT0Px3KOsy9(chr(48) + '\157' + chr(0b10101 + 0o33), 8)] != xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'w&\xfd\x9d!\x9d]'), '\x64' + chr(101) + chr(111 - 12) + chr(0b1101111) + chr(2975 - 2875) + '\x65')(chr(9167 - 9050) + '\164' + '\x66' + chr(0b11100 + 0o21) + chr(0b111000))) or _jHiN4Dh3IBd[ehT0Px3KOsy9('\x30' + chr(6822 - 6711) + chr(0b110001), 8)] != ehT0Px3KOsy9('\x30' + chr(10742 - 10631) + '\062', 3665 - 3657) or _jHiN4Dh3IBd[ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x32', 8)] != c2A0yzQpDQB3(xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'L\x19\xf6\x858\xcej\xa9bf>*'), chr(100) + chr(101) + chr(8915 - 8816) + chr(111) + chr(0b10100 + 0o120) + '\x65')(chr(0b1110101) + '\164' + chr(4952 - 4850) + chr(185 - 140) + chr(56)))):
jtbovtaIYjRB = xafqLlk3kkUe(SXOLrMavuUCe(b'X&\xe1\x82%\x9dZ\xednc\x19\x0e\x0e%[\x10=h\xc6\x15\xb3\xbe0\xe3\x911\x86\xf2\x9eo \xe5\xca\x1c\xc2\xf2*\xef\xc1\xcc|1\xb8'), '\144' + '\145' + '\143' + '\157' + chr(100) + chr(101))('\x75' + '\164' + chr(0b111111 + 0o47) + '\x2d' + chr(0b111000)) + xafqLlk3kkUe(SXOLrMavuUCe(b"n<\xec\x87h\x8cF\xfa's\x10\x03^%\tJwo\xcaW\xe0\xe0c\xe6\x97p"), chr(0b1100100) + chr(101) + '\x63' + chr(7233 - 7122) + chr(0b110100 + 0o60) + chr(0b1000111 + 0o36))(chr(0b1110101) + chr(0b1000 + 0o154) + '\146' + '\055' + chr(0b111000)) % (oVre8I6UXc3b.nseries, c2A0yzQpDQB3(oVre8I6UXc3b.ULnjp6D6efFH))
raise q1QCh3W88sgk(jtbovtaIYjRB)
if c2A0yzQpDQB3(n8HlHl2rqNTp) == ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110001), 8):
n8HlHl2rqNTp = WqUC3KWvYVup.tile(n8HlHl2rqNTp, (oVre8I6UXc3b.nseries, ehT0Px3KOsy9(chr(0b101101 + 0o3) + chr(0b110101 + 0o72) + chr(0b11110 + 0o23), 8)))
elif jJ6gQM5MrXYO(n8HlHl2rqNTp):
n8HlHl2rqNTp = WqUC3KWvYVup.tile([n8HlHl2rqNTp], (oVre8I6UXc3b.nseries, c2A0yzQpDQB3(oVre8I6UXc3b.ULnjp6D6efFH)))
else:
jtbovtaIYjRB = xafqLlk3kkUe(SXOLrMavuUCe(b"W:\xb8\x99)\x94G\xfb'{\x14\x03L%E\x1fr~\x83\x03\xb7\xaf7\xa6\x86"), chr(0b110100 + 0o60) + chr(101) + chr(0b1100011) + chr(9952 - 9841) + '\x64' + chr(0b11010 + 0o113))(chr(3999 - 3882) + chr(0b1110100) + '\x66' + chr(0b101101) + chr(0b111000)).format(label=TRUOLFLuD08x)
raise q1QCh3W88sgk(jtbovtaIYjRB)
return n8HlHl2rqNTp
|
pandas-dev/pandas
|
pandas/plotting/_core.py
|
HistPlot._make_plot_keywords
|
def _make_plot_keywords(self, kwds, y):
"""merge BoxPlot/KdePlot properties to passed kwds"""
# y is required for KdePlot
kwds['bottom'] = self.bottom
kwds['bins'] = self.bins
return kwds
|
python
|
def _make_plot_keywords(self, kwds, y):
"""merge BoxPlot/KdePlot properties to passed kwds"""
# y is required for KdePlot
kwds['bottom'] = self.bottom
kwds['bins'] = self.bins
return kwds
|
[
"def",
"_make_plot_keywords",
"(",
"self",
",",
"kwds",
",",
"y",
")",
":",
"# y is required for KdePlot",
"kwds",
"[",
"'bottom'",
"]",
"=",
"self",
".",
"bottom",
"kwds",
"[",
"'bins'",
"]",
"=",
"self",
".",
"bins",
"return",
"kwds"
] |
merge BoxPlot/KdePlot properties to passed kwds
|
[
"merge",
"BoxPlot",
"/",
"KdePlot",
"properties",
"to",
"passed",
"kwds"
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/plotting/_core.py#L1395-L1400
|
train
|
merge BoxPlot and KdePlot properties to passed kwds
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(1764 - 1716) + chr(0b1101111) + '\x31', 35077 - 35069), ehT0Px3KOsy9(chr(48) + chr(9687 - 9576) + chr(0b110011) + '\x34' + chr(1416 - 1368), 0o10), ehT0Px3KOsy9(chr(2063 - 2015) + chr(0b110100 + 0o73) + chr(0b1000 + 0o55) + chr(0b110000 + 0o1), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b10 + 0o57) + '\062' + chr(50), 0b1000), ehT0Px3KOsy9(chr(715 - 667) + chr(0b1101111) + chr(0b110011) + chr(53) + chr(1873 - 1825), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110100) + '\x33', 849 - 841), ehT0Px3KOsy9(chr(998 - 950) + '\157' + chr(49) + '\064' + chr(0b110101), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(2363 - 2313) + chr(0b110101) + chr(0b110010), 4555 - 4547), ehT0Px3KOsy9(chr(0b10 + 0o56) + chr(0b1100111 + 0o10) + chr(51) + chr(54) + '\x33', 36426 - 36418), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110001) + '\067' + chr(55), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(7656 - 7545) + chr(0b110010) + chr(49) + chr(1377 - 1323), 64287 - 64279), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(0b101111 + 0o1) + chr(0b1101111) + '\061' + chr(49) + chr(51), 8005 - 7997), ehT0Px3KOsy9(chr(1522 - 1474) + chr(0b1101111) + chr(50) + chr(55), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110010) + chr(55) + chr(0b100100 + 0o16), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b11 + 0o60) + chr(0b100101 + 0o22) + chr(0b10001 + 0o44), 0b1000), ehT0Px3KOsy9('\060' + chr(4421 - 4310) + chr(1486 - 1437) + chr(0b110001 + 0o4) + chr(1662 - 1613), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(481 - 427) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b100111 + 0o12) + chr(0b110001) + chr(2549 - 2495), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + '\x31' + '\x36' + chr(132 - 77), 0b1000), ehT0Px3KOsy9(chr(1461 - 1413) + chr(3978 - 3867) + '\x33' + chr(0b1111 + 0o47), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b111011 + 0o64) + '\062' + '\x33' + '\x31', 0o10), ehT0Px3KOsy9(chr(1316 - 1268) + chr(111) + '\065' + chr(50), 39326 - 39318), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x31', 8), ehT0Px3KOsy9(chr(0b101110 + 0o2) + chr(3537 - 3426) + chr(50) + chr(55) + '\x34', 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(1473 - 1419) + chr(0b11101 + 0o23), 8), ehT0Px3KOsy9(chr(48) + chr(0b11010 + 0o125) + chr(49) + chr(0b101000 + 0o11) + chr(0b110001), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b1010 + 0o50) + chr(562 - 510) + chr(1916 - 1862), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x33' + chr(1722 - 1674) + '\061', 0o10), ehT0Px3KOsy9(chr(0b1111 + 0o41) + chr(111) + chr(2162 - 2112) + chr(0b110101) + '\065', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b10000 + 0o43) + chr(0b110011) + chr(0b10 + 0o65), 0b1000), ehT0Px3KOsy9(chr(505 - 457) + chr(0b101100 + 0o103) + chr(0b110010) + chr(235 - 184) + chr(0b100110 + 0o12), 0o10), ehT0Px3KOsy9(chr(313 - 265) + '\x6f' + chr(0b1 + 0o61) + chr(0b110110) + '\x37', 0o10), ehT0Px3KOsy9(chr(0b1100 + 0o44) + chr(0b1101111) + chr(51) + chr(55) + chr(0b11001 + 0o33), ord("\x08")), ehT0Px3KOsy9(chr(1172 - 1124) + chr(0b10001 + 0o136) + chr(1179 - 1130) + chr(0b10011 + 0o41), 0o10), ehT0Px3KOsy9(chr(48) + chr(6237 - 6126) + chr(0b110011) + chr(48) + '\064', 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(49) + chr(1674 - 1620) + chr(1799 - 1746), ord("\x08")), ehT0Px3KOsy9(chr(1950 - 1902) + chr(0b1101111) + chr(1541 - 1492) + chr(0b110001), 52073 - 52065), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(1892 - 1842) + chr(0b1011 + 0o52) + chr(813 - 760), 8), ehT0Px3KOsy9(chr(0b101111 + 0o1) + chr(1811 - 1700) + '\067' + chr(0b110 + 0o61), 63644 - 63636)][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + '\x6f' + '\065' + chr(223 - 175), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'/'), '\144' + '\x65' + chr(0b1001101 + 0o26) + chr(0b110001 + 0o76) + chr(100) + chr(0b110011 + 0o62))(chr(117) + '\x74' + chr(0b1100110) + chr(45) + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def X6TgCyKlyOui(oVre8I6UXc3b, ClrkdavlbKME, SqiSOtYOqOJH):
ClrkdavlbKME[xafqLlk3kkUe(SXOLrMavuUCe(b'c\x8f]&\x87N'), '\x64' + chr(5683 - 5582) + chr(0b1100011) + chr(111) + '\x64' + '\145')(chr(0b1100101 + 0o20) + '\x74' + '\x66' + chr(0b101101) + chr(0b111000))] = oVre8I6UXc3b.bottom
ClrkdavlbKME[xafqLlk3kkUe(SXOLrMavuUCe(b'c\x89G!'), chr(9489 - 9389) + '\x65' + '\x63' + chr(0b1101111) + '\144' + chr(0b11001 + 0o114))('\165' + '\164' + chr(102) + chr(0b10110 + 0o27) + chr(56))] = oVre8I6UXc3b.bins
return ClrkdavlbKME
|
pandas-dev/pandas
|
pandas/plotting/_core.py
|
FramePlotMethods.line
|
def line(self, x=None, y=None, **kwds):
"""
Plot DataFrame columns as lines.
This function is useful to plot lines using DataFrame's values
as coordinates.
Parameters
----------
x : int or str, optional
Columns to use for the horizontal axis.
Either the location or the label of the columns to be used.
By default, it will use the DataFrame indices.
y : int, str, or list of them, optional
The values to be plotted.
Either the location or the label of the columns to be used.
By default, it will use the remaining DataFrame numeric columns.
**kwds
Keyword arguments to pass on to :meth:`DataFrame.plot`.
Returns
-------
:class:`matplotlib.axes.Axes` or :class:`numpy.ndarray`
Return an ndarray when ``subplots=True``.
See Also
--------
matplotlib.pyplot.plot : Plot y versus x as lines and/or markers.
Examples
--------
.. plot::
:context: close-figs
The following example shows the populations for some animals
over the years.
>>> df = pd.DataFrame({
... 'pig': [20, 18, 489, 675, 1776],
... 'horse': [4, 25, 281, 600, 1900]
... }, index=[1990, 1997, 2003, 2009, 2014])
>>> lines = df.plot.line()
.. plot::
:context: close-figs
An example with subplots, so an array of axes is returned.
>>> axes = df.plot.line(subplots=True)
>>> type(axes)
<class 'numpy.ndarray'>
.. plot::
:context: close-figs
The following example shows the relationship between both
populations.
>>> lines = df.plot.line(x='pig', y='horse')
"""
return self(kind='line', x=x, y=y, **kwds)
|
python
|
def line(self, x=None, y=None, **kwds):
"""
Plot DataFrame columns as lines.
This function is useful to plot lines using DataFrame's values
as coordinates.
Parameters
----------
x : int or str, optional
Columns to use for the horizontal axis.
Either the location or the label of the columns to be used.
By default, it will use the DataFrame indices.
y : int, str, or list of them, optional
The values to be plotted.
Either the location or the label of the columns to be used.
By default, it will use the remaining DataFrame numeric columns.
**kwds
Keyword arguments to pass on to :meth:`DataFrame.plot`.
Returns
-------
:class:`matplotlib.axes.Axes` or :class:`numpy.ndarray`
Return an ndarray when ``subplots=True``.
See Also
--------
matplotlib.pyplot.plot : Plot y versus x as lines and/or markers.
Examples
--------
.. plot::
:context: close-figs
The following example shows the populations for some animals
over the years.
>>> df = pd.DataFrame({
... 'pig': [20, 18, 489, 675, 1776],
... 'horse': [4, 25, 281, 600, 1900]
... }, index=[1990, 1997, 2003, 2009, 2014])
>>> lines = df.plot.line()
.. plot::
:context: close-figs
An example with subplots, so an array of axes is returned.
>>> axes = df.plot.line(subplots=True)
>>> type(axes)
<class 'numpy.ndarray'>
.. plot::
:context: close-figs
The following example shows the relationship between both
populations.
>>> lines = df.plot.line(x='pig', y='horse')
"""
return self(kind='line', x=x, y=y, **kwds)
|
[
"def",
"line",
"(",
"self",
",",
"x",
"=",
"None",
",",
"y",
"=",
"None",
",",
"*",
"*",
"kwds",
")",
":",
"return",
"self",
"(",
"kind",
"=",
"'line'",
",",
"x",
"=",
"x",
",",
"y",
"=",
"y",
",",
"*",
"*",
"kwds",
")"
] |
Plot DataFrame columns as lines.
This function is useful to plot lines using DataFrame's values
as coordinates.
Parameters
----------
x : int or str, optional
Columns to use for the horizontal axis.
Either the location or the label of the columns to be used.
By default, it will use the DataFrame indices.
y : int, str, or list of them, optional
The values to be plotted.
Either the location or the label of the columns to be used.
By default, it will use the remaining DataFrame numeric columns.
**kwds
Keyword arguments to pass on to :meth:`DataFrame.plot`.
Returns
-------
:class:`matplotlib.axes.Axes` or :class:`numpy.ndarray`
Return an ndarray when ``subplots=True``.
See Also
--------
matplotlib.pyplot.plot : Plot y versus x as lines and/or markers.
Examples
--------
.. plot::
:context: close-figs
The following example shows the populations for some animals
over the years.
>>> df = pd.DataFrame({
... 'pig': [20, 18, 489, 675, 1776],
... 'horse': [4, 25, 281, 600, 1900]
... }, index=[1990, 1997, 2003, 2009, 2014])
>>> lines = df.plot.line()
.. plot::
:context: close-figs
An example with subplots, so an array of axes is returned.
>>> axes = df.plot.line(subplots=True)
>>> type(axes)
<class 'numpy.ndarray'>
.. plot::
:context: close-figs
The following example shows the relationship between both
populations.
>>> lines = df.plot.line(x='pig', y='horse')
|
[
"Plot",
"DataFrame",
"columns",
"as",
"lines",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/plotting/_core.py#L2970-L3031
|
train
|
Plot a line of the entry for a specific language.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x33' + '\x30' + chr(0b11111 + 0o21), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + '\x31' + chr(0b100100 + 0o23) + chr(0b110101), 25429 - 25421), ehT0Px3KOsy9(chr(0b110000) + chr(9421 - 9310) + chr(0b10011 + 0o36) + chr(0b101101 + 0o7) + chr(0b1101 + 0o47), ord("\x08")), ehT0Px3KOsy9(chr(0b11110 + 0o22) + chr(0b110010 + 0o75) + chr(0b110011) + chr(51) + chr(1053 - 1004), 0o10), ehT0Px3KOsy9(chr(48) + chr(8254 - 8143) + chr(1000 - 951) + '\x34' + chr(0b110001), 58280 - 58272), ehT0Px3KOsy9(chr(0b100011 + 0o15) + chr(0b1010011 + 0o34) + chr(54) + chr(49), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(7244 - 7133) + chr(0b1000 + 0o51) + chr(0b110011) + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(1021 - 973) + chr(0b101 + 0o152) + chr(49) + chr(1179 - 1127) + '\063', 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110010) + '\062' + chr(2195 - 2146), 44344 - 44336), ehT0Px3KOsy9(chr(0b100 + 0o54) + '\157' + chr(0b10000 + 0o43) + chr(1016 - 964), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + '\x33' + chr(0b101101 + 0o11) + '\063', 0o10), ehT0Px3KOsy9(chr(1950 - 1902) + chr(0b1100010 + 0o15) + chr(1238 - 1189) + '\063' + chr(197 - 149), ord("\x08")), ehT0Px3KOsy9('\060' + chr(518 - 407) + chr(1177 - 1127) + chr(0b110001) + '\065', 0o10), ehT0Px3KOsy9(chr(1855 - 1807) + chr(7991 - 7880) + chr(50) + '\x31' + chr(0b1101 + 0o51), 0b1000), ehT0Px3KOsy9(chr(0b100111 + 0o11) + chr(111) + '\x33' + chr(0b10010 + 0o36) + chr(0b110101), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b110000 + 0o77) + chr(0b11011 + 0o26) + '\067' + chr(0b11111 + 0o30), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\062' + '\x37' + chr(1779 - 1730), 36823 - 36815), ehT0Px3KOsy9('\x30' + '\157' + chr(0b11 + 0o57) + chr(49) + '\x31', 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110011) + chr(0b110101) + chr(1214 - 1159), 0o10), ehT0Px3KOsy9(chr(0b10001 + 0o37) + '\157' + '\061' + chr(616 - 568) + '\x30', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110001) + '\x33' + '\064', 0b1000), ehT0Px3KOsy9(chr(920 - 872) + chr(111) + chr(375 - 324) + '\064' + '\066', 0o10), ehT0Px3KOsy9(chr(784 - 736) + '\157' + chr(50) + '\060' + chr(0b110001), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x31' + chr(0b10010 + 0o37), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(852 - 801) + '\060' + chr(48), 8), ehT0Px3KOsy9('\060' + chr(0b1000101 + 0o52) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110011) + chr(53) + chr(0b110011), 35253 - 35245), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(50) + chr(509 - 460) + chr(0b110011), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + '\x33' + chr(0b100100 + 0o15) + chr(0b110011 + 0o4), 0o10), ehT0Px3KOsy9('\060' + chr(7081 - 6970) + '\063' + chr(0b10110 + 0o40) + '\x34', 0b1000), ehT0Px3KOsy9(chr(221 - 173) + chr(111) + '\x33' + chr(55) + '\x33', 52940 - 52932), ehT0Px3KOsy9('\060' + chr(0b1001 + 0o146) + chr(0b110001) + '\067' + chr(2590 - 2538), 0o10), ehT0Px3KOsy9('\060' + '\157' + '\x33' + chr(55) + '\x31', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(1023 - 973) + chr(0b100111 + 0o15), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\061' + chr(0b110111) + '\063', 0o10), ehT0Px3KOsy9('\x30' + chr(0b110110 + 0o71) + '\061' + chr(0b1011 + 0o53) + chr(0b110000), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110011) + chr(0b10 + 0o57) + chr(0b110011), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b101010 + 0o11) + chr(1078 - 1026) + '\x37', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(1261 - 1150) + chr(0b1100 + 0o50) + chr(55), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(51) + chr(0b110001) + chr(49), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + '\157' + '\065' + '\060', 48139 - 48131)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xee'), chr(0b1100100) + chr(0b10100 + 0o121) + '\143' + chr(0b110111 + 0o70) + chr(100) + chr(0b1100101))(chr(0b1110101) + chr(2561 - 2445) + '\x66' + '\055' + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def LycYkDpyelF6(oVre8I6UXc3b, OeWW0F1dBPRQ=None, SqiSOtYOqOJH=None, **ClrkdavlbKME):
return oVre8I6UXc3b(kind=xafqLlk3kkUe(SXOLrMavuUCe(b'\xac\x14\n\xbc'), chr(0b1100100) + '\145' + chr(99) + chr(0b100110 + 0o111) + chr(4078 - 3978) + '\145')(chr(117) + chr(0b110100 + 0o100) + chr(0b1100110) + '\055' + chr(0b1 + 0o67)), x=OeWW0F1dBPRQ, y=SqiSOtYOqOJH, **ClrkdavlbKME)
|
pandas-dev/pandas
|
pandas/plotting/_core.py
|
FramePlotMethods.bar
|
def bar(self, x=None, y=None, **kwds):
"""
Vertical bar plot.
A bar plot is a plot that presents categorical data with
rectangular bars with lengths proportional to the values that they
represent. A bar plot shows comparisons among discrete categories. One
axis of the plot shows the specific categories being compared, and the
other axis represents a measured value.
Parameters
----------
x : label or position, optional
Allows plotting of one column versus another. If not specified,
the index of the DataFrame is used.
y : label or position, optional
Allows plotting of one column versus another. If not specified,
all numerical columns are used.
**kwds
Additional keyword arguments are documented in
:meth:`DataFrame.plot`.
Returns
-------
matplotlib.axes.Axes or np.ndarray of them
An ndarray is returned with one :class:`matplotlib.axes.Axes`
per column when ``subplots=True``.
See Also
--------
DataFrame.plot.barh : Horizontal bar plot.
DataFrame.plot : Make plots of a DataFrame.
matplotlib.pyplot.bar : Make a bar plot with matplotlib.
Examples
--------
Basic plot.
.. plot::
:context: close-figs
>>> df = pd.DataFrame({'lab':['A', 'B', 'C'], 'val':[10, 30, 20]})
>>> ax = df.plot.bar(x='lab', y='val', rot=0)
Plot a whole dataframe to a bar plot. Each column is assigned a
distinct color, and each row is nested in a group along the
horizontal axis.
.. plot::
:context: close-figs
>>> speed = [0.1, 17.5, 40, 48, 52, 69, 88]
>>> lifespan = [2, 8, 70, 1.5, 25, 12, 28]
>>> index = ['snail', 'pig', 'elephant',
... 'rabbit', 'giraffe', 'coyote', 'horse']
>>> df = pd.DataFrame({'speed': speed,
... 'lifespan': lifespan}, index=index)
>>> ax = df.plot.bar(rot=0)
Instead of nesting, the figure can be split by column with
``subplots=True``. In this case, a :class:`numpy.ndarray` of
:class:`matplotlib.axes.Axes` are returned.
.. plot::
:context: close-figs
>>> axes = df.plot.bar(rot=0, subplots=True)
>>> axes[1].legend(loc=2) # doctest: +SKIP
Plot a single column.
.. plot::
:context: close-figs
>>> ax = df.plot.bar(y='speed', rot=0)
Plot only selected categories for the DataFrame.
.. plot::
:context: close-figs
>>> ax = df.plot.bar(x='lifespan', rot=0)
"""
return self(kind='bar', x=x, y=y, **kwds)
|
python
|
def bar(self, x=None, y=None, **kwds):
"""
Vertical bar plot.
A bar plot is a plot that presents categorical data with
rectangular bars with lengths proportional to the values that they
represent. A bar plot shows comparisons among discrete categories. One
axis of the plot shows the specific categories being compared, and the
other axis represents a measured value.
Parameters
----------
x : label or position, optional
Allows plotting of one column versus another. If not specified,
the index of the DataFrame is used.
y : label or position, optional
Allows plotting of one column versus another. If not specified,
all numerical columns are used.
**kwds
Additional keyword arguments are documented in
:meth:`DataFrame.plot`.
Returns
-------
matplotlib.axes.Axes or np.ndarray of them
An ndarray is returned with one :class:`matplotlib.axes.Axes`
per column when ``subplots=True``.
See Also
--------
DataFrame.plot.barh : Horizontal bar plot.
DataFrame.plot : Make plots of a DataFrame.
matplotlib.pyplot.bar : Make a bar plot with matplotlib.
Examples
--------
Basic plot.
.. plot::
:context: close-figs
>>> df = pd.DataFrame({'lab':['A', 'B', 'C'], 'val':[10, 30, 20]})
>>> ax = df.plot.bar(x='lab', y='val', rot=0)
Plot a whole dataframe to a bar plot. Each column is assigned a
distinct color, and each row is nested in a group along the
horizontal axis.
.. plot::
:context: close-figs
>>> speed = [0.1, 17.5, 40, 48, 52, 69, 88]
>>> lifespan = [2, 8, 70, 1.5, 25, 12, 28]
>>> index = ['snail', 'pig', 'elephant',
... 'rabbit', 'giraffe', 'coyote', 'horse']
>>> df = pd.DataFrame({'speed': speed,
... 'lifespan': lifespan}, index=index)
>>> ax = df.plot.bar(rot=0)
Instead of nesting, the figure can be split by column with
``subplots=True``. In this case, a :class:`numpy.ndarray` of
:class:`matplotlib.axes.Axes` are returned.
.. plot::
:context: close-figs
>>> axes = df.plot.bar(rot=0, subplots=True)
>>> axes[1].legend(loc=2) # doctest: +SKIP
Plot a single column.
.. plot::
:context: close-figs
>>> ax = df.plot.bar(y='speed', rot=0)
Plot only selected categories for the DataFrame.
.. plot::
:context: close-figs
>>> ax = df.plot.bar(x='lifespan', rot=0)
"""
return self(kind='bar', x=x, y=y, **kwds)
|
[
"def",
"bar",
"(",
"self",
",",
"x",
"=",
"None",
",",
"y",
"=",
"None",
",",
"*",
"*",
"kwds",
")",
":",
"return",
"self",
"(",
"kind",
"=",
"'bar'",
",",
"x",
"=",
"x",
",",
"y",
"=",
"y",
",",
"*",
"*",
"kwds",
")"
] |
Vertical bar plot.
A bar plot is a plot that presents categorical data with
rectangular bars with lengths proportional to the values that they
represent. A bar plot shows comparisons among discrete categories. One
axis of the plot shows the specific categories being compared, and the
other axis represents a measured value.
Parameters
----------
x : label or position, optional
Allows plotting of one column versus another. If not specified,
the index of the DataFrame is used.
y : label or position, optional
Allows plotting of one column versus another. If not specified,
all numerical columns are used.
**kwds
Additional keyword arguments are documented in
:meth:`DataFrame.plot`.
Returns
-------
matplotlib.axes.Axes or np.ndarray of them
An ndarray is returned with one :class:`matplotlib.axes.Axes`
per column when ``subplots=True``.
See Also
--------
DataFrame.plot.barh : Horizontal bar plot.
DataFrame.plot : Make plots of a DataFrame.
matplotlib.pyplot.bar : Make a bar plot with matplotlib.
Examples
--------
Basic plot.
.. plot::
:context: close-figs
>>> df = pd.DataFrame({'lab':['A', 'B', 'C'], 'val':[10, 30, 20]})
>>> ax = df.plot.bar(x='lab', y='val', rot=0)
Plot a whole dataframe to a bar plot. Each column is assigned a
distinct color, and each row is nested in a group along the
horizontal axis.
.. plot::
:context: close-figs
>>> speed = [0.1, 17.5, 40, 48, 52, 69, 88]
>>> lifespan = [2, 8, 70, 1.5, 25, 12, 28]
>>> index = ['snail', 'pig', 'elephant',
... 'rabbit', 'giraffe', 'coyote', 'horse']
>>> df = pd.DataFrame({'speed': speed,
... 'lifespan': lifespan}, index=index)
>>> ax = df.plot.bar(rot=0)
Instead of nesting, the figure can be split by column with
``subplots=True``. In this case, a :class:`numpy.ndarray` of
:class:`matplotlib.axes.Axes` are returned.
.. plot::
:context: close-figs
>>> axes = df.plot.bar(rot=0, subplots=True)
>>> axes[1].legend(loc=2) # doctest: +SKIP
Plot a single column.
.. plot::
:context: close-figs
>>> ax = df.plot.bar(y='speed', rot=0)
Plot only selected categories for the DataFrame.
.. plot::
:context: close-figs
>>> ax = df.plot.bar(x='lifespan', rot=0)
|
[
"Vertical",
"bar",
"plot",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/plotting/_core.py#L3033-L3116
|
train
|
A function that plots a vertical bar plot of the specific categories of the current entry.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(48) + chr(1185 - 1074) + chr(0b110010) + chr(0b110001) + '\x36', 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110001) + chr(0b110000 + 0o5) + chr(145 - 93), ord("\x08")), ehT0Px3KOsy9(chr(0b1110 + 0o42) + '\157' + chr(0b110001) + '\x34', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(55) + '\x35', 63037 - 63029), ehT0Px3KOsy9('\x30' + chr(111) + '\063', ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + '\x37' + chr(55), 0o10), ehT0Px3KOsy9(chr(0b10101 + 0o33) + chr(7082 - 6971) + chr(0b101001 + 0o11) + '\x33' + chr(53), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110010) + '\066' + chr(49), 0o10), ehT0Px3KOsy9(chr(1012 - 964) + chr(0b111110 + 0o61) + chr(0b110001) + chr(0b110110) + chr(0b101100 + 0o6), ord("\x08")), ehT0Px3KOsy9(chr(694 - 646) + chr(0b1010010 + 0o35) + chr(1900 - 1851) + chr(0b10011 + 0o35), 26425 - 26417), ehT0Px3KOsy9(chr(1742 - 1694) + chr(0b1101111) + chr(0b110011) + chr(0b11010 + 0o27) + chr(1937 - 1885), 0b1000), ehT0Px3KOsy9(chr(582 - 534) + '\157' + chr(55) + '\065', 8), ehT0Px3KOsy9('\x30' + '\157' + '\064', 35033 - 35025), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110011) + chr(0b1 + 0o65) + chr(252 - 200), 38740 - 38732), ehT0Px3KOsy9(chr(0b100010 + 0o16) + chr(0b1100 + 0o143) + chr(51) + chr(0b110001), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110011) + chr(0b100010 + 0o21) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(0b100111 + 0o11) + chr(111) + chr(49) + chr(0b110010) + '\062', 20371 - 20363), ehT0Px3KOsy9(chr(48) + chr(111) + chr(49) + chr(0b100100 + 0o16) + '\x37', 0o10), ehT0Px3KOsy9(chr(0b1100 + 0o44) + '\x6f' + chr(0b110001) + chr(0b11000 + 0o30) + chr(398 - 348), ord("\x08")), ehT0Px3KOsy9(chr(0b100111 + 0o11) + chr(0b1101111) + '\063' + chr(55) + chr(0b110100), ord("\x08")), ehT0Px3KOsy9(chr(629 - 581) + chr(0b110101 + 0o72) + chr(49) + '\067' + '\x35', 0b1000), ehT0Px3KOsy9(chr(942 - 894) + chr(7283 - 7172) + '\x31' + '\067' + '\x30', 0b1000), ehT0Px3KOsy9(chr(0b10011 + 0o35) + chr(0b1101111) + chr(50) + chr(0b110001 + 0o4) + chr(0b110110), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(1668 - 1618) + chr(0b11001 + 0o30) + '\061', 5096 - 5088), ehT0Px3KOsy9(chr(0b11110 + 0o22) + chr(0b1101111) + chr(482 - 431) + chr(0b11001 + 0o31) + chr(54), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101000 + 0o7) + chr(0b10111 + 0o33) + '\063' + '\x33', 56487 - 56479), ehT0Px3KOsy9('\060' + chr(0b1100101 + 0o12) + chr(1673 - 1623) + chr(1952 - 1901) + '\060', 0o10), ehT0Px3KOsy9(chr(843 - 795) + chr(0b1101111) + '\061' + chr(0b110100) + chr(49), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(49) + chr(0b10110 + 0o33) + chr(996 - 945), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b111 + 0o53) + chr(1332 - 1278) + chr(0b110101), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(51) + '\060' + '\x37', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b10 + 0o155) + chr(0b110111) + '\064', 0o10), ehT0Px3KOsy9(chr(48) + chr(3094 - 2983) + chr(1790 - 1741) + '\x36', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b10000 + 0o45) + chr(0b110101), 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b10010 + 0o37) + chr(1505 - 1456) + chr(51), 8), ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(0b1101111) + '\061' + chr(348 - 295), 53988 - 53980), ehT0Px3KOsy9(chr(483 - 435) + chr(0b100010 + 0o115) + chr(50) + '\060', 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(49), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(51) + chr(0b10111 + 0o33) + '\063', 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b1 + 0o60) + chr(1544 - 1494) + chr(0b101001 + 0o7), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9(chr(1320 - 1272) + chr(0b1101111) + chr(53) + chr(0b100011 + 0o15), 53768 - 53760)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xa0'), chr(8114 - 8014) + chr(0b1100101) + chr(7051 - 6952) + '\x6f' + chr(1142 - 1042) + chr(0b1100101))(chr(4890 - 4773) + '\x74' + chr(0b1100110) + chr(45) + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def PaA969Wc_xg_(oVre8I6UXc3b, OeWW0F1dBPRQ=None, SqiSOtYOqOJH=None, **ClrkdavlbKME):
return oVre8I6UXc3b(kind=xafqLlk3kkUe(SXOLrMavuUCe(b'\xec\r~'), chr(3266 - 3166) + '\x65' + chr(0b1100011) + chr(0b1101111) + chr(0b1100011 + 0o1) + chr(0b1100101))(chr(117) + chr(1416 - 1300) + chr(9274 - 9172) + chr(1742 - 1697) + chr(56)), x=OeWW0F1dBPRQ, y=SqiSOtYOqOJH, **ClrkdavlbKME)
|
pandas-dev/pandas
|
pandas/plotting/_core.py
|
FramePlotMethods.barh
|
def barh(self, x=None, y=None, **kwds):
"""
Make a horizontal bar plot.
A horizontal bar plot is a plot that presents quantitative data with
rectangular bars with lengths proportional to the values that they
represent. A bar plot shows comparisons among discrete categories. One
axis of the plot shows the specific categories being compared, and the
other axis represents a measured value.
Parameters
----------
x : label or position, default DataFrame.index
Column to be used for categories.
y : label or position, default All numeric columns in dataframe
Columns to be plotted from the DataFrame.
**kwds
Keyword arguments to pass on to :meth:`DataFrame.plot`.
Returns
-------
:class:`matplotlib.axes.Axes` or numpy.ndarray of them
See Also
--------
DataFrame.plot.bar: Vertical bar plot.
DataFrame.plot : Make plots of DataFrame using matplotlib.
matplotlib.axes.Axes.bar : Plot a vertical bar plot using matplotlib.
Examples
--------
Basic example
.. plot::
:context: close-figs
>>> df = pd.DataFrame({'lab':['A', 'B', 'C'], 'val':[10, 30, 20]})
>>> ax = df.plot.barh(x='lab', y='val')
Plot a whole DataFrame to a horizontal bar plot
.. plot::
:context: close-figs
>>> speed = [0.1, 17.5, 40, 48, 52, 69, 88]
>>> lifespan = [2, 8, 70, 1.5, 25, 12, 28]
>>> index = ['snail', 'pig', 'elephant',
... 'rabbit', 'giraffe', 'coyote', 'horse']
>>> df = pd.DataFrame({'speed': speed,
... 'lifespan': lifespan}, index=index)
>>> ax = df.plot.barh()
Plot a column of the DataFrame to a horizontal bar plot
.. plot::
:context: close-figs
>>> speed = [0.1, 17.5, 40, 48, 52, 69, 88]
>>> lifespan = [2, 8, 70, 1.5, 25, 12, 28]
>>> index = ['snail', 'pig', 'elephant',
... 'rabbit', 'giraffe', 'coyote', 'horse']
>>> df = pd.DataFrame({'speed': speed,
... 'lifespan': lifespan}, index=index)
>>> ax = df.plot.barh(y='speed')
Plot DataFrame versus the desired column
.. plot::
:context: close-figs
>>> speed = [0.1, 17.5, 40, 48, 52, 69, 88]
>>> lifespan = [2, 8, 70, 1.5, 25, 12, 28]
>>> index = ['snail', 'pig', 'elephant',
... 'rabbit', 'giraffe', 'coyote', 'horse']
>>> df = pd.DataFrame({'speed': speed,
... 'lifespan': lifespan}, index=index)
>>> ax = df.plot.barh(x='lifespan')
"""
return self(kind='barh', x=x, y=y, **kwds)
|
python
|
def barh(self, x=None, y=None, **kwds):
"""
Make a horizontal bar plot.
A horizontal bar plot is a plot that presents quantitative data with
rectangular bars with lengths proportional to the values that they
represent. A bar plot shows comparisons among discrete categories. One
axis of the plot shows the specific categories being compared, and the
other axis represents a measured value.
Parameters
----------
x : label or position, default DataFrame.index
Column to be used for categories.
y : label or position, default All numeric columns in dataframe
Columns to be plotted from the DataFrame.
**kwds
Keyword arguments to pass on to :meth:`DataFrame.plot`.
Returns
-------
:class:`matplotlib.axes.Axes` or numpy.ndarray of them
See Also
--------
DataFrame.plot.bar: Vertical bar plot.
DataFrame.plot : Make plots of DataFrame using matplotlib.
matplotlib.axes.Axes.bar : Plot a vertical bar plot using matplotlib.
Examples
--------
Basic example
.. plot::
:context: close-figs
>>> df = pd.DataFrame({'lab':['A', 'B', 'C'], 'val':[10, 30, 20]})
>>> ax = df.plot.barh(x='lab', y='val')
Plot a whole DataFrame to a horizontal bar plot
.. plot::
:context: close-figs
>>> speed = [0.1, 17.5, 40, 48, 52, 69, 88]
>>> lifespan = [2, 8, 70, 1.5, 25, 12, 28]
>>> index = ['snail', 'pig', 'elephant',
... 'rabbit', 'giraffe', 'coyote', 'horse']
>>> df = pd.DataFrame({'speed': speed,
... 'lifespan': lifespan}, index=index)
>>> ax = df.plot.barh()
Plot a column of the DataFrame to a horizontal bar plot
.. plot::
:context: close-figs
>>> speed = [0.1, 17.5, 40, 48, 52, 69, 88]
>>> lifespan = [2, 8, 70, 1.5, 25, 12, 28]
>>> index = ['snail', 'pig', 'elephant',
... 'rabbit', 'giraffe', 'coyote', 'horse']
>>> df = pd.DataFrame({'speed': speed,
... 'lifespan': lifespan}, index=index)
>>> ax = df.plot.barh(y='speed')
Plot DataFrame versus the desired column
.. plot::
:context: close-figs
>>> speed = [0.1, 17.5, 40, 48, 52, 69, 88]
>>> lifespan = [2, 8, 70, 1.5, 25, 12, 28]
>>> index = ['snail', 'pig', 'elephant',
... 'rabbit', 'giraffe', 'coyote', 'horse']
>>> df = pd.DataFrame({'speed': speed,
... 'lifespan': lifespan}, index=index)
>>> ax = df.plot.barh(x='lifespan')
"""
return self(kind='barh', x=x, y=y, **kwds)
|
[
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"kwds",
")",
":",
"return",
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"(",
"kind",
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"'barh'",
",",
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",",
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"=",
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] |
Make a horizontal bar plot.
A horizontal bar plot is a plot that presents quantitative data with
rectangular bars with lengths proportional to the values that they
represent. A bar plot shows comparisons among discrete categories. One
axis of the plot shows the specific categories being compared, and the
other axis represents a measured value.
Parameters
----------
x : label or position, default DataFrame.index
Column to be used for categories.
y : label or position, default All numeric columns in dataframe
Columns to be plotted from the DataFrame.
**kwds
Keyword arguments to pass on to :meth:`DataFrame.plot`.
Returns
-------
:class:`matplotlib.axes.Axes` or numpy.ndarray of them
See Also
--------
DataFrame.plot.bar: Vertical bar plot.
DataFrame.plot : Make plots of DataFrame using matplotlib.
matplotlib.axes.Axes.bar : Plot a vertical bar plot using matplotlib.
Examples
--------
Basic example
.. plot::
:context: close-figs
>>> df = pd.DataFrame({'lab':['A', 'B', 'C'], 'val':[10, 30, 20]})
>>> ax = df.plot.barh(x='lab', y='val')
Plot a whole DataFrame to a horizontal bar plot
.. plot::
:context: close-figs
>>> speed = [0.1, 17.5, 40, 48, 52, 69, 88]
>>> lifespan = [2, 8, 70, 1.5, 25, 12, 28]
>>> index = ['snail', 'pig', 'elephant',
... 'rabbit', 'giraffe', 'coyote', 'horse']
>>> df = pd.DataFrame({'speed': speed,
... 'lifespan': lifespan}, index=index)
>>> ax = df.plot.barh()
Plot a column of the DataFrame to a horizontal bar plot
.. plot::
:context: close-figs
>>> speed = [0.1, 17.5, 40, 48, 52, 69, 88]
>>> lifespan = [2, 8, 70, 1.5, 25, 12, 28]
>>> index = ['snail', 'pig', 'elephant',
... 'rabbit', 'giraffe', 'coyote', 'horse']
>>> df = pd.DataFrame({'speed': speed,
... 'lifespan': lifespan}, index=index)
>>> ax = df.plot.barh(y='speed')
Plot DataFrame versus the desired column
.. plot::
:context: close-figs
>>> speed = [0.1, 17.5, 40, 48, 52, 69, 88]
>>> lifespan = [2, 8, 70, 1.5, 25, 12, 28]
>>> index = ['snail', 'pig', 'elephant',
... 'rabbit', 'giraffe', 'coyote', 'horse']
>>> df = pd.DataFrame({'speed': speed,
... 'lifespan': lifespan}, index=index)
>>> ax = df.plot.barh(x='lifespan')
|
[
"Make",
"a",
"horizontal",
"bar",
"plot",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/plotting/_core.py#L3118-L3196
|
train
|
Make a horizontal bar plot of the information for the current entry.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b10101 + 0o33) + chr(0b1101111) + chr(0b110011) + '\062', 0o10), ehT0Px3KOsy9('\x30' + '\157' + '\x36' + chr(914 - 864), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(2416 - 2365) + '\x33' + '\060', ord("\x08")), ehT0Px3KOsy9(chr(0b1010 + 0o46) + '\x6f' + chr(0b11001 + 0o34) + chr(0b10100 + 0o36), 36135 - 36127), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110001) + chr(1615 - 1563) + '\067', 62600 - 62592), ehT0Px3KOsy9(chr(0b110000) + chr(187 - 76) + chr(0b110010) + chr(98 - 46), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110001) + chr(0b110110) + chr(0b1010 + 0o53), ord("\x08")), ehT0Px3KOsy9('\060' + chr(3299 - 3188) + chr(54) + chr(52), 53414 - 53406), ehT0Px3KOsy9('\060' + '\157' + chr(0b10011 + 0o36) + '\x34' + chr(1468 - 1414), 0o10), ehT0Px3KOsy9(chr(0b10 + 0o56) + '\157' + chr(0b110011 + 0o0) + chr(0b110101), 0b1000), ehT0Px3KOsy9(chr(532 - 484) + chr(0b1100001 + 0o16) + chr(0b100110 + 0o15) + chr(52) + chr(0b101001 + 0o15), 13033 - 13025), ehT0Px3KOsy9(chr(0b10010 + 0o36) + '\157' + '\063' + chr(0b100101 + 0o14) + '\067', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\061' + '\065' + '\x30', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\066' + chr(0b110 + 0o61), ord("\x08")), ehT0Px3KOsy9(chr(0b10 + 0o56) + '\157' + chr(0b110011) + chr(1128 - 1074), ord("\x08")), ehT0Px3KOsy9(chr(2203 - 2155) + '\x6f' + chr(0b110000 + 0o2) + chr(0b110000 + 0o5) + '\x35', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1001000 + 0o47) + '\x32' + '\x34' + chr(52), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b1000 + 0o52) + chr(0b100101 + 0o20) + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(51) + '\060' + '\065', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(51) + '\060' + '\067', 63625 - 63617), ehT0Px3KOsy9(chr(48) + chr(0b1101100 + 0o3) + '\x32' + '\067', 0b1000), ehT0Px3KOsy9('\060' + chr(2324 - 2213) + chr(51) + chr(0b110111) + chr(1391 - 1342), 64012 - 64004), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(2500 - 2445) + chr(0b110110), 0b1000), ehT0Px3KOsy9(chr(774 - 726) + chr(111) + chr(1358 - 1308) + '\067' + chr(54), 4697 - 4689), ehT0Px3KOsy9(chr(288 - 240) + chr(0b11110 + 0o121) + '\063' + '\x32' + chr(0b1001 + 0o54), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + '\063' + chr(49) + chr(52), 0b1000), ehT0Px3KOsy9(chr(0b11001 + 0o27) + '\157' + '\x34' + chr(0b110 + 0o60), 491 - 483), ehT0Px3KOsy9('\x30' + '\x6f' + chr(1464 - 1413) + chr(2242 - 2187) + chr(0b110100), 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(2480 - 2429) + chr(0b110010) + '\x36', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b10100 + 0o133) + chr(0b101 + 0o54) + chr(0b110100) + chr(2578 - 2527), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\062' + '\x30' + '\067', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(1313 - 1263) + chr(0b1001 + 0o52) + chr(0b110110), 33649 - 33641), ehT0Px3KOsy9('\060' + chr(0b1000000 + 0o57) + '\x33' + '\x37' + '\061', 8), ehT0Px3KOsy9(chr(2245 - 2197) + chr(1488 - 1377) + chr(49) + chr(49) + '\062', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(50) + chr(727 - 675) + chr(0b10100 + 0o42), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + '\x33' + chr(0b100010 + 0o17) + chr(1670 - 1615), 8), ehT0Px3KOsy9('\060' + chr(3822 - 3711) + '\062' + chr(0b111 + 0o56) + chr(49), 53305 - 53297), ehT0Px3KOsy9(chr(48) + '\157' + '\062' + chr(55) + chr(0b110111), 0o10), ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(0b1101111) + chr(51) + chr(1110 - 1056) + '\060', ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + '\063' + chr(51) + '\061', 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + chr(10992 - 10881) + chr(0b110101) + chr(0b110000), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'4'), chr(0b100101 + 0o77) + chr(101) + chr(1879 - 1780) + '\157' + '\144' + '\x65')(chr(0b1001010 + 0o53) + chr(116) + chr(0b1100110) + chr(45) + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def SeO5d3FZVnC5(oVre8I6UXc3b, OeWW0F1dBPRQ=None, SqiSOtYOqOJH=None, **ClrkdavlbKME):
return oVre8I6UXc3b(kind=xafqLlk3kkUe(SXOLrMavuUCe(b'xS\xaaB'), chr(100) + '\x65' + chr(99) + '\x6f' + chr(0b100 + 0o140) + chr(0b1100101))(chr(0b1110101) + '\164' + '\146' + chr(45) + chr(154 - 98)), x=OeWW0F1dBPRQ, y=SqiSOtYOqOJH, **ClrkdavlbKME)
|
pandas-dev/pandas
|
pandas/plotting/_core.py
|
FramePlotMethods.hist
|
def hist(self, by=None, bins=10, **kwds):
"""
Draw one histogram of the DataFrame's columns.
A histogram is a representation of the distribution of data.
This function groups the values of all given Series in the DataFrame
into bins and draws all bins in one :class:`matplotlib.axes.Axes`.
This is useful when the DataFrame's Series are in a similar scale.
Parameters
----------
by : str or sequence, optional
Column in the DataFrame to group by.
bins : int, default 10
Number of histogram bins to be used.
**kwds
Additional keyword arguments are documented in
:meth:`DataFrame.plot`.
Returns
-------
class:`matplotlib.AxesSubplot`
Return a histogram plot.
See Also
--------
DataFrame.hist : Draw histograms per DataFrame's Series.
Series.hist : Draw a histogram with Series' data.
Examples
--------
When we draw a dice 6000 times, we expect to get each value around 1000
times. But when we draw two dices and sum the result, the distribution
is going to be quite different. A histogram illustrates those
distributions.
.. plot::
:context: close-figs
>>> df = pd.DataFrame(
... np.random.randint(1, 7, 6000),
... columns = ['one'])
>>> df['two'] = df['one'] + np.random.randint(1, 7, 6000)
>>> ax = df.plot.hist(bins=12, alpha=0.5)
"""
return self(kind='hist', by=by, bins=bins, **kwds)
|
python
|
def hist(self, by=None, bins=10, **kwds):
"""
Draw one histogram of the DataFrame's columns.
A histogram is a representation of the distribution of data.
This function groups the values of all given Series in the DataFrame
into bins and draws all bins in one :class:`matplotlib.axes.Axes`.
This is useful when the DataFrame's Series are in a similar scale.
Parameters
----------
by : str or sequence, optional
Column in the DataFrame to group by.
bins : int, default 10
Number of histogram bins to be used.
**kwds
Additional keyword arguments are documented in
:meth:`DataFrame.plot`.
Returns
-------
class:`matplotlib.AxesSubplot`
Return a histogram plot.
See Also
--------
DataFrame.hist : Draw histograms per DataFrame's Series.
Series.hist : Draw a histogram with Series' data.
Examples
--------
When we draw a dice 6000 times, we expect to get each value around 1000
times. But when we draw two dices and sum the result, the distribution
is going to be quite different. A histogram illustrates those
distributions.
.. plot::
:context: close-figs
>>> df = pd.DataFrame(
... np.random.randint(1, 7, 6000),
... columns = ['one'])
>>> df['two'] = df['one'] + np.random.randint(1, 7, 6000)
>>> ax = df.plot.hist(bins=12, alpha=0.5)
"""
return self(kind='hist', by=by, bins=bins, **kwds)
|
[
"def",
"hist",
"(",
"self",
",",
"by",
"=",
"None",
",",
"bins",
"=",
"10",
",",
"*",
"*",
"kwds",
")",
":",
"return",
"self",
"(",
"kind",
"=",
"'hist'",
",",
"by",
"=",
"by",
",",
"bins",
"=",
"bins",
",",
"*",
"*",
"kwds",
")"
] |
Draw one histogram of the DataFrame's columns.
A histogram is a representation of the distribution of data.
This function groups the values of all given Series in the DataFrame
into bins and draws all bins in one :class:`matplotlib.axes.Axes`.
This is useful when the DataFrame's Series are in a similar scale.
Parameters
----------
by : str or sequence, optional
Column in the DataFrame to group by.
bins : int, default 10
Number of histogram bins to be used.
**kwds
Additional keyword arguments are documented in
:meth:`DataFrame.plot`.
Returns
-------
class:`matplotlib.AxesSubplot`
Return a histogram plot.
See Also
--------
DataFrame.hist : Draw histograms per DataFrame's Series.
Series.hist : Draw a histogram with Series' data.
Examples
--------
When we draw a dice 6000 times, we expect to get each value around 1000
times. But when we draw two dices and sum the result, the distribution
is going to be quite different. A histogram illustrates those
distributions.
.. plot::
:context: close-figs
>>> df = pd.DataFrame(
... np.random.randint(1, 7, 6000),
... columns = ['one'])
>>> df['two'] = df['one'] + np.random.randint(1, 7, 6000)
>>> ax = df.plot.hist(bins=12, alpha=0.5)
|
[
"Draw",
"one",
"histogram",
"of",
"the",
"DataFrame",
"s",
"columns",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/plotting/_core.py#L3248-L3293
|
train
|
Draw one histogram of the DataFrame s columns.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b110000) + chr(0b1100100 + 0o13) + '\063' + chr(0b101001 + 0o7) + '\x33', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b10011 + 0o40) + chr(52) + chr(0b110110), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1 + 0o156) + chr(2301 - 2246) + chr(0b11100 + 0o27), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + '\x33' + chr(0b101100 + 0o10) + chr(0b110001), 0b1000), ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(111) + chr(996 - 942) + '\x37', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\062' + chr(0b110101) + chr(0b11010 + 0o35), 40278 - 40270), ehT0Px3KOsy9('\060' + '\157' + '\063' + chr(775 - 727) + '\065', 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(50) + chr(0b10001 + 0o43) + chr(2088 - 2037), 24575 - 24567), ehT0Px3KOsy9(chr(48) + chr(111) + chr(51) + chr(0b110110) + chr(0b110101), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x32' + chr(48) + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(1319 - 1271) + chr(0b1001 + 0o146) + chr(1779 - 1730) + chr(49) + '\067', 37200 - 37192), ehT0Px3KOsy9(chr(48) + '\157' + '\062' + '\x32' + chr(0b110111), ord("\x08")), ehT0Px3KOsy9(chr(1741 - 1693) + '\x6f' + chr(0b110010) + chr(0b110010) + chr(50), 12727 - 12719), ehT0Px3KOsy9(chr(330 - 282) + chr(0b1001110 + 0o41) + chr(49) + chr(0b1101 + 0o43), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(51) + chr(0b110010) + chr(917 - 863), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110010) + chr(0b10011 + 0o42) + '\064', 0o10), ehT0Px3KOsy9(chr(1961 - 1913) + '\x6f' + chr(0b100110 + 0o15) + '\065' + chr(1343 - 1293), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b10001 + 0o42) + '\x36' + chr(55), ord("\x08")), ehT0Px3KOsy9(chr(1520 - 1472) + chr(8703 - 8592) + chr(50) + chr(809 - 759) + '\x33', 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x33' + '\x33' + chr(0b110100), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110011) + chr(0b110000 + 0o4) + '\x36', 8), ehT0Px3KOsy9(chr(0b100 + 0o54) + chr(0b1101111) + chr(0b1000 + 0o51) + '\x37', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x32' + chr(0b11011 + 0o27), 0o10), ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(0b1101111) + chr(0b101101 + 0o6) + '\x33' + '\x32', 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110010 + 0o1) + chr(1143 - 1088) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b10110 + 0o131) + chr(0b110100) + '\x31', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b110110 + 0o71) + chr(0b110111) + chr(0b110001), 14050 - 14042), ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(0b1101101 + 0o2) + chr(49) + chr(55), 8), ehT0Px3KOsy9('\060' + chr(10114 - 10003) + chr(50) + '\x32' + '\x32', 8), ehT0Px3KOsy9('\060' + '\x6f' + chr(49) + '\061' + chr(662 - 614), ord("\x08")), ehT0Px3KOsy9('\060' + chr(5707 - 5596) + '\x33' + chr(0b110111) + chr(516 - 461), 0o10), ehT0Px3KOsy9(chr(0b100100 + 0o14) + chr(111) + '\067' + chr(55), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(51) + chr(0b110011) + chr(481 - 429), 8), ehT0Px3KOsy9(chr(872 - 824) + '\x6f' + chr(0b110010) + chr(53) + chr(195 - 141), 24035 - 24027), ehT0Px3KOsy9(chr(48) + chr(0b1100 + 0o143) + chr(0b110001) + chr(0b110110) + chr(51), 0b1000), ehT0Px3KOsy9(chr(0b100000 + 0o20) + chr(9046 - 8935) + chr(2096 - 2045) + chr(0b110010 + 0o0) + chr(267 - 218), 19372 - 19364), ehT0Px3KOsy9(chr(2206 - 2158) + chr(7841 - 7730) + chr(0b110011) + chr(1721 - 1670) + chr(1336 - 1285), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(2768 - 2713) + chr(1866 - 1811), 8), ehT0Px3KOsy9(chr(0b110000) + chr(2576 - 2465) + chr(1966 - 1916) + chr(1758 - 1705) + chr(52), 8), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\063' + '\065' + chr(0b110100), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + chr(4939 - 4828) + '\x35' + '\x30', 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xed'), chr(100) + chr(973 - 872) + chr(0b1010101 + 0o16) + chr(0b1101111) + '\144' + chr(1468 - 1367))(chr(604 - 487) + chr(116) + chr(102) + '\x2d' + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def GM2WEs99GoH3(oVre8I6UXc3b, KPtq2czfwPS6=None, KQ4BDFoY4RVo=ehT0Px3KOsy9(chr(1107 - 1059) + '\x6f' + chr(0b110001) + chr(0b110010), 61982 - 61974), **ClrkdavlbKME):
return oVre8I6UXc3b(kind=xafqLlk3kkUe(SXOLrMavuUCe(b'\xab\x8fH\x95'), '\x64' + chr(101) + chr(0b1000 + 0o133) + chr(111) + '\x64' + '\145')(chr(0b111111 + 0o66) + chr(0b1000001 + 0o63) + chr(0b10110 + 0o120) + '\055' + chr(83 - 27)), by=KPtq2czfwPS6, bins=KQ4BDFoY4RVo, **ClrkdavlbKME)
|
pandas-dev/pandas
|
pandas/plotting/_core.py
|
FramePlotMethods.area
|
def area(self, x=None, y=None, **kwds):
"""
Draw a stacked area plot.
An area plot displays quantitative data visually.
This function wraps the matplotlib area function.
Parameters
----------
x : label or position, optional
Coordinates for the X axis. By default uses the index.
y : label or position, optional
Column to plot. By default uses all columns.
stacked : bool, default True
Area plots are stacked by default. Set to False to create a
unstacked plot.
**kwds : optional
Additional keyword arguments are documented in
:meth:`DataFrame.plot`.
Returns
-------
matplotlib.axes.Axes or numpy.ndarray
Area plot, or array of area plots if subplots is True.
See Also
--------
DataFrame.plot : Make plots of DataFrame using matplotlib / pylab.
Examples
--------
Draw an area plot based on basic business metrics:
.. plot::
:context: close-figs
>>> df = pd.DataFrame({
... 'sales': [3, 2, 3, 9, 10, 6],
... 'signups': [5, 5, 6, 12, 14, 13],
... 'visits': [20, 42, 28, 62, 81, 50],
... }, index=pd.date_range(start='2018/01/01', end='2018/07/01',
... freq='M'))
>>> ax = df.plot.area()
Area plots are stacked by default. To produce an unstacked plot,
pass ``stacked=False``:
.. plot::
:context: close-figs
>>> ax = df.plot.area(stacked=False)
Draw an area plot for a single column:
.. plot::
:context: close-figs
>>> ax = df.plot.area(y='sales')
Draw with a different `x`:
.. plot::
:context: close-figs
>>> df = pd.DataFrame({
... 'sales': [3, 2, 3],
... 'visits': [20, 42, 28],
... 'day': [1, 2, 3],
... })
>>> ax = df.plot.area(x='day')
"""
return self(kind='area', x=x, y=y, **kwds)
|
python
|
def area(self, x=None, y=None, **kwds):
"""
Draw a stacked area plot.
An area plot displays quantitative data visually.
This function wraps the matplotlib area function.
Parameters
----------
x : label or position, optional
Coordinates for the X axis. By default uses the index.
y : label or position, optional
Column to plot. By default uses all columns.
stacked : bool, default True
Area plots are stacked by default. Set to False to create a
unstacked plot.
**kwds : optional
Additional keyword arguments are documented in
:meth:`DataFrame.plot`.
Returns
-------
matplotlib.axes.Axes or numpy.ndarray
Area plot, or array of area plots if subplots is True.
See Also
--------
DataFrame.plot : Make plots of DataFrame using matplotlib / pylab.
Examples
--------
Draw an area plot based on basic business metrics:
.. plot::
:context: close-figs
>>> df = pd.DataFrame({
... 'sales': [3, 2, 3, 9, 10, 6],
... 'signups': [5, 5, 6, 12, 14, 13],
... 'visits': [20, 42, 28, 62, 81, 50],
... }, index=pd.date_range(start='2018/01/01', end='2018/07/01',
... freq='M'))
>>> ax = df.plot.area()
Area plots are stacked by default. To produce an unstacked plot,
pass ``stacked=False``:
.. plot::
:context: close-figs
>>> ax = df.plot.area(stacked=False)
Draw an area plot for a single column:
.. plot::
:context: close-figs
>>> ax = df.plot.area(y='sales')
Draw with a different `x`:
.. plot::
:context: close-figs
>>> df = pd.DataFrame({
... 'sales': [3, 2, 3],
... 'visits': [20, 42, 28],
... 'day': [1, 2, 3],
... })
>>> ax = df.plot.area(x='day')
"""
return self(kind='area', x=x, y=y, **kwds)
|
[
"def",
"area",
"(",
"self",
",",
"x",
"=",
"None",
",",
"y",
"=",
"None",
",",
"*",
"*",
"kwds",
")",
":",
"return",
"self",
"(",
"kind",
"=",
"'area'",
",",
"x",
"=",
"x",
",",
"y",
"=",
"y",
",",
"*",
"*",
"kwds",
")"
] |
Draw a stacked area plot.
An area plot displays quantitative data visually.
This function wraps the matplotlib area function.
Parameters
----------
x : label or position, optional
Coordinates for the X axis. By default uses the index.
y : label or position, optional
Column to plot. By default uses all columns.
stacked : bool, default True
Area plots are stacked by default. Set to False to create a
unstacked plot.
**kwds : optional
Additional keyword arguments are documented in
:meth:`DataFrame.plot`.
Returns
-------
matplotlib.axes.Axes or numpy.ndarray
Area plot, or array of area plots if subplots is True.
See Also
--------
DataFrame.plot : Make plots of DataFrame using matplotlib / pylab.
Examples
--------
Draw an area plot based on basic business metrics:
.. plot::
:context: close-figs
>>> df = pd.DataFrame({
... 'sales': [3, 2, 3, 9, 10, 6],
... 'signups': [5, 5, 6, 12, 14, 13],
... 'visits': [20, 42, 28, 62, 81, 50],
... }, index=pd.date_range(start='2018/01/01', end='2018/07/01',
... freq='M'))
>>> ax = df.plot.area()
Area plots are stacked by default. To produce an unstacked plot,
pass ``stacked=False``:
.. plot::
:context: close-figs
>>> ax = df.plot.area(stacked=False)
Draw an area plot for a single column:
.. plot::
:context: close-figs
>>> ax = df.plot.area(y='sales')
Draw with a different `x`:
.. plot::
:context: close-figs
>>> df = pd.DataFrame({
... 'sales': [3, 2, 3],
... 'visits': [20, 42, 28],
... 'day': [1, 2, 3],
... })
>>> ax = df.plot.area(x='day')
|
[
"Draw",
"a",
"stacked",
"area",
"plot",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/plotting/_core.py#L3341-L3412
|
train
|
This function creates an area plot showing quantitative data visually.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + '\157' + chr(2584 - 2529) + chr(55), 0o10), ehT0Px3KOsy9('\x30' + chr(0b10101 + 0o132) + chr(49) + '\x36' + '\067', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + '\x31' + chr(0b110000 + 0o0), 0o10), ehT0Px3KOsy9('\060' + '\157' + '\063' + chr(2034 - 1980) + chr(0b110100), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(654 - 605) + chr(0b110100) + chr(693 - 641), 0b1000), ehT0Px3KOsy9('\060' + chr(10907 - 10796) + chr(0b100011 + 0o17) + chr(1495 - 1443) + chr(0b110100), 32212 - 32204), ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(8567 - 8456) + chr(1680 - 1629) + '\x36' + chr(0b11000 + 0o35), 49438 - 49430), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110010) + '\x35' + '\x31', 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\061' + chr(0b110010) + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + '\062' + chr(600 - 551) + chr(1393 - 1345), 2128 - 2120), ehT0Px3KOsy9('\x30' + chr(722 - 611) + chr(0b110011) + chr(0b10110 + 0o32) + '\x36', 64143 - 64135), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b1010 + 0o50) + chr(51) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(1856 - 1808) + chr(0b1101111) + chr(0b110011) + chr(52), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(4436 - 4325) + '\063' + '\x32' + '\063', 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + '\x35' + chr(0b110100), 56431 - 56423), ehT0Px3KOsy9(chr(453 - 405) + chr(0b1101111) + '\063' + chr(0b110001) + chr(0b110011), 28285 - 28277), ehT0Px3KOsy9('\x30' + chr(111) + '\061' + '\x36' + chr(0b110000), 0o10), ehT0Px3KOsy9(chr(2197 - 2149) + chr(0b1100001 + 0o16) + chr(49) + '\060' + chr(52), 0o10), ehT0Px3KOsy9('\x30' + chr(8144 - 8033) + chr(49) + chr(2539 - 2484) + '\062', 0o10), ehT0Px3KOsy9(chr(0b110000 + 0o0) + '\x6f' + chr(0b1111 + 0o44) + chr(0b10010 + 0o42) + '\065', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(49) + chr(0b1100 + 0o45) + '\061', 0o10), ehT0Px3KOsy9(chr(0b101110 + 0o2) + '\x6f' + chr(53) + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\062' + chr(0b110111) + '\x33', 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b100101 + 0o15) + chr(49) + chr(702 - 654), 8), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110001) + chr(0b101101 + 0o7) + chr(48), 20178 - 20170), ehT0Px3KOsy9('\060' + '\x6f' + '\066' + chr(803 - 749), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x32' + '\060' + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(1435 - 1387) + '\x6f' + '\064' + '\065', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + '\063' + chr(0b100101 + 0o15), 0o10), ehT0Px3KOsy9(chr(675 - 627) + '\x6f' + chr(0b110001) + chr(49) + '\x30', 0b1000), ehT0Px3KOsy9(chr(0b11100 + 0o24) + '\157' + '\x31' + '\x32' + '\064', 45045 - 45037), ehT0Px3KOsy9(chr(48) + '\157' + '\062' + '\064', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\061' + chr(0b110100 + 0o1) + '\x35', 0o10), ehT0Px3KOsy9('\060' + chr(0b1011 + 0o144) + chr(0b110011) + '\061' + '\060', 0o10), ehT0Px3KOsy9(chr(1712 - 1664) + chr(0b1101111) + chr(0b10101 + 0o36) + chr(0b100000 + 0o20) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b10110 + 0o34) + chr(0b100110 + 0o13) + chr(0b110110), 0o10), ehT0Px3KOsy9(chr(1740 - 1692) + chr(111) + chr(0b110011) + chr(0b110110) + chr(0b110101), 8), ehT0Px3KOsy9(chr(0b110000) + chr(12138 - 12027) + chr(1155 - 1106) + chr(1880 - 1826) + '\067', 8), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(1777 - 1724) + chr(0b110110), 0b1000), ehT0Px3KOsy9(chr(64 - 16) + chr(0b100110 + 0o111) + chr(2292 - 2238) + chr(55), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + chr(0b1001 + 0o146) + '\065' + '\x30', ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x11'), chr(100) + '\145' + chr(1096 - 997) + '\x6f' + '\x64' + '\x65')(chr(0b1110101) + chr(0b1110100) + chr(0b10010 + 0o124) + '\x2d' + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def WABECtcYvOwd(oVre8I6UXc3b, OeWW0F1dBPRQ=None, SqiSOtYOqOJH=None, **ClrkdavlbKME):
return oVre8I6UXc3b(kind=xafqLlk3kkUe(SXOLrMavuUCe(b'^\x05m\x95'), '\x64' + chr(7154 - 7053) + chr(1626 - 1527) + chr(0b1101111) + chr(0b1100100) + '\x65')(chr(117) + '\164' + chr(0b1100110) + chr(1132 - 1087) + chr(0b111000)), x=OeWW0F1dBPRQ, y=SqiSOtYOqOJH, **ClrkdavlbKME)
|
pandas-dev/pandas
|
pandas/plotting/_core.py
|
FramePlotMethods.scatter
|
def scatter(self, x, y, s=None, c=None, **kwds):
"""
Create a scatter plot with varying marker point size and color.
The coordinates of each point are defined by two dataframe columns and
filled circles are used to represent each point. This kind of plot is
useful to see complex correlations between two variables. Points could
be for instance natural 2D coordinates like longitude and latitude in
a map or, in general, any pair of metrics that can be plotted against
each other.
Parameters
----------
x : int or str
The column name or column position to be used as horizontal
coordinates for each point.
y : int or str
The column name or column position to be used as vertical
coordinates for each point.
s : scalar or array_like, optional
The size of each point. Possible values are:
- A single scalar so all points have the same size.
- A sequence of scalars, which will be used for each point's size
recursively. For instance, when passing [2,14] all points size
will be either 2 or 14, alternatively.
c : str, int or array_like, optional
The color of each point. Possible values are:
- A single color string referred to by name, RGB or RGBA code,
for instance 'red' or '#a98d19'.
- A sequence of color strings referred to by name, RGB or RGBA
code, which will be used for each point's color recursively. For
instance ['green','yellow'] all points will be filled in green or
yellow, alternatively.
- A column name or position whose values will be used to color the
marker points according to a colormap.
**kwds
Keyword arguments to pass on to :meth:`DataFrame.plot`.
Returns
-------
:class:`matplotlib.axes.Axes` or numpy.ndarray of them
See Also
--------
matplotlib.pyplot.scatter : Scatter plot using multiple input data
formats.
Examples
--------
Let's see how to draw a scatter plot using coordinates from the values
in a DataFrame's columns.
.. plot::
:context: close-figs
>>> df = pd.DataFrame([[5.1, 3.5, 0], [4.9, 3.0, 0], [7.0, 3.2, 1],
... [6.4, 3.2, 1], [5.9, 3.0, 2]],
... columns=['length', 'width', 'species'])
>>> ax1 = df.plot.scatter(x='length',
... y='width',
... c='DarkBlue')
And now with the color determined by a column as well.
.. plot::
:context: close-figs
>>> ax2 = df.plot.scatter(x='length',
... y='width',
... c='species',
... colormap='viridis')
"""
return self(kind='scatter', x=x, y=y, c=c, s=s, **kwds)
|
python
|
def scatter(self, x, y, s=None, c=None, **kwds):
"""
Create a scatter plot with varying marker point size and color.
The coordinates of each point are defined by two dataframe columns and
filled circles are used to represent each point. This kind of plot is
useful to see complex correlations between two variables. Points could
be for instance natural 2D coordinates like longitude and latitude in
a map or, in general, any pair of metrics that can be plotted against
each other.
Parameters
----------
x : int or str
The column name or column position to be used as horizontal
coordinates for each point.
y : int or str
The column name or column position to be used as vertical
coordinates for each point.
s : scalar or array_like, optional
The size of each point. Possible values are:
- A single scalar so all points have the same size.
- A sequence of scalars, which will be used for each point's size
recursively. For instance, when passing [2,14] all points size
will be either 2 or 14, alternatively.
c : str, int or array_like, optional
The color of each point. Possible values are:
- A single color string referred to by name, RGB or RGBA code,
for instance 'red' or '#a98d19'.
- A sequence of color strings referred to by name, RGB or RGBA
code, which will be used for each point's color recursively. For
instance ['green','yellow'] all points will be filled in green or
yellow, alternatively.
- A column name or position whose values will be used to color the
marker points according to a colormap.
**kwds
Keyword arguments to pass on to :meth:`DataFrame.plot`.
Returns
-------
:class:`matplotlib.axes.Axes` or numpy.ndarray of them
See Also
--------
matplotlib.pyplot.scatter : Scatter plot using multiple input data
formats.
Examples
--------
Let's see how to draw a scatter plot using coordinates from the values
in a DataFrame's columns.
.. plot::
:context: close-figs
>>> df = pd.DataFrame([[5.1, 3.5, 0], [4.9, 3.0, 0], [7.0, 3.2, 1],
... [6.4, 3.2, 1], [5.9, 3.0, 2]],
... columns=['length', 'width', 'species'])
>>> ax1 = df.plot.scatter(x='length',
... y='width',
... c='DarkBlue')
And now with the color determined by a column as well.
.. plot::
:context: close-figs
>>> ax2 = df.plot.scatter(x='length',
... y='width',
... c='species',
... colormap='viridis')
"""
return self(kind='scatter', x=x, y=y, c=c, s=s, **kwds)
|
[
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",",
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",",
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"'scatter'",
",",
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"=",
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")"
] |
Create a scatter plot with varying marker point size and color.
The coordinates of each point are defined by two dataframe columns and
filled circles are used to represent each point. This kind of plot is
useful to see complex correlations between two variables. Points could
be for instance natural 2D coordinates like longitude and latitude in
a map or, in general, any pair of metrics that can be plotted against
each other.
Parameters
----------
x : int or str
The column name or column position to be used as horizontal
coordinates for each point.
y : int or str
The column name or column position to be used as vertical
coordinates for each point.
s : scalar or array_like, optional
The size of each point. Possible values are:
- A single scalar so all points have the same size.
- A sequence of scalars, which will be used for each point's size
recursively. For instance, when passing [2,14] all points size
will be either 2 or 14, alternatively.
c : str, int or array_like, optional
The color of each point. Possible values are:
- A single color string referred to by name, RGB or RGBA code,
for instance 'red' or '#a98d19'.
- A sequence of color strings referred to by name, RGB or RGBA
code, which will be used for each point's color recursively. For
instance ['green','yellow'] all points will be filled in green or
yellow, alternatively.
- A column name or position whose values will be used to color the
marker points according to a colormap.
**kwds
Keyword arguments to pass on to :meth:`DataFrame.plot`.
Returns
-------
:class:`matplotlib.axes.Axes` or numpy.ndarray of them
See Also
--------
matplotlib.pyplot.scatter : Scatter plot using multiple input data
formats.
Examples
--------
Let's see how to draw a scatter plot using coordinates from the values
in a DataFrame's columns.
.. plot::
:context: close-figs
>>> df = pd.DataFrame([[5.1, 3.5, 0], [4.9, 3.0, 0], [7.0, 3.2, 1],
... [6.4, 3.2, 1], [5.9, 3.0, 2]],
... columns=['length', 'width', 'species'])
>>> ax1 = df.plot.scatter(x='length',
... y='width',
... c='DarkBlue')
And now with the color determined by a column as well.
.. plot::
:context: close-figs
>>> ax2 = df.plot.scatter(x='length',
... y='width',
... c='species',
... colormap='viridis')
|
[
"Create",
"a",
"scatter",
"plot",
"with",
"varying",
"marker",
"point",
"size",
"and",
"color",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/plotting/_core.py#L3463-L3542
|
train
|
Creates a scatter plot of the data for the given marker point size and color.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b110000) + chr(0b1000001 + 0o56) + chr(0b110010) + chr(49) + '\x31', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b10110 + 0o35) + chr(53) + '\060', 0o10), ehT0Px3KOsy9(chr(1542 - 1494) + chr(0b110001 + 0o76) + chr(148 - 98) + chr(253 - 200) + '\060', 0o10), ehT0Px3KOsy9(chr(1725 - 1677) + chr(8813 - 8702) + '\062' + chr(0b110000) + chr(0b110100), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b111111 + 0o60) + chr(0b110011) + chr(51) + '\064', 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + '\x31' + chr(0b110000) + '\x33', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x35' + '\062', 35753 - 35745), ehT0Px3KOsy9('\060' + '\x6f' + '\x33' + chr(48) + chr(0b10101 + 0o40), 56402 - 56394), ehT0Px3KOsy9('\060' + chr(0b100010 + 0o115) + chr(52) + chr(1609 - 1559), 0o10), ehT0Px3KOsy9(chr(2055 - 2007) + chr(0b1101100 + 0o3) + chr(0b110100) + chr(0b100110 + 0o14), 8), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x32' + '\x34' + '\x35', 0o10), ehT0Px3KOsy9(chr(1005 - 957) + chr(0b1000000 + 0o57) + chr(0b110010) + chr(0b0 + 0o66) + '\x30', 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(1669 - 1620) + chr(0b101111 + 0o6) + chr(100 - 48), ord("\x08")), ehT0Px3KOsy9(chr(0b1100 + 0o44) + '\x6f' + '\x33' + chr(48) + chr(0b100000 + 0o26), ord("\x08")), ehT0Px3KOsy9('\060' + chr(7679 - 7568) + chr(49) + chr(1390 - 1342) + '\x33', 8), ehT0Px3KOsy9(chr(262 - 214) + chr(0b1101010 + 0o5) + chr(0b110011) + chr(806 - 752) + chr(173 - 120), 0o10), ehT0Px3KOsy9(chr(1255 - 1207) + chr(6411 - 6300) + chr(1502 - 1451) + '\060' + '\x31', 15786 - 15778), ehT0Px3KOsy9('\060' + '\157' + chr(49) + chr(49) + chr(0b101101 + 0o3), 11043 - 11035), ehT0Px3KOsy9(chr(1906 - 1858) + chr(111) + '\061' + chr(2578 - 2523) + chr(0b110010), 19599 - 19591), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110010 + 0o1) + chr(1376 - 1323) + chr(0b110101), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + '\063' + chr(0b110001) + chr(0b110010), 8627 - 8619), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(844 - 794) + '\066' + '\064', 0b1000), ehT0Px3KOsy9(chr(0b100 + 0o54) + '\157' + chr(385 - 335) + '\x37', ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110010) + chr(1134 - 1079) + chr(0b110100), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(0b100000 + 0o22) + chr(0b110100), 9600 - 9592), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110011) + chr(0b110101) + '\065', 8), ehT0Px3KOsy9(chr(0b1000 + 0o50) + chr(111) + chr(0b110001) + chr(0b110001) + chr(0b110010), 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(49) + chr(54) + chr(54), 57463 - 57455), ehT0Px3KOsy9('\x30' + '\157' + '\063' + chr(0b110100) + chr(265 - 210), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + '\062' + chr(54), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(51) + chr(0b110101) + '\x34', ord("\x08")), ehT0Px3KOsy9(chr(0b11110 + 0o22) + chr(8355 - 8244) + '\x32' + chr(0b110101) + '\067', ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + '\x36' + '\065', 51373 - 51365), ehT0Px3KOsy9(chr(387 - 339) + chr(111) + '\063' + chr(0b100011 + 0o22) + '\065', 8), ehT0Px3KOsy9(chr(48) + chr(0b1000011 + 0o54) + '\x32' + '\x32' + chr(119 - 68), 0o10), ehT0Px3KOsy9(chr(0b100011 + 0o15) + chr(0b1100 + 0o143) + chr(980 - 931) + '\067' + '\x37', 0b1000), ehT0Px3KOsy9('\060' + chr(0b110011 + 0o74) + '\x32' + chr(52), 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x33' + chr(51) + chr(48), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(1035 - 924) + chr(0b11110 + 0o30) + '\x31', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111 + 0o0) + chr(51) + chr(53) + chr(680 - 632), 8)][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + '\157' + '\065' + chr(48), 36139 - 36131)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xa7'), '\144' + chr(101) + chr(99) + '\157' + chr(100) + '\x65')('\165' + '\x74' + chr(1398 - 1296) + chr(0b111 + 0o46) + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def m0cIOEVV8stJ(oVre8I6UXc3b, OeWW0F1dBPRQ, SqiSOtYOqOJH, vGrByMSYMp9h=None, qzn1Ctg9WgNh=None, **ClrkdavlbKME):
return oVre8I6UXc3b(kind=xafqLlk3kkUe(SXOLrMavuUCe(b'\xfa\x8b\xc9\xf0\xa8&X'), chr(0b10001 + 0o123) + '\x65' + '\x63' + chr(0b11001 + 0o126) + '\x64' + '\x65')('\165' + chr(10619 - 10503) + '\x66' + '\x2d' + chr(1622 - 1566)), x=OeWW0F1dBPRQ, y=SqiSOtYOqOJH, c=qzn1Ctg9WgNh, s=vGrByMSYMp9h, **ClrkdavlbKME)
|
pandas-dev/pandas
|
pandas/plotting/_core.py
|
FramePlotMethods.hexbin
|
def hexbin(self, x, y, C=None, reduce_C_function=None, gridsize=None,
**kwds):
"""
Generate a hexagonal binning plot.
Generate a hexagonal binning plot of `x` versus `y`. If `C` is `None`
(the default), this is a histogram of the number of occurrences
of the observations at ``(x[i], y[i])``.
If `C` is specified, specifies values at given coordinates
``(x[i], y[i])``. These values are accumulated for each hexagonal
bin and then reduced according to `reduce_C_function`,
having as default the NumPy's mean function (:meth:`numpy.mean`).
(If `C` is specified, it must also be a 1-D sequence
of the same length as `x` and `y`, or a column label.)
Parameters
----------
x : int or str
The column label or position for x points.
y : int or str
The column label or position for y points.
C : int or str, optional
The column label or position for the value of `(x, y)` point.
reduce_C_function : callable, default `np.mean`
Function of one argument that reduces all the values in a bin to
a single number (e.g. `np.mean`, `np.max`, `np.sum`, `np.std`).
gridsize : int or tuple of (int, int), default 100
The number of hexagons in the x-direction.
The corresponding number of hexagons in the y-direction is
chosen in a way that the hexagons are approximately regular.
Alternatively, gridsize can be a tuple with two elements
specifying the number of hexagons in the x-direction and the
y-direction.
**kwds
Additional keyword arguments are documented in
:meth:`DataFrame.plot`.
Returns
-------
matplotlib.AxesSubplot
The matplotlib ``Axes`` on which the hexbin is plotted.
See Also
--------
DataFrame.plot : Make plots of a DataFrame.
matplotlib.pyplot.hexbin : Hexagonal binning plot using matplotlib,
the matplotlib function that is used under the hood.
Examples
--------
The following examples are generated with random data from
a normal distribution.
.. plot::
:context: close-figs
>>> n = 10000
>>> df = pd.DataFrame({'x': np.random.randn(n),
... 'y': np.random.randn(n)})
>>> ax = df.plot.hexbin(x='x', y='y', gridsize=20)
The next example uses `C` and `np.sum` as `reduce_C_function`.
Note that `'observations'` values ranges from 1 to 5 but the result
plot shows values up to more than 25. This is because of the
`reduce_C_function`.
.. plot::
:context: close-figs
>>> n = 500
>>> df = pd.DataFrame({
... 'coord_x': np.random.uniform(-3, 3, size=n),
... 'coord_y': np.random.uniform(30, 50, size=n),
... 'observations': np.random.randint(1,5, size=n)
... })
>>> ax = df.plot.hexbin(x='coord_x',
... y='coord_y',
... C='observations',
... reduce_C_function=np.sum,
... gridsize=10,
... cmap="viridis")
"""
if reduce_C_function is not None:
kwds['reduce_C_function'] = reduce_C_function
if gridsize is not None:
kwds['gridsize'] = gridsize
return self(kind='hexbin', x=x, y=y, C=C, **kwds)
|
python
|
def hexbin(self, x, y, C=None, reduce_C_function=None, gridsize=None,
**kwds):
"""
Generate a hexagonal binning plot.
Generate a hexagonal binning plot of `x` versus `y`. If `C` is `None`
(the default), this is a histogram of the number of occurrences
of the observations at ``(x[i], y[i])``.
If `C` is specified, specifies values at given coordinates
``(x[i], y[i])``. These values are accumulated for each hexagonal
bin and then reduced according to `reduce_C_function`,
having as default the NumPy's mean function (:meth:`numpy.mean`).
(If `C` is specified, it must also be a 1-D sequence
of the same length as `x` and `y`, or a column label.)
Parameters
----------
x : int or str
The column label or position for x points.
y : int or str
The column label or position for y points.
C : int or str, optional
The column label or position for the value of `(x, y)` point.
reduce_C_function : callable, default `np.mean`
Function of one argument that reduces all the values in a bin to
a single number (e.g. `np.mean`, `np.max`, `np.sum`, `np.std`).
gridsize : int or tuple of (int, int), default 100
The number of hexagons in the x-direction.
The corresponding number of hexagons in the y-direction is
chosen in a way that the hexagons are approximately regular.
Alternatively, gridsize can be a tuple with two elements
specifying the number of hexagons in the x-direction and the
y-direction.
**kwds
Additional keyword arguments are documented in
:meth:`DataFrame.plot`.
Returns
-------
matplotlib.AxesSubplot
The matplotlib ``Axes`` on which the hexbin is plotted.
See Also
--------
DataFrame.plot : Make plots of a DataFrame.
matplotlib.pyplot.hexbin : Hexagonal binning plot using matplotlib,
the matplotlib function that is used under the hood.
Examples
--------
The following examples are generated with random data from
a normal distribution.
.. plot::
:context: close-figs
>>> n = 10000
>>> df = pd.DataFrame({'x': np.random.randn(n),
... 'y': np.random.randn(n)})
>>> ax = df.plot.hexbin(x='x', y='y', gridsize=20)
The next example uses `C` and `np.sum` as `reduce_C_function`.
Note that `'observations'` values ranges from 1 to 5 but the result
plot shows values up to more than 25. This is because of the
`reduce_C_function`.
.. plot::
:context: close-figs
>>> n = 500
>>> df = pd.DataFrame({
... 'coord_x': np.random.uniform(-3, 3, size=n),
... 'coord_y': np.random.uniform(30, 50, size=n),
... 'observations': np.random.randint(1,5, size=n)
... })
>>> ax = df.plot.hexbin(x='coord_x',
... y='coord_y',
... C='observations',
... reduce_C_function=np.sum,
... gridsize=10,
... cmap="viridis")
"""
if reduce_C_function is not None:
kwds['reduce_C_function'] = reduce_C_function
if gridsize is not None:
kwds['gridsize'] = gridsize
return self(kind='hexbin', x=x, y=y, C=C, **kwds)
|
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"kwds",
")"
] |
Generate a hexagonal binning plot.
Generate a hexagonal binning plot of `x` versus `y`. If `C` is `None`
(the default), this is a histogram of the number of occurrences
of the observations at ``(x[i], y[i])``.
If `C` is specified, specifies values at given coordinates
``(x[i], y[i])``. These values are accumulated for each hexagonal
bin and then reduced according to `reduce_C_function`,
having as default the NumPy's mean function (:meth:`numpy.mean`).
(If `C` is specified, it must also be a 1-D sequence
of the same length as `x` and `y`, or a column label.)
Parameters
----------
x : int or str
The column label or position for x points.
y : int or str
The column label or position for y points.
C : int or str, optional
The column label or position for the value of `(x, y)` point.
reduce_C_function : callable, default `np.mean`
Function of one argument that reduces all the values in a bin to
a single number (e.g. `np.mean`, `np.max`, `np.sum`, `np.std`).
gridsize : int or tuple of (int, int), default 100
The number of hexagons in the x-direction.
The corresponding number of hexagons in the y-direction is
chosen in a way that the hexagons are approximately regular.
Alternatively, gridsize can be a tuple with two elements
specifying the number of hexagons in the x-direction and the
y-direction.
**kwds
Additional keyword arguments are documented in
:meth:`DataFrame.plot`.
Returns
-------
matplotlib.AxesSubplot
The matplotlib ``Axes`` on which the hexbin is plotted.
See Also
--------
DataFrame.plot : Make plots of a DataFrame.
matplotlib.pyplot.hexbin : Hexagonal binning plot using matplotlib,
the matplotlib function that is used under the hood.
Examples
--------
The following examples are generated with random data from
a normal distribution.
.. plot::
:context: close-figs
>>> n = 10000
>>> df = pd.DataFrame({'x': np.random.randn(n),
... 'y': np.random.randn(n)})
>>> ax = df.plot.hexbin(x='x', y='y', gridsize=20)
The next example uses `C` and `np.sum` as `reduce_C_function`.
Note that `'observations'` values ranges from 1 to 5 but the result
plot shows values up to more than 25. This is because of the
`reduce_C_function`.
.. plot::
:context: close-figs
>>> n = 500
>>> df = pd.DataFrame({
... 'coord_x': np.random.uniform(-3, 3, size=n),
... 'coord_y': np.random.uniform(30, 50, size=n),
... 'observations': np.random.randint(1,5, size=n)
... })
>>> ax = df.plot.hexbin(x='coord_x',
... y='coord_y',
... C='observations',
... reduce_C_function=np.sum,
... gridsize=10,
... cmap="viridis")
|
[
"Generate",
"a",
"hexagonal",
"binning",
"plot",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/plotting/_core.py#L3544-L3631
|
train
|
Generates a hexagonal binning plot of the given x and y points.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110010) + chr(0b10010 + 0o45), 15603 - 15595), ehT0Px3KOsy9(chr(114 - 66) + '\157' + chr(0b110110) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(828 - 780) + '\157' + chr(0b110001) + chr(0b110111) + '\x34', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1011011 + 0o24) + chr(49) + '\067' + '\x37', ord("\x08")), ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(0b1001011 + 0o44) + chr(0b100101 + 0o14) + chr(49) + '\x37', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(9189 - 9078) + '\061' + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(0b10111 + 0o31) + '\x6f' + chr(1535 - 1486) + chr(726 - 674) + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(793 - 745) + chr(111) + chr(49) + chr(55) + chr(813 - 760), 41432 - 41424), ehT0Px3KOsy9('\x30' + chr(111) + chr(592 - 542) + chr(0b110111) + chr(0b10010 + 0o42), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(1600 - 1489) + chr(55) + '\066', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b100 + 0o57) + '\062', 0o10), ehT0Px3KOsy9('\x30' + chr(0b110111 + 0o70) + '\x31' + chr(0b110101) + chr(0b1000 + 0o57), 0o10), ehT0Px3KOsy9(chr(787 - 739) + chr(10162 - 10051) + chr(0b110001) + '\062' + '\063', 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(0b110010) + '\065' + '\x31', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b1001 + 0o53) + chr(0b11101 + 0o24), 51804 - 51796), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(2204 - 2155) + '\066' + chr(2395 - 2345), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(50) + '\x31' + chr(50), 11202 - 11194), ehT0Px3KOsy9(chr(0b11100 + 0o24) + chr(0b1101111) + chr(0b110101) + chr(282 - 230), ord("\x08")), ehT0Px3KOsy9(chr(380 - 332) + '\157' + '\061' + chr(0b110000), 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(825 - 774) + '\x32', 8), ehT0Px3KOsy9(chr(0b11000 + 0o30) + chr(0b1010 + 0o145) + chr(897 - 846) + chr(0b110100) + chr(0b110110), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\062' + chr(52) + '\x31', 20050 - 20042), ehT0Px3KOsy9(chr(48) + chr(111) + chr(52) + chr(0b110001), 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(398 - 344) + chr(0b110110), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(1138 - 1027) + chr(0b110001) + '\x30' + chr(1694 - 1642), 39288 - 39280), ehT0Px3KOsy9(chr(1487 - 1439) + chr(0b1101111) + '\061' + '\061' + chr(0b110110), 32575 - 32567), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x34', ord("\x08")), ehT0Px3KOsy9(chr(2211 - 2163) + chr(0b1101111) + chr(0b110001) + chr(0b110101) + chr(2454 - 2399), 8), ehT0Px3KOsy9('\x30' + chr(0b111000 + 0o67) + chr(49) + chr(0b110101) + chr(53), 10139 - 10131), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x32' + chr(50) + '\060', ord("\x08")), ehT0Px3KOsy9(chr(2243 - 2195) + chr(0b1100010 + 0o15) + chr(527 - 478) + chr(54), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b101000 + 0o107) + chr(0b100000 + 0o21) + chr(0b110110) + chr(935 - 886), ord("\x08")), ehT0Px3KOsy9(chr(0b10001 + 0o37) + '\x6f' + '\x32' + chr(52) + '\061', 8), ehT0Px3KOsy9('\x30' + chr(0b100100 + 0o113) + '\065' + chr(0b110010), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(1757 - 1707) + '\065' + chr(49), 8), ehT0Px3KOsy9(chr(90 - 42) + chr(6181 - 6070) + chr(0b110001) + chr(932 - 884) + '\062', 52392 - 52384), ehT0Px3KOsy9('\x30' + '\x6f' + '\063' + chr(2013 - 1964) + chr(2050 - 1999), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110001) + chr(0b11101 + 0o27) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x33' + chr(1931 - 1882) + chr(0b110000 + 0o1), 16853 - 16845), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x32' + chr(1646 - 1598) + chr(0b10011 + 0o42), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b10 + 0o56) + '\x6f' + chr(0b110101) + chr(48), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'9'), '\x64' + chr(2098 - 1997) + chr(0b1100011) + '\x6f' + '\x64' + '\x65')(chr(117) + chr(10433 - 10317) + '\x66' + chr(45) + chr(377 - 321)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def C_AhoSHYi3xd(oVre8I6UXc3b, OeWW0F1dBPRQ, SqiSOtYOqOJH, GjrcPZV7TjBn=None, jaxUsQ93gAf3=None, mKXW36uCtalY=None, **ClrkdavlbKME):
if jaxUsQ93gAf3 is not None:
ClrkdavlbKME[xafqLlk3kkUe(SXOLrMavuUCe(b'eP\x18\n,m<>\xe3Xo\x010\xddH\x1d\xe4'), chr(100) + chr(0b110111 + 0o56) + '\143' + '\x6f' + '\x64' + chr(4521 - 4420))(chr(117) + chr(0b1000100 + 0o60) + chr(9791 - 9689) + chr(1547 - 1502) + chr(56))] = jaxUsQ93gAf3
if mKXW36uCtalY is not None:
ClrkdavlbKME[xafqLlk3kkUe(SXOLrMavuUCe(b'pG\x15\x1b<a\x19\x18'), '\x64' + chr(4709 - 4608) + '\143' + chr(1444 - 1333) + chr(100) + chr(0b1011011 + 0o12))(chr(0b100000 + 0o125) + chr(0b1110100) + chr(7623 - 7521) + chr(45) + chr(422 - 366))] = mKXW36uCtalY
return oVre8I6UXc3b(kind=xafqLlk3kkUe(SXOLrMavuUCe(b'\x7fP\x04\x1d&f'), '\144' + '\x65' + chr(99) + chr(0b1101111) + chr(100) + '\x65')(chr(117) + chr(9843 - 9727) + chr(0b1001010 + 0o34) + '\055' + '\x38'), x=OeWW0F1dBPRQ, y=SqiSOtYOqOJH, C=GjrcPZV7TjBn, **ClrkdavlbKME)
|
pandas-dev/pandas
|
pandas/core/indexes/api.py
|
_get_objs_combined_axis
|
def _get_objs_combined_axis(objs, intersect=False, axis=0, sort=True):
"""
Extract combined index: return intersection or union (depending on the
value of "intersect") of indexes on given axis, or None if all objects
lack indexes (e.g. they are numpy arrays).
Parameters
----------
objs : list of objects
Each object will only be considered if it has a _get_axis
attribute.
intersect : bool, default False
If True, calculate the intersection between indexes. Otherwise,
calculate the union.
axis : {0 or 'index', 1 or 'outer'}, default 0
The axis to extract indexes from.
sort : bool, default True
Whether the result index should come out sorted or not.
Returns
-------
Index
"""
obs_idxes = [obj._get_axis(axis) for obj in objs
if hasattr(obj, '_get_axis')]
if obs_idxes:
return _get_combined_index(obs_idxes, intersect=intersect, sort=sort)
|
python
|
def _get_objs_combined_axis(objs, intersect=False, axis=0, sort=True):
"""
Extract combined index: return intersection or union (depending on the
value of "intersect") of indexes on given axis, or None if all objects
lack indexes (e.g. they are numpy arrays).
Parameters
----------
objs : list of objects
Each object will only be considered if it has a _get_axis
attribute.
intersect : bool, default False
If True, calculate the intersection between indexes. Otherwise,
calculate the union.
axis : {0 or 'index', 1 or 'outer'}, default 0
The axis to extract indexes from.
sort : bool, default True
Whether the result index should come out sorted or not.
Returns
-------
Index
"""
obs_idxes = [obj._get_axis(axis) for obj in objs
if hasattr(obj, '_get_axis')]
if obs_idxes:
return _get_combined_index(obs_idxes, intersect=intersect, sort=sort)
|
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] |
Extract combined index: return intersection or union (depending on the
value of "intersect") of indexes on given axis, or None if all objects
lack indexes (e.g. they are numpy arrays).
Parameters
----------
objs : list of objects
Each object will only be considered if it has a _get_axis
attribute.
intersect : bool, default False
If True, calculate the intersection between indexes. Otherwise,
calculate the union.
axis : {0 or 'index', 1 or 'outer'}, default 0
The axis to extract indexes from.
sort : bool, default True
Whether the result index should come out sorted or not.
Returns
-------
Index
|
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9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/indexes/api.py#L44-L70
|
train
|
Extract combined index from a list of objects.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b10001 + 0o37) + chr(0b1101111) + chr(0b110011) + chr(52) + '\064', 44334 - 44326), ehT0Px3KOsy9(chr(592 - 544) + chr(111) + chr(54) + chr(0b110010), 10422 - 10414), ehT0Px3KOsy9(chr(0b0 + 0o60) + chr(0b1000010 + 0o55) + '\063' + '\x35' + chr(50), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(50) + chr(48) + '\066', 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + '\062' + chr(0b110111) + chr(0b10101 + 0o34), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b100011 + 0o20) + chr(0b110010) + chr(702 - 650), 43033 - 43025), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x32' + chr(0b110 + 0o54), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1110 + 0o141) + chr(49) + '\061' + '\x36', 0b1000), ehT0Px3KOsy9(chr(0b100000 + 0o20) + chr(111) + chr(49) + chr(2113 - 2065) + '\065', 0o10), ehT0Px3KOsy9('\060' + chr(8984 - 8873) + chr(0b101100 + 0o5) + '\x32' + '\x31', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(49) + chr(0b110100) + chr(243 - 195), 28462 - 28454), ehT0Px3KOsy9(chr(0b110000) + chr(0b100000 + 0o117) + '\x32' + chr(0b110111) + chr(0b1001 + 0o47), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110001) + chr(574 - 522), 0b1000), ehT0Px3KOsy9('\060' + chr(9350 - 9239) + '\061' + chr(0b110101) + chr(0b101010 + 0o14), 0b1000), ehT0Px3KOsy9(chr(48) + chr(8964 - 8853) + '\062' + '\x34' + chr(1659 - 1611), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(6894 - 6783) + chr(0b110010) + chr(49), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110110) + '\060', 48119 - 48111), ehT0Px3KOsy9(chr(0b100000 + 0o20) + '\x6f' + chr(1423 - 1373) + chr(53) + chr(1056 - 1007), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b100110 + 0o13) + chr(0b110110) + '\x33', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b100100 + 0o113) + chr(0b1100 + 0o45) + '\063' + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(1811 - 1763) + chr(111) + '\063' + chr(0b110010) + chr(0b110011), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(6889 - 6778) + chr(2059 - 2009) + '\065', 0o10), ehT0Px3KOsy9('\060' + '\x6f' + '\061' + chr(0b100001 + 0o21) + '\061', 8), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(51) + chr(0b1111 + 0o43) + chr(0b110011), 8), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\063' + chr(0b10110 + 0o32), 20190 - 20182), ehT0Px3KOsy9(chr(1263 - 1215) + '\157' + '\062' + '\062', 8), ehT0Px3KOsy9(chr(48) + chr(9091 - 8980) + '\063' + '\064' + '\067', 50014 - 50006), ehT0Px3KOsy9(chr(0b11011 + 0o25) + '\157' + chr(0b110001) + chr(0b110000) + chr(0b110110), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110010) + chr(52) + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(50) + chr(0b101 + 0o55), 8), ehT0Px3KOsy9(chr(48) + chr(0b110 + 0o151) + '\062' + chr(0b10 + 0o57) + '\063', 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(50) + '\x32' + '\x35', 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(0b1010 + 0o51) + chr(53) + chr(0b100110 + 0o13), 0b1000), ehT0Px3KOsy9(chr(0b1100 + 0o44) + chr(111) + chr(0b101110 + 0o5) + '\x35' + chr(1561 - 1509), 57485 - 57477), ehT0Px3KOsy9('\x30' + '\x6f' + chr(50) + chr(0b110001) + chr(52), 0b1000), ehT0Px3KOsy9(chr(0b10010 + 0o36) + chr(0b1101111) + chr(895 - 844) + chr(0b0 + 0o61) + '\x34', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(4884 - 4773) + '\x33' + chr(0b0 + 0o62) + '\x37', 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(49) + chr(1906 - 1856) + '\062', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110011) + chr(55) + chr(0b110110), ord("\x08")), ehT0Px3KOsy9(chr(0b101000 + 0o10) + chr(0b1101111) + '\x32' + '\061' + chr(389 - 338), 8)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b11001 + 0o27) + '\x6f' + chr(53) + chr(0b110000), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xca'), chr(100) + chr(7043 - 6942) + chr(99) + chr(0b1101111) + chr(100) + chr(0b1000100 + 0o41))(chr(0b111000 + 0o75) + chr(0b111111 + 0o65) + '\x66' + chr(907 - 862) + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def S4SPHwx6J5po(RPf1nbYRQtES, LvuFd8jNQc6v=ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(0b1101111) + chr(48), 10705 - 10697), cRTh61qyvi24=ehT0Px3KOsy9(chr(579 - 531) + '\157' + '\x30', 8), tlxzdTw4q2JZ=ehT0Px3KOsy9('\x30' + chr(533 - 422) + chr(0b110001), 0o10)):
RdvE_ymzTi4Q = [mDuDykdz0pcm._get_axis(cRTh61qyvi24) for mDuDykdz0pcm in RPf1nbYRQtES if lot1PSoAwYhj(mDuDykdz0pcm, xafqLlk3kkUe(SXOLrMavuUCe(b"\xbbU\x8f\xf2\xe6\xb5j'6"), chr(0b1100100) + chr(0b1100101) + '\x63' + '\157' + chr(0b1011111 + 0o5) + '\x65')(chr(7590 - 7473) + chr(0b1110100) + '\146' + chr(0b110 + 0o47) + '\070'))]
if RdvE_ymzTi4Q:
return mxPOK6rvE_Bi(RdvE_ymzTi4Q, intersect=LvuFd8jNQc6v, sort=tlxzdTw4q2JZ)
|
pandas-dev/pandas
|
pandas/core/indexes/api.py
|
_get_distinct_objs
|
def _get_distinct_objs(objs):
"""
Return a list with distinct elements of "objs" (different ids).
Preserves order.
"""
ids = set()
res = []
for obj in objs:
if not id(obj) in ids:
ids.add(id(obj))
res.append(obj)
return res
|
python
|
def _get_distinct_objs(objs):
"""
Return a list with distinct elements of "objs" (different ids).
Preserves order.
"""
ids = set()
res = []
for obj in objs:
if not id(obj) in ids:
ids.add(id(obj))
res.append(obj)
return res
|
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"objs",
":",
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"(",
"id",
"(",
"obj",
")",
")",
"res",
".",
"append",
"(",
"obj",
")",
"return",
"res"
] |
Return a list with distinct elements of "objs" (different ids).
Preserves order.
|
[
"Return",
"a",
"list",
"with",
"distinct",
"elements",
"of",
"objs",
"(",
"different",
"ids",
")",
".",
"Preserves",
"order",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/indexes/api.py#L73-L84
|
train
|
Return a list with distinct elements of objs. Preserves order.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x31' + chr(48) + chr(2154 - 2101), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110011) + chr(0b10110 + 0o33) + chr(0b110101), 46881 - 46873), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\062' + '\067' + chr(0b100010 + 0o24), 0b1000), ehT0Px3KOsy9('\060' + chr(6611 - 6500) + chr(50) + '\x34' + chr(48), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b100110 + 0o111) + chr(256 - 207) + chr(50) + chr(53), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110011) + chr(0b11010 + 0o33) + chr(48), 1685 - 1677), ehT0Px3KOsy9(chr(48) + '\x6f' + '\061' + chr(0b110001) + '\x37', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1010110 + 0o31) + chr(53) + chr(0b1 + 0o66), 4952 - 4944), ehT0Px3KOsy9(chr(1298 - 1250) + chr(8037 - 7926) + chr(721 - 672) + '\066' + chr(0b10100 + 0o43), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + '\060', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x33' + '\x36' + '\061', ord("\x08")), ehT0Px3KOsy9('\060' + chr(2117 - 2006) + chr(0b1111 + 0o43) + '\x37' + chr(0b110011), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b101100 + 0o7) + chr(2207 - 2158), ord("\x08")), ehT0Px3KOsy9(chr(0b100000 + 0o20) + chr(111) + '\x31' + '\x33' + chr(0b110 + 0o53), 28618 - 28610), ehT0Px3KOsy9(chr(0b100111 + 0o11) + chr(3854 - 3743) + chr(49) + chr(48), ord("\x08")), ehT0Px3KOsy9(chr(0b1101 + 0o43) + chr(0b111101 + 0o62) + chr(0b110100), 34399 - 34391), ehT0Px3KOsy9('\060' + chr(809 - 698) + chr(685 - 634) + chr(0b11011 + 0o32) + chr(834 - 779), 0b1000), ehT0Px3KOsy9(chr(0b11100 + 0o24) + chr(0b1101111) + '\064' + chr(52), ord("\x08")), ehT0Px3KOsy9(chr(0b11 + 0o55) + chr(8814 - 8703) + chr(50) + chr(932 - 878) + '\061', ord("\x08")), ehT0Px3KOsy9('\060' + chr(8675 - 8564) + chr(51) + chr(2579 - 2524) + chr(48), ord("\x08")), ehT0Px3KOsy9(chr(1119 - 1071) + chr(111) + '\062' + chr(1014 - 965) + chr(513 - 462), 0b1000), ehT0Px3KOsy9(chr(0b10010 + 0o36) + chr(5035 - 4924) + '\063' + chr(0b110100) + '\x30', 0b1000), ehT0Px3KOsy9(chr(0b100011 + 0o15) + '\x6f' + chr(50) + chr(48) + '\065', 26282 - 26274), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110011) + chr(0b110110) + '\x35', 0o10), ehT0Px3KOsy9(chr(0b100011 + 0o15) + chr(0b1100 + 0o143) + chr(49) + chr(0b110110) + chr(640 - 591), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + '\061' + chr(2431 - 2376) + chr(48), ord("\x08")), ehT0Px3KOsy9(chr(0b101000 + 0o10) + chr(111) + chr(0b110011) + '\x32' + '\061', 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b101011 + 0o7) + chr(0b110011 + 0o3) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b10111 + 0o36) + '\x37', 8), ehT0Px3KOsy9(chr(0b1010 + 0o46) + '\157' + chr(50) + chr(571 - 523) + '\x33', 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(55) + chr(52), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + '\x31' + chr(0b110101), 0b1000), ehT0Px3KOsy9(chr(48) + chr(11882 - 11771) + chr(0b1000 + 0o53) + '\x30' + chr(0b110110), 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(0b101001 + 0o10) + chr(1690 - 1639) + chr(0b110111), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + '\063' + chr(0b100010 + 0o22) + '\x30', 8), ehT0Px3KOsy9('\x30' + chr(0b100001 + 0o116) + chr(0b110011) + '\x31' + chr(2791 - 2737), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110001) + chr(0b1011 + 0o45) + chr(1232 - 1180), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110001) + '\x31' + chr(0b110110), 18142 - 18134), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x33' + chr(50) + chr(0b110001), 8), ehT0Px3KOsy9(chr(48) + chr(12229 - 12118) + '\x33' + '\062' + chr(2227 - 2178), 8)][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + '\157' + chr(1439 - 1386) + chr(0b1001 + 0o47), 38461 - 38453)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'k'), '\x64' + '\145' + chr(4222 - 4123) + chr(0b1010000 + 0o37) + '\144' + chr(0b1100101))(chr(0b1110100 + 0o1) + chr(116) + '\146' + chr(1353 - 1308) + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def WLXWf4DuIU18(RPf1nbYRQtES):
zdjj2pRemk_P = MVEN8G6CxlvR()
MsbwfslwLjRO = []
for mDuDykdz0pcm in RPf1nbYRQtES:
if not z8EhBlYI2Bx4(mDuDykdz0pcm) in zdjj2pRemk_P:
xafqLlk3kkUe(zdjj2pRemk_P, xafqLlk3kkUe(SXOLrMavuUCe(b'$\xa9\xda'), '\x64' + chr(494 - 393) + '\x63' + '\x6f' + chr(100) + chr(101))('\165' + chr(116) + chr(0b1011011 + 0o13) + '\x2d' + chr(0b111000)))(z8EhBlYI2Bx4(mDuDykdz0pcm))
xafqLlk3kkUe(MsbwfslwLjRO, xafqLlk3kkUe(SXOLrMavuUCe(b'$\xbd\xce\xc5;\x8c'), chr(100) + '\145' + chr(99) + '\157' + chr(0b1100100) + chr(0b1011001 + 0o14))('\x75' + '\x74' + chr(0b1100110) + chr(0b100010 + 0o13) + chr(1933 - 1877)))(mDuDykdz0pcm)
return MsbwfslwLjRO
|
pandas-dev/pandas
|
pandas/core/indexes/api.py
|
_get_combined_index
|
def _get_combined_index(indexes, intersect=False, sort=False):
"""
Return the union or intersection of indexes.
Parameters
----------
indexes : list of Index or list objects
When intersect=True, do not accept list of lists.
intersect : bool, default False
If True, calculate the intersection between indexes. Otherwise,
calculate the union.
sort : bool, default False
Whether the result index should come out sorted or not.
Returns
-------
Index
"""
# TODO: handle index names!
indexes = _get_distinct_objs(indexes)
if len(indexes) == 0:
index = Index([])
elif len(indexes) == 1:
index = indexes[0]
elif intersect:
index = indexes[0]
for other in indexes[1:]:
index = index.intersection(other)
else:
index = _union_indexes(indexes, sort=sort)
index = ensure_index(index)
if sort:
try:
index = index.sort_values()
except TypeError:
pass
return index
|
python
|
def _get_combined_index(indexes, intersect=False, sort=False):
"""
Return the union or intersection of indexes.
Parameters
----------
indexes : list of Index or list objects
When intersect=True, do not accept list of lists.
intersect : bool, default False
If True, calculate the intersection between indexes. Otherwise,
calculate the union.
sort : bool, default False
Whether the result index should come out sorted or not.
Returns
-------
Index
"""
# TODO: handle index names!
indexes = _get_distinct_objs(indexes)
if len(indexes) == 0:
index = Index([])
elif len(indexes) == 1:
index = indexes[0]
elif intersect:
index = indexes[0]
for other in indexes[1:]:
index = index.intersection(other)
else:
index = _union_indexes(indexes, sort=sort)
index = ensure_index(index)
if sort:
try:
index = index.sort_values()
except TypeError:
pass
return index
|
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] |
Return the union or intersection of indexes.
Parameters
----------
indexes : list of Index or list objects
When intersect=True, do not accept list of lists.
intersect : bool, default False
If True, calculate the intersection between indexes. Otherwise,
calculate the union.
sort : bool, default False
Whether the result index should come out sorted or not.
Returns
-------
Index
|
[
"Return",
"the",
"union",
"or",
"intersection",
"of",
"indexes",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/indexes/api.py#L87-L125
|
train
|
Returns the union or intersection of the given list of indexes.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110111) + '\067', ord("\x08")), ehT0Px3KOsy9(chr(1976 - 1928) + '\157' + chr(0b100110 + 0o13) + chr(616 - 566) + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(0b11010 + 0o26) + '\x6f' + chr(0b110010) + chr(0b110110) + '\067', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\063' + chr(0b11101 + 0o27) + chr(1956 - 1905), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b100011 + 0o114) + chr(474 - 424) + '\067' + '\062', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\063' + chr(0b110110) + chr(1292 - 1243), 30139 - 30131), ehT0Px3KOsy9(chr(932 - 884) + chr(9740 - 9629) + chr(2301 - 2251) + '\x37' + '\066', 28189 - 28181), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x31' + chr(51) + chr(0b111 + 0o60), 63333 - 63325), ehT0Px3KOsy9(chr(0b101000 + 0o10) + chr(111) + chr(0b110011) + '\x37' + '\061', 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(49) + '\x35' + chr(1890 - 1841), 34744 - 34736), ehT0Px3KOsy9(chr(2223 - 2175) + chr(0b10001 + 0o136) + chr(0b110111) + chr(0b110010), 2306 - 2298), ehT0Px3KOsy9('\x30' + chr(111) + chr(1961 - 1912) + chr(0b110110) + '\061', 4088 - 4080), ehT0Px3KOsy9(chr(1634 - 1586) + '\x6f' + chr(589 - 539) + chr(54) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1011010 + 0o25) + '\062' + chr(0b110001) + chr(0b110111), 0o10), ehT0Px3KOsy9(chr(0b1111 + 0o41) + chr(0b1000 + 0o147) + '\x32' + '\067' + '\x30', 6222 - 6214), ehT0Px3KOsy9(chr(1862 - 1814) + chr(0b1101111) + chr(565 - 516) + chr(0b110110 + 0o1), 0o10), ehT0Px3KOsy9(chr(1472 - 1424) + '\x6f' + chr(0b110100), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b10101 + 0o34) + chr(0b11000 + 0o32) + '\064', 0o10), ehT0Px3KOsy9('\x30' + chr(1029 - 918) + chr(0b10000 + 0o42) + '\062' + '\x31', 0o10), ehT0Px3KOsy9(chr(1073 - 1025) + '\x6f' + chr(0b110001) + chr(0b1 + 0o57) + '\x34', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\063', 0o10), ehT0Px3KOsy9(chr(2161 - 2113) + chr(0b1101111) + '\x33' + '\x33' + chr(55), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(2476 - 2425) + chr(54) + chr(588 - 533), 63715 - 63707), ehT0Px3KOsy9('\060' + '\x6f' + chr(2306 - 2256) + '\062' + chr(710 - 657), 0o10), ehT0Px3KOsy9('\x30' + chr(0b101110 + 0o101) + '\x33' + chr(2121 - 2067), 0b1000), ehT0Px3KOsy9(chr(0b101011 + 0o5) + '\x6f' + chr(1809 - 1760) + chr(0b110011) + chr(0b11100 + 0o30), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x37' + chr(50), 8), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b10101 + 0o36), 8), ehT0Px3KOsy9('\060' + chr(111) + chr(0b101010 + 0o14) + '\x32', 0o10), ehT0Px3KOsy9('\060' + chr(263 - 152) + chr(0b110001) + chr(49) + chr(0b110000), 12322 - 12314), ehT0Px3KOsy9(chr(2131 - 2083) + chr(0b1101111) + '\x35' + chr(0b11101 + 0o30), 0o10), ehT0Px3KOsy9(chr(2020 - 1972) + '\x6f' + chr(0b1 + 0o60) + chr(0b1101 + 0o52) + chr(50), 23056 - 23048), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x31' + chr(49), ord("\x08")), ehT0Px3KOsy9(chr(0b100 + 0o54) + chr(111) + chr(0b110001) + chr(0b1111 + 0o46) + chr(1995 - 1941), 0o10), ehT0Px3KOsy9(chr(1827 - 1779) + '\157' + '\x32' + '\x30', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b101000 + 0o11) + chr(0b1 + 0o65), 560 - 552), ehT0Px3KOsy9(chr(48) + chr(1904 - 1793) + chr(902 - 851) + chr(0b110110) + chr(0b11011 + 0o26), 8), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b11110 + 0o27) + chr(0b110000), 0b1000), ehT0Px3KOsy9('\x30' + chr(745 - 634) + '\062' + chr(905 - 854), 0o10), ehT0Px3KOsy9(chr(0b11111 + 0o21) + chr(111) + chr(0b110001) + '\063' + chr(0b100110 + 0o16), 8)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + '\157' + chr(0b100 + 0o61) + '\060', 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x11'), '\x64' + chr(0b1000010 + 0o43) + chr(6005 - 5906) + chr(111) + chr(321 - 221) + '\145')('\165' + chr(0b1110100) + chr(102) + chr(45) + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def mxPOK6rvE_Bi(AjrnLNzw5Jx9, LvuFd8jNQc6v=ehT0Px3KOsy9(chr(219 - 171) + '\157' + chr(0b110000), 0b1000), tlxzdTw4q2JZ=ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x30', 8)):
AjrnLNzw5Jx9 = WLXWf4DuIU18(AjrnLNzw5Jx9)
if c2A0yzQpDQB3(AjrnLNzw5Jx9) == ehT0Px3KOsy9('\060' + chr(7387 - 7276) + chr(0b110000), 8):
XdowRbJKZWL9 = EJkE1Nx1bysb([])
elif c2A0yzQpDQB3(AjrnLNzw5Jx9) == ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110001), ord("\x08")):
XdowRbJKZWL9 = AjrnLNzw5Jx9[ehT0Px3KOsy9(chr(0b110000) + chr(10909 - 10798) + chr(0b10001 + 0o37), 8)]
elif LvuFd8jNQc6v:
XdowRbJKZWL9 = AjrnLNzw5Jx9[ehT0Px3KOsy9(chr(2185 - 2137) + chr(0b1001111 + 0o40) + chr(286 - 238), 8)]
for KK0ERS7DqYrY in AjrnLNzw5Jx9[ehT0Px3KOsy9('\x30' + chr(111) + chr(0b101110 + 0o3), 8):]:
XdowRbJKZWL9 = XdowRbJKZWL9.intersection(KK0ERS7DqYrY)
else:
XdowRbJKZWL9 = ZcF4seQtcWcJ(AjrnLNzw5Jx9, sort=tlxzdTw4q2JZ)
XdowRbJKZWL9 = KFvEC5zbP6VW(XdowRbJKZWL9)
if tlxzdTw4q2JZ:
try:
XdowRbJKZWL9 = XdowRbJKZWL9.sort_values()
except sznFqDbNBHlx:
pass
return XdowRbJKZWL9
|
pandas-dev/pandas
|
pandas/core/indexes/api.py
|
_union_indexes
|
def _union_indexes(indexes, sort=True):
"""
Return the union of indexes.
The behavior of sort and names is not consistent.
Parameters
----------
indexes : list of Index or list objects
sort : bool, default True
Whether the result index should come out sorted or not.
Returns
-------
Index
"""
if len(indexes) == 0:
raise AssertionError('Must have at least 1 Index to union')
if len(indexes) == 1:
result = indexes[0]
if isinstance(result, list):
result = Index(sorted(result))
return result
indexes, kind = _sanitize_and_check(indexes)
def _unique_indices(inds):
"""
Convert indexes to lists and concatenate them, removing duplicates.
The final dtype is inferred.
Parameters
----------
inds : list of Index or list objects
Returns
-------
Index
"""
def conv(i):
if isinstance(i, Index):
i = i.tolist()
return i
return Index(
lib.fast_unique_multiple_list([conv(i) for i in inds], sort=sort))
if kind == 'special':
result = indexes[0]
if hasattr(result, 'union_many'):
return result.union_many(indexes[1:])
else:
for other in indexes[1:]:
result = result.union(other)
return result
elif kind == 'array':
index = indexes[0]
for other in indexes[1:]:
if not index.equals(other):
if sort is None:
# TODO: remove once pd.concat sort default changes
warnings.warn(_sort_msg, FutureWarning, stacklevel=8)
sort = True
return _unique_indices(indexes)
name = _get_consensus_names(indexes)[0]
if name != index.name:
index = index._shallow_copy(name=name)
return index
else: # kind='list'
return _unique_indices(indexes)
|
python
|
def _union_indexes(indexes, sort=True):
"""
Return the union of indexes.
The behavior of sort and names is not consistent.
Parameters
----------
indexes : list of Index or list objects
sort : bool, default True
Whether the result index should come out sorted or not.
Returns
-------
Index
"""
if len(indexes) == 0:
raise AssertionError('Must have at least 1 Index to union')
if len(indexes) == 1:
result = indexes[0]
if isinstance(result, list):
result = Index(sorted(result))
return result
indexes, kind = _sanitize_and_check(indexes)
def _unique_indices(inds):
"""
Convert indexes to lists and concatenate them, removing duplicates.
The final dtype is inferred.
Parameters
----------
inds : list of Index or list objects
Returns
-------
Index
"""
def conv(i):
if isinstance(i, Index):
i = i.tolist()
return i
return Index(
lib.fast_unique_multiple_list([conv(i) for i in inds], sort=sort))
if kind == 'special':
result = indexes[0]
if hasattr(result, 'union_many'):
return result.union_many(indexes[1:])
else:
for other in indexes[1:]:
result = result.union(other)
return result
elif kind == 'array':
index = indexes[0]
for other in indexes[1:]:
if not index.equals(other):
if sort is None:
# TODO: remove once pd.concat sort default changes
warnings.warn(_sort_msg, FutureWarning, stacklevel=8)
sort = True
return _unique_indices(indexes)
name = _get_consensus_names(indexes)[0]
if name != index.name:
index = index._shallow_copy(name=name)
return index
else: # kind='list'
return _unique_indices(indexes)
|
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Return the union of indexes.
The behavior of sort and names is not consistent.
Parameters
----------
indexes : list of Index or list objects
sort : bool, default True
Whether the result index should come out sorted or not.
Returns
-------
Index
|
[
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] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/indexes/api.py#L128-L202
|
train
|
Returns the union of the given list of indexes.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\063' + '\x37' + '\x37', 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(1097 - 1048) + chr(53) + '\x31', 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(50) + chr(53) + '\067', 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(49) + chr(0b110111) + '\x37', 0b1000), ehT0Px3KOsy9(chr(0b110000 + 0o0) + chr(0b1101111) + '\x33' + chr(2153 - 2104) + chr(0b100100 + 0o16), 56353 - 56345), ehT0Px3KOsy9(chr(953 - 905) + chr(0b1101111) + chr(0b110010) + chr(0b110000) + chr(0b110100), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b1011 + 0o52) + '\x36', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\062' + '\064' + chr(497 - 447), 0b1000), ehT0Px3KOsy9('\x30' + chr(11269 - 11158) + chr(50) + chr(2588 - 2534) + chr(0b11001 + 0o34), 38288 - 38280), ehT0Px3KOsy9(chr(483 - 435) + chr(12120 - 12009) + '\062' + chr(55) + chr(0b110011), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b110 + 0o151) + chr(0b110010) + chr(51) + chr(0b110111), 48126 - 48118), ehT0Px3KOsy9(chr(48) + '\157' + chr(49) + '\x35' + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110010) + chr(49) + chr(50), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(0b1000 + 0o52) + '\x33' + chr(0b11110 + 0o25), ord("\x08")), ehT0Px3KOsy9(chr(0b1011 + 0o45) + '\x6f' + chr(0b110001) + chr(0b101100 + 0o13) + chr(54), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b10100 + 0o35) + chr(2053 - 2005) + chr(2636 - 2581), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + '\061' + chr(0b101 + 0o53) + chr(0b1110 + 0o45), 28090 - 28082), ehT0Px3KOsy9(chr(813 - 765) + '\x6f' + chr(0b11101 + 0o26) + '\x36' + chr(0b110010), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(106 - 52), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(142 - 92) + chr(0b110111) + '\x34', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1011 + 0o144) + chr(0b110010) + '\x31' + chr(50), 8), ehT0Px3KOsy9(chr(0b1110 + 0o42) + chr(0b1101111) + chr(408 - 356) + '\x35', 0b1000), ehT0Px3KOsy9('\x30' + '\157' + '\061' + chr(0b110001) + chr(275 - 221), ord("\x08")), ehT0Px3KOsy9(chr(119 - 71) + chr(4596 - 4485) + '\x31' + chr(0b110010) + '\065', 0o10), ehT0Px3KOsy9(chr(2082 - 2034) + chr(0b1101111) + '\063' + chr(49) + chr(0b110010), 8), ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(0b1001111 + 0o40) + chr(0b110011) + chr(0b1101 + 0o43) + '\066', 60044 - 60036), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(53) + '\x33', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b10111 + 0o36) + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(2594 - 2483) + chr(0b111 + 0o53) + chr(51) + '\063', 8), ehT0Px3KOsy9(chr(412 - 364) + chr(7345 - 7234) + '\066' + chr(0b110100), ord("\x08")), ehT0Px3KOsy9(chr(0b1001 + 0o47) + chr(0b1010100 + 0o33) + '\062' + chr(2028 - 1973) + chr(0b100010 + 0o22), 8), ehT0Px3KOsy9(chr(1319 - 1271) + chr(0b111111 + 0o60) + '\x33' + chr(0b1001 + 0o47) + chr(1629 - 1575), 8), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110000 + 0o3) + '\061' + chr(52), 58231 - 58223), ehT0Px3KOsy9(chr(0b11000 + 0o30) + '\157' + '\062' + chr(0b110000) + chr(1822 - 1771), 38406 - 38398), ehT0Px3KOsy9(chr(0b110000) + chr(12144 - 12033) + chr(0b1111 + 0o42) + chr(0b101001 + 0o12) + chr(0b110110), 6427 - 6419), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(50) + chr(0b110010) + chr(0b110011), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(6892 - 6781) + chr(0b11000 + 0o32) + '\x32' + chr(153 - 99), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + '\x31' + chr(0b110101), 35693 - 35685), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(525 - 476) + '\x34' + chr(0b1011 + 0o53), 0o10), ehT0Px3KOsy9(chr(1753 - 1705) + chr(111) + chr(0b110001) + chr(0b100011 + 0o22) + chr(0b110110), 34071 - 34063)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + chr(7619 - 7508) + chr(2242 - 2189) + '\060', 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xd1'), chr(100) + chr(7002 - 6901) + '\x63' + '\157' + chr(9670 - 9570) + chr(101))('\x75' + '\x74' + chr(102) + chr(45) + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def ZcF4seQtcWcJ(AjrnLNzw5Jx9, tlxzdTw4q2JZ=ehT0Px3KOsy9(chr(48) + chr(111) + chr(2376 - 2327), ord("\x08"))):
if c2A0yzQpDQB3(AjrnLNzw5Jx9) == ehT0Px3KOsy9(chr(0b110000) + chr(0b1011111 + 0o20) + '\x30', 0b1000):
raise vcEHXBQXuDuh(xafqLlk3kkUe(SXOLrMavuUCe(b'\xb2\x1c\xdc\x0b\xea\xecO\xd4\xd0\x9b\xfe\x1c\xaa\xf7\x1b&0\x86&\x8d\xaal 1\xaf\xbe\x0b]\xf4\x14\xc9\xa8\xa5\xec0'), chr(0b1100100) + '\x65' + chr(3123 - 3024) + chr(0b100101 + 0o112) + chr(100) + '\x65')('\165' + chr(0b1110100) + chr(4600 - 4498) + chr(0b1000 + 0o45) + '\x38'))
if c2A0yzQpDQB3(AjrnLNzw5Jx9) == ehT0Px3KOsy9('\x30' + chr(111) + '\x31', 8):
ShZmEKfTkAOZ = AjrnLNzw5Jx9[ehT0Px3KOsy9(chr(0b11100 + 0o24) + chr(0b1011001 + 0o26) + '\060', 8)]
if PlSM16l2KDPD(ShZmEKfTkAOZ, YyaZ4tpXu4lf):
ShZmEKfTkAOZ = EJkE1Nx1bysb(vUlqIvNSaRMa(ShZmEKfTkAOZ))
return ShZmEKfTkAOZ
(AjrnLNzw5Jx9, el8JiuKFoeai) = SSZUcObFZuSr(AjrnLNzw5Jx9)
def M3Dh72AQhWnu(HP9YF4VVcIuY):
def m1sWr00SVpVY(WVxHKyX45z_L):
if PlSM16l2KDPD(WVxHKyX45z_L, EJkE1Nx1bysb):
WVxHKyX45z_L = WVxHKyX45z_L.tolist()
return WVxHKyX45z_L
return EJkE1Nx1bysb(xafqLlk3kkUe(JiWVXlj3BjzT, xafqLlk3kkUe(SXOLrMavuUCe(b"\x99\x08\xdc\x0b\x95\xf1@\xcb\xc4\xce\xfa7\xe7\xee\x123*\x82j\xd9\xd5I'&\xbe"), chr(100) + chr(101) + '\x63' + chr(1601 - 1490) + chr(0b1100100) + chr(101))('\165' + chr(0b1110100) + chr(102) + '\x2d' + chr(56)))([m1sWr00SVpVY(WVxHKyX45z_L) for WVxHKyX45z_L in HP9YF4VVcIuY], sort=tlxzdTw4q2JZ))
if el8JiuKFoeai == xafqLlk3kkUe(SXOLrMavuUCe(b'\x8c\x19\xca\x1c\xa3\xe5B'), '\144' + '\145' + '\143' + chr(12124 - 12013) + '\x64' + chr(0b1100101))(chr(0b1110101) + chr(0b1110100) + chr(102) + chr(0b101101) + '\x38'):
ShZmEKfTkAOZ = AjrnLNzw5Jx9[ehT0Px3KOsy9(chr(48) + chr(0b100110 + 0o111) + '\x30', 8)]
if lot1PSoAwYhj(ShZmEKfTkAOZ, xafqLlk3kkUe(SXOLrMavuUCe(b'\x8a\x07\xc6\x10\xa4\xdbC\xc3\xdb\xc2'), '\144' + chr(101) + '\x63' + chr(0b1101111) + chr(100) + '\145')('\x75' + '\x74' + '\146' + '\x2d' + chr(0b111000))):
return xafqLlk3kkUe(ShZmEKfTkAOZ, xafqLlk3kkUe(SXOLrMavuUCe(b'\x8a\x07\xc6\x10\xa4\xdbC\xc3\xdb\xc2'), chr(0b1001110 + 0o26) + chr(0b10010 + 0o123) + chr(0b1000110 + 0o35) + chr(111) + chr(0b1100100) + chr(0b101001 + 0o74))(chr(117) + chr(8031 - 7915) + '\x66' + chr(0b101101) + '\x38'))(AjrnLNzw5Jx9[ehT0Px3KOsy9(chr(0b110000) + chr(0b1101011 + 0o4) + chr(49), 8):])
else:
for KK0ERS7DqYrY in AjrnLNzw5Jx9[ehT0Px3KOsy9(chr(0b110 + 0o52) + chr(111) + chr(2320 - 2271), 8):]:
ShZmEKfTkAOZ = ShZmEKfTkAOZ.union(KK0ERS7DqYrY)
return ShZmEKfTkAOZ
elif el8JiuKFoeai == xafqLlk3kkUe(SXOLrMavuUCe(b'\x9e\x1b\xdd\x1e\xb3'), chr(6329 - 6229) + '\145' + '\143' + '\x6f' + chr(100) + chr(101))(chr(1235 - 1118) + '\164' + '\x66' + chr(45) + '\x38'):
XdowRbJKZWL9 = AjrnLNzw5Jx9[ehT0Px3KOsy9(chr(0b11 + 0o55) + chr(111) + chr(1398 - 1350), 8)]
for KK0ERS7DqYrY in AjrnLNzw5Jx9[ehT0Px3KOsy9(chr(238 - 190) + chr(0b1101111) + '\061', 8):]:
if not xafqLlk3kkUe(XdowRbJKZWL9, xafqLlk3kkUe(SXOLrMavuUCe(b'\x9a\x18\xda\x1e\xa6\xf7'), chr(0b1100100) + chr(101) + '\143' + chr(0b1101111) + '\x64' + '\145')('\x75' + chr(1746 - 1630) + '\146' + chr(0b101101) + '\x38'))(KK0ERS7DqYrY):
if tlxzdTw4q2JZ is None:
xafqLlk3kkUe(fJoTPf8D_opC, xafqLlk3kkUe(SXOLrMavuUCe(b'\x88\x08\xdd\x11'), '\x64' + '\145' + chr(0b100011 + 0o100) + chr(0b11110 + 0o121) + '\144' + chr(7172 - 7071))(chr(0b1110101) + '\164' + '\146' + chr(45) + chr(2023 - 1967)))(g2mEWSdTYt7Q, VHAt7CcYKC2T, stacklevel=ehT0Px3KOsy9(chr(793 - 745) + chr(111) + '\061' + chr(0b110000), 17661 - 17653))
tlxzdTw4q2JZ = ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110001), 8)
return M3Dh72AQhWnu(AjrnLNzw5Jx9)
AIvJRzLdDfgF = znvfqcl2Li30(AjrnLNzw5Jx9)[ehT0Px3KOsy9('\x30' + chr(9951 - 9840) + chr(48), 8)]
if AIvJRzLdDfgF != xafqLlk3kkUe(XdowRbJKZWL9, xafqLlk3kkUe(SXOLrMavuUCe(b'\xbe \xd95\x98\xfeb\xc6\xf1\xdd\xf8.'), '\x64' + '\145' + chr(99) + chr(0b1101111) + chr(0b1010000 + 0o24) + chr(0b1100101))(chr(11176 - 11059) + chr(0b1110100) + '\x66' + '\055' + '\x38')):
XdowRbJKZWL9 = XdowRbJKZWL9._shallow_copy(name=AIvJRzLdDfgF)
return XdowRbJKZWL9
else:
return M3Dh72AQhWnu(AjrnLNzw5Jx9)
|
pandas-dev/pandas
|
pandas/core/indexes/api.py
|
_sanitize_and_check
|
def _sanitize_and_check(indexes):
"""
Verify the type of indexes and convert lists to Index.
Cases:
- [list, list, ...]: Return ([list, list, ...], 'list')
- [list, Index, ...]: Return _sanitize_and_check([Index, Index, ...])
Lists are sorted and converted to Index.
- [Index, Index, ...]: Return ([Index, Index, ...], TYPE)
TYPE = 'special' if at least one special type, 'array' otherwise.
Parameters
----------
indexes : list of Index or list objects
Returns
-------
sanitized_indexes : list of Index or list objects
type : {'list', 'array', 'special'}
"""
kinds = list({type(index) for index in indexes})
if list in kinds:
if len(kinds) > 1:
indexes = [Index(com.try_sort(x))
if not isinstance(x, Index) else
x for x in indexes]
kinds.remove(list)
else:
return indexes, 'list'
if len(kinds) > 1 or Index not in kinds:
return indexes, 'special'
else:
return indexes, 'array'
|
python
|
def _sanitize_and_check(indexes):
"""
Verify the type of indexes and convert lists to Index.
Cases:
- [list, list, ...]: Return ([list, list, ...], 'list')
- [list, Index, ...]: Return _sanitize_and_check([Index, Index, ...])
Lists are sorted and converted to Index.
- [Index, Index, ...]: Return ([Index, Index, ...], TYPE)
TYPE = 'special' if at least one special type, 'array' otherwise.
Parameters
----------
indexes : list of Index or list objects
Returns
-------
sanitized_indexes : list of Index or list objects
type : {'list', 'array', 'special'}
"""
kinds = list({type(index) for index in indexes})
if list in kinds:
if len(kinds) > 1:
indexes = [Index(com.try_sort(x))
if not isinstance(x, Index) else
x for x in indexes]
kinds.remove(list)
else:
return indexes, 'list'
if len(kinds) > 1 or Index not in kinds:
return indexes, 'special'
else:
return indexes, 'array'
|
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] |
Verify the type of indexes and convert lists to Index.
Cases:
- [list, list, ...]: Return ([list, list, ...], 'list')
- [list, Index, ...]: Return _sanitize_and_check([Index, Index, ...])
Lists are sorted and converted to Index.
- [Index, Index, ...]: Return ([Index, Index, ...], TYPE)
TYPE = 'special' if at least one special type, 'array' otherwise.
Parameters
----------
indexes : list of Index or list objects
Returns
-------
sanitized_indexes : list of Index or list objects
type : {'list', 'array', 'special'}
|
[
"Verify",
"the",
"type",
"of",
"indexes",
"and",
"convert",
"lists",
"to",
"Index",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/indexes/api.py#L205-L240
|
train
|
Verify the type of indexes and convert lists to Index.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(48) + chr(8249 - 8138) + chr(49) + chr(92 - 40) + '\065', ord("\x08")), ehT0Px3KOsy9(chr(0b10010 + 0o36) + chr(1007 - 896) + chr(1259 - 1209) + chr(50) + chr(2367 - 2318), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b101011 + 0o104) + chr(0b110111), 28575 - 28567), ehT0Px3KOsy9('\x30' + chr(111) + chr(1065 - 1012) + '\x34', 0b1000), ehT0Px3KOsy9(chr(247 - 199) + chr(111) + chr(50) + chr(54) + chr(0b110000), 24930 - 24922), ehT0Px3KOsy9('\x30' + chr(5868 - 5757) + '\061' + '\x34' + chr(0b101011 + 0o7), 44587 - 44579), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110001) + chr(0b110111) + '\x35', 62757 - 62749), ehT0Px3KOsy9(chr(0b110000) + chr(0b1000101 + 0o52) + chr(50) + chr(0b110010), 7815 - 7807), ehT0Px3KOsy9('\x30' + '\157' + chr(2217 - 2167), 0o10), ehT0Px3KOsy9(chr(0b10010 + 0o36) + chr(111) + chr(0b110001) + chr(0b100101 + 0o14) + '\x35', ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110001) + chr(0b110101) + chr(52), 12132 - 12124), ehT0Px3KOsy9('\x30' + chr(0b1001 + 0o146) + chr(0b1111 + 0o44) + '\x34' + '\x33', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b110000 + 0o77) + '\062' + chr(53) + chr(51), 0o10), ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(7919 - 7808) + '\x32' + chr(50) + chr(0b1111 + 0o44), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110000 + 0o1), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(5240 - 5129) + chr(2078 - 2029) + chr(50) + chr(49), 0o10), ehT0Px3KOsy9(chr(0b11111 + 0o21) + '\x6f' + '\x33' + '\x37' + chr(0b110000), 0o10), ehT0Px3KOsy9('\060' + chr(9240 - 9129) + chr(51) + '\x35' + chr(0b111 + 0o52), 0o10), ehT0Px3KOsy9(chr(0b10 + 0o56) + chr(111) + '\064' + chr(0b110001), 1195 - 1187), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110010) + '\x36' + chr(668 - 619), ord("\x08")), ehT0Px3KOsy9(chr(0b100100 + 0o14) + '\x6f' + chr(0b11000 + 0o31) + chr(0b110000) + chr(0b1111 + 0o45), 55402 - 55394), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110111) + '\060', 19732 - 19724), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(2269 - 2219) + '\065' + chr(1732 - 1682), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1001000 + 0o47) + '\062' + chr(0b1001 + 0o56) + chr(143 - 95), ord("\x08")), ehT0Px3KOsy9(chr(236 - 188) + chr(0b1101111) + chr(866 - 816) + chr(2143 - 2090) + '\063', 8), ehT0Px3KOsy9(chr(63 - 15) + '\x6f' + '\x37' + chr(0b1101 + 0o47), 0o10), ehT0Px3KOsy9('\x30' + '\157' + '\066' + chr(929 - 876), 0b1000), ehT0Px3KOsy9(chr(323 - 275) + chr(0b111010 + 0o65) + chr(50) + chr(0b110110), 9579 - 9571), ehT0Px3KOsy9('\060' + '\157' + chr(2152 - 2099) + '\066', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x33' + chr(0b1100 + 0o53) + '\067', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b10100 + 0o36) + chr(0b110100 + 0o2) + chr(51), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1011 + 0o144) + '\x31' + chr(923 - 870) + chr(0b110101), 48629 - 48621), ehT0Px3KOsy9(chr(48) + chr(0b100101 + 0o112) + chr(50) + '\062' + '\061', 8), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110001) + chr(0b110101) + chr(522 - 468), 45230 - 45222), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\062' + '\x36', 8), ehT0Px3KOsy9(chr(0b110000) + chr(6772 - 6661) + chr(0b11101 + 0o24) + chr(0b10011 + 0o40) + '\x35', 0o10), ehT0Px3KOsy9(chr(0b1 + 0o57) + chr(111) + '\061' + '\x32' + chr(0b100111 + 0o13), 0b1000), ehT0Px3KOsy9(chr(935 - 887) + '\157' + chr(2298 - 2248) + chr(587 - 534) + chr(523 - 473), 8), ehT0Px3KOsy9(chr(1139 - 1091) + chr(3380 - 3269) + chr(0b110001) + chr(0b101110 + 0o4), 0b1000), ehT0Px3KOsy9(chr(0b11000 + 0o30) + chr(111) + '\061' + chr(49) + '\063', 30846 - 30838)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b101 + 0o53) + chr(10386 - 10275) + chr(53) + chr(0b110000), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'K'), '\144' + chr(3297 - 3196) + chr(0b100010 + 0o101) + chr(0b11100 + 0o123) + '\x64' + chr(0b1100101))('\165' + chr(326 - 210) + chr(6696 - 6594) + chr(899 - 854) + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def SSZUcObFZuSr(AjrnLNzw5Jx9):
deTKmlCBZ4cX = YyaZ4tpXu4lf({wmQmyeWBmUpv(XdowRbJKZWL9) for XdowRbJKZWL9 in AjrnLNzw5Jx9})
if YyaZ4tpXu4lf in deTKmlCBZ4cX:
if c2A0yzQpDQB3(deTKmlCBZ4cX) > ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110001), 8):
AjrnLNzw5Jx9 = [EJkE1Nx1bysb(CDQ27PYjPxZQ.try_sort(OeWW0F1dBPRQ)) if not PlSM16l2KDPD(OeWW0F1dBPRQ, EJkE1Nx1bysb) else OeWW0F1dBPRQ for OeWW0F1dBPRQ in AjrnLNzw5Jx9]
xafqLlk3kkUe(deTKmlCBZ4cX, xafqLlk3kkUe(SXOLrMavuUCe(b'\x17\xf4jC\xc6\x07'), chr(0b1100100) + chr(0b110110 + 0o57) + chr(0b1100011) + '\x6f' + chr(100) + chr(0b1100101))('\x75' + chr(7338 - 7222) + chr(0b1100000 + 0o6) + chr(0b11000 + 0o25) + '\x38'))(YyaZ4tpXu4lf)
else:
return (AjrnLNzw5Jx9, xafqLlk3kkUe(SXOLrMavuUCe(b'\t\xf8tX'), chr(0b1011111 + 0o5) + '\x65' + '\x63' + chr(0b110100 + 0o73) + chr(0b1100100) + chr(0b1100101))(chr(0b1011001 + 0o34) + chr(0b1110100) + '\146' + '\x2d' + '\x38'))
if c2A0yzQpDQB3(deTKmlCBZ4cX) > ehT0Px3KOsy9('\060' + '\157' + '\x31', 8) or EJkE1Nx1bysb not in deTKmlCBZ4cX:
return (AjrnLNzw5Jx9, xafqLlk3kkUe(SXOLrMavuUCe(b'\x16\xe1bO\xd9\x03\x11'), chr(0b1100100 + 0o0) + chr(5249 - 5148) + chr(0b1011011 + 0o10) + chr(11698 - 11587) + chr(0b101010 + 0o72) + chr(5043 - 4942))(chr(0b1110101) + chr(8961 - 8845) + '\x66' + chr(842 - 797) + '\070'))
else:
return (AjrnLNzw5Jx9, xafqLlk3kkUe(SXOLrMavuUCe(b'\x04\xe3uM\xc9'), '\x64' + chr(0b1100101) + chr(652 - 553) + '\157' + '\144' + '\145')('\165' + chr(116) + chr(102) + chr(0b101101) + '\070'))
|
pandas-dev/pandas
|
pandas/core/indexes/api.py
|
_get_consensus_names
|
def _get_consensus_names(indexes):
"""
Give a consensus 'names' to indexes.
If there's exactly one non-empty 'names', return this,
otherwise, return empty.
Parameters
----------
indexes : list of Index objects
Returns
-------
list
A list representing the consensus 'names' found.
"""
# find the non-none names, need to tupleify to make
# the set hashable, then reverse on return
consensus_names = {tuple(i.names) for i in indexes
if com._any_not_none(*i.names)}
if len(consensus_names) == 1:
return list(list(consensus_names)[0])
return [None] * indexes[0].nlevels
|
python
|
def _get_consensus_names(indexes):
"""
Give a consensus 'names' to indexes.
If there's exactly one non-empty 'names', return this,
otherwise, return empty.
Parameters
----------
indexes : list of Index objects
Returns
-------
list
A list representing the consensus 'names' found.
"""
# find the non-none names, need to tupleify to make
# the set hashable, then reverse on return
consensus_names = {tuple(i.names) for i in indexes
if com._any_not_none(*i.names)}
if len(consensus_names) == 1:
return list(list(consensus_names)[0])
return [None] * indexes[0].nlevels
|
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"]",
")",
"return",
"[",
"None",
"]",
"*",
"indexes",
"[",
"0",
"]",
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] |
Give a consensus 'names' to indexes.
If there's exactly one non-empty 'names', return this,
otherwise, return empty.
Parameters
----------
indexes : list of Index objects
Returns
-------
list
A list representing the consensus 'names' found.
|
[
"Give",
"a",
"consensus",
"names",
"to",
"indexes",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/indexes/api.py#L243-L266
|
train
|
Returns a list of consensus names for the given indexes.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(48) + '\157' + chr(0b10101 + 0o36) + '\066', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b101110 + 0o101) + chr(0b110011) + '\065' + chr(776 - 722), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110001) + chr(1379 - 1326) + '\066', 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(54) + '\x33', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(51) + '\061' + '\x30', 9751 - 9743), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\061' + chr(53) + chr(0b110010 + 0o2), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + '\063' + chr(54) + chr(0b110111), 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110000 + 0o2) + chr(54) + chr(0b11011 + 0o32), 5345 - 5337), ehT0Px3KOsy9(chr(48) + '\157' + '\x33' + '\x31' + chr(997 - 942), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110001) + chr(0b110100) + chr(906 - 855), 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(50) + chr(48) + chr(1693 - 1643), ord("\x08")), ehT0Px3KOsy9(chr(1968 - 1920) + '\x6f' + chr(0b10110 + 0o35) + chr(49) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(0b11001 + 0o27) + '\x6f' + chr(0b11110 + 0o25) + '\x32', 0o10), ehT0Px3KOsy9(chr(2184 - 2136) + chr(111) + chr(49) + chr(2090 - 2039) + '\x31', 1616 - 1608), ehT0Px3KOsy9('\x30' + '\x6f' + chr(2647 - 2592) + chr(49), 31152 - 31144), ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(0b110100 + 0o73) + '\x32' + chr(51) + chr(0b110110), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(49) + chr(1310 - 1261) + chr(1072 - 1019), 47963 - 47955), ehT0Px3KOsy9(chr(1221 - 1173) + chr(287 - 176) + chr(0b10100 + 0o37) + '\063' + chr(0b110110), 18202 - 18194), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\062' + chr(0b1101 + 0o45) + chr(0b110101), 0b1000), ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(0b1000 + 0o147) + chr(2520 - 2469) + '\064', 28986 - 28978), ehT0Px3KOsy9('\060' + '\x6f' + chr(1726 - 1676) + chr(0b10010 + 0o44) + '\065', 8), ehT0Px3KOsy9('\x30' + '\157' + chr(0b101 + 0o55) + chr(0b11010 + 0o26) + chr(2303 - 2251), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(0b110001) + chr(473 - 421) + chr(0b110101), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + '\x33' + chr(0b110011) + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(673 - 625) + chr(0b1101111) + chr(579 - 528) + chr(0b110111) + '\066', 0b1000), ehT0Px3KOsy9('\060' + chr(0b101100 + 0o103) + chr(49) + chr(2051 - 1996) + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(661 - 613) + chr(0b1101111) + chr(0b110010) + chr(0b110110), 0o10), ehT0Px3KOsy9(chr(1777 - 1729) + '\157' + chr(0b110101) + chr(54), 0b1000), ehT0Px3KOsy9(chr(0b100100 + 0o14) + chr(0b111101 + 0o62) + chr(50) + chr(51), 0o10), ehT0Px3KOsy9('\x30' + chr(0b100010 + 0o115) + '\063' + chr(1916 - 1868) + '\x35', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110011) + '\065' + chr(0b110000), 28120 - 28112), ehT0Px3KOsy9(chr(0b100110 + 0o12) + '\x6f' + chr(0b110001) + chr(0b110100) + chr(0b110100), 29028 - 29020), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(2033 - 1983) + '\060', 0o10), ehT0Px3KOsy9(chr(750 - 702) + chr(111) + chr(831 - 777) + '\060', 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(1891 - 1842) + chr(0b110111) + '\x36', 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(50) + chr(0b101000 + 0o14) + '\061', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(50) + chr(0b110100) + chr(0b1 + 0o63), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b100111 + 0o14) + '\060' + chr(0b11000 + 0o34), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(176 - 127) + chr(51) + chr(0b100 + 0o63), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(55) + chr(275 - 223), 40418 - 40410)][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + chr(0b111010 + 0o65) + '\x35' + '\x30', 62787 - 62779)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'0'), chr(0b1100100) + chr(101) + chr(99) + '\157' + chr(100) + chr(0b1100101))('\165' + '\164' + chr(3863 - 3761) + '\x2d' + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def znvfqcl2Li30(AjrnLNzw5Jx9):
AwO1_ufKquKM = {KNyTy8rYcwji(WVxHKyX45z_L.OcnR1hZ7pGdr) for WVxHKyX45z_L in AjrnLNzw5Jx9 if CDQ27PYjPxZQ._any_not_none(*WVxHKyX45z_L.OcnR1hZ7pGdr)}
if c2A0yzQpDQB3(AwO1_ufKquKM) == ehT0Px3KOsy9('\x30' + '\157' + chr(49), 37504 - 37496):
return YyaZ4tpXu4lf(YyaZ4tpXu4lf(AwO1_ufKquKM)[ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110000), 0o10)])
return [None] * xafqLlk3kkUe(AjrnLNzw5Jx9[ehT0Px3KOsy9(chr(0b101110 + 0o2) + '\157' + chr(1062 - 1014), 8)], xafqLlk3kkUe(SXOLrMavuUCe(b'p\x82\x0bE\xad\x00\x84'), chr(0b1100100) + chr(0b1100101) + chr(99) + '\x6f' + '\144' + chr(101))('\165' + chr(0b1110100) + chr(0b1100110) + chr(0b10011 + 0o32) + '\x38'))
|
pandas-dev/pandas
|
pandas/core/indexes/api.py
|
_all_indexes_same
|
def _all_indexes_same(indexes):
"""
Determine if all indexes contain the same elements.
Parameters
----------
indexes : list of Index objects
Returns
-------
bool
True if all indexes contain the same elements, False otherwise.
"""
first = indexes[0]
for index in indexes[1:]:
if not first.equals(index):
return False
return True
|
python
|
def _all_indexes_same(indexes):
"""
Determine if all indexes contain the same elements.
Parameters
----------
indexes : list of Index objects
Returns
-------
bool
True if all indexes contain the same elements, False otherwise.
"""
first = indexes[0]
for index in indexes[1:]:
if not first.equals(index):
return False
return True
|
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")",
":",
"first",
"=",
"indexes",
"[",
"0",
"]",
"for",
"index",
"in",
"indexes",
"[",
"1",
":",
"]",
":",
"if",
"not",
"first",
".",
"equals",
"(",
"index",
")",
":",
"return",
"False",
"return",
"True"
] |
Determine if all indexes contain the same elements.
Parameters
----------
indexes : list of Index objects
Returns
-------
bool
True if all indexes contain the same elements, False otherwise.
|
[
"Determine",
"if",
"all",
"indexes",
"contain",
"the",
"same",
"elements",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/indexes/api.py#L269-L286
|
train
|
Determines if all indexes contain the same elements.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(48) + '\157' + chr(0b101111 + 0o3) + '\x33', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(2550 - 2499) + chr(0b110110) + '\x37', 0o10), ehT0Px3KOsy9('\060' + chr(8886 - 8775) + chr(0b101000 + 0o14) + chr(768 - 717), 0b1000), ehT0Px3KOsy9(chr(0b11011 + 0o25) + '\x6f' + chr(2052 - 2003) + '\060' + chr(0b110101), 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(49) + chr(51) + chr(1578 - 1530), 0b1000), ehT0Px3KOsy9(chr(1537 - 1489) + chr(3778 - 3667) + chr(0b110100) + '\x34', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b10 + 0o155) + chr(0b110011) + '\065' + chr(2139 - 2087), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b11 + 0o57) + chr(528 - 478) + chr(53), 6152 - 6144), ehT0Px3KOsy9('\x30' + '\x6f' + chr(1166 - 1116) + chr(49) + chr(0b101100 + 0o5), 0o10), ehT0Px3KOsy9(chr(0b100101 + 0o13) + chr(0b1101111) + chr(51) + '\x36' + '\065', ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110001) + '\x33' + '\061', ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110001 + 0o2) + chr(1900 - 1847) + chr(2682 - 2629), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1010100 + 0o33) + '\061' + chr(2299 - 2250) + '\065', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b110100 + 0o73) + chr(1718 - 1668) + chr(0b110000) + chr(1218 - 1165), ord("\x08")), ehT0Px3KOsy9(chr(1620 - 1572) + chr(7691 - 7580) + chr(1046 - 997) + '\067' + chr(49), 52675 - 52667), ehT0Px3KOsy9('\x30' + chr(0b1011101 + 0o22) + '\061' + chr(0b101111 + 0o7) + '\064', 13346 - 13338), ehT0Px3KOsy9(chr(0b110000) + chr(1869 - 1758) + '\063' + chr(766 - 718) + '\x33', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(4488 - 4377) + chr(0b110001) + chr(1081 - 1031) + chr(0b10 + 0o65), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b101001 + 0o106) + chr(0b110011) + chr(543 - 494) + '\x33', 59987 - 59979), ehT0Px3KOsy9(chr(0b110000 + 0o0) + '\157' + chr(54) + chr(49), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b100010 + 0o21) + '\063' + '\065', ord("\x08")), ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(111) + chr(2378 - 2329) + '\x30' + chr(2250 - 2201), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110001) + chr(0b110100) + '\060', ord("\x08")), ehT0Px3KOsy9(chr(1552 - 1504) + chr(2728 - 2617) + chr(0b100001 + 0o21) + chr(51) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1011000 + 0o27) + '\061' + chr(0b1000 + 0o52) + '\x37', 8), ehT0Px3KOsy9(chr(2037 - 1989) + chr(9699 - 9588) + '\x31' + chr(53) + '\x37', 0b1000), ehT0Px3KOsy9('\060' + chr(111) + '\x31' + chr(0b101000 + 0o10) + chr(0b1010 + 0o47), 8), ehT0Px3KOsy9('\x30' + chr(0b1010 + 0o145) + '\063' + chr(0b101 + 0o60) + chr(740 - 691), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(50) + '\067' + chr(2602 - 2547), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110 + 0o53) + chr(1076 - 1022), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(0b11001 + 0o35) + chr(0b100100 + 0o22), 0o10), ehT0Px3KOsy9('\x30' + chr(0b11111 + 0o120) + chr(238 - 189) + chr(0b10101 + 0o40) + '\065', 0o10), ehT0Px3KOsy9('\x30' + chr(0b100 + 0o153) + chr(158 - 103), 13693 - 13685), ehT0Px3KOsy9(chr(0b110000) + chr(8070 - 7959) + chr(575 - 520) + chr(0b110110), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110001) + chr(1402 - 1353) + '\067', 0o10), ehT0Px3KOsy9('\060' + chr(0b1000111 + 0o50) + '\x32' + chr(0b110001) + '\x37', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\063' + chr(0b110001) + chr(2224 - 2176), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\063' + chr(0b11101 + 0o24) + chr(2257 - 2205), 57815 - 57807), ehT0Px3KOsy9('\060' + chr(0b111001 + 0o66) + chr(51) + chr(0b110000) + chr(0b11010 + 0o34), 0o10), ehT0Px3KOsy9(chr(0b11001 + 0o27) + '\x6f' + '\062' + chr(662 - 614), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b10010 + 0o43) + chr(0b11000 + 0o30), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'='), chr(0b1100 + 0o130) + chr(101) + chr(0b1100011) + chr(0b110110 + 0o71) + chr(0b1100100) + '\x65')(chr(117) + chr(116) + '\146' + chr(45) + chr(0b110110 + 0o2)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def ATmrh0suWvUi(AjrnLNzw5Jx9):
It1LJs8swHZQ = AjrnLNzw5Jx9[ehT0Px3KOsy9(chr(0b100111 + 0o11) + chr(0b1000011 + 0o54) + '\x30', 9117 - 9109)]
for XdowRbJKZWL9 in AjrnLNzw5Jx9[ehT0Px3KOsy9('\060' + '\x6f' + '\061', ord("\x08")):]:
if not xafqLlk3kkUe(It1LJs8swHZQ, xafqLlk3kkUe(SXOLrMavuUCe(b'v\x86V$4W'), chr(0b11110 + 0o106) + '\x65' + '\143' + chr(0b101001 + 0o106) + chr(0b110 + 0o136) + chr(5487 - 5386))(chr(117) + chr(10610 - 10494) + chr(102) + chr(0b1010 + 0o43) + '\x38'))(XdowRbJKZWL9):
return ehT0Px3KOsy9(chr(0b110000) + chr(0b1000000 + 0o57) + '\060', 8)
return ehT0Px3KOsy9(chr(0b110000) + chr(0b110110 + 0o71) + chr(0b110001), 8)
|
pandas-dev/pandas
|
pandas/io/sql.py
|
_convert_params
|
def _convert_params(sql, params):
"""Convert SQL and params args to DBAPI2.0 compliant format."""
args = [sql]
if params is not None:
if hasattr(params, 'keys'): # test if params is a mapping
args += [params]
else:
args += [list(params)]
return args
|
python
|
def _convert_params(sql, params):
"""Convert SQL and params args to DBAPI2.0 compliant format."""
args = [sql]
if params is not None:
if hasattr(params, 'keys'): # test if params is a mapping
args += [params]
else:
args += [list(params)]
return args
|
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] |
Convert SQL and params args to DBAPI2.0 compliant format.
|
[
"Convert",
"SQL",
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"params",
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] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/io/sql.py#L57-L65
|
train
|
Convert SQL and params args to DBAPI2. 0 compliant format.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + '\157' + chr(0b110001 + 0o4) + chr(0b110101), 0b1000), ehT0Px3KOsy9(chr(997 - 949) + chr(5922 - 5811) + chr(0b10011 + 0o36) + chr(0b11000 + 0o33) + '\067', 0o10), ehT0Px3KOsy9(chr(1454 - 1406) + chr(2893 - 2782) + chr(0b110001) + '\x30' + chr(0b11001 + 0o32), 46584 - 46576), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(50) + chr(0b110001) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b10001 + 0o136) + chr(50) + chr(1249 - 1198) + chr(0b11101 + 0o27), 56765 - 56757), ehT0Px3KOsy9(chr(331 - 283) + chr(111) + chr(51) + chr(0b101101 + 0o12) + chr(0b110100), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b100010 + 0o115) + '\x33' + chr(50) + chr(0b11000 + 0o30), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110011) + chr(1728 - 1680) + chr(53), 16553 - 16545), ehT0Px3KOsy9(chr(445 - 397) + chr(8611 - 8500) + '\x31' + '\062', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110010) + chr(0b10000 + 0o43) + chr(55), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(3548 - 3437) + chr(0b110001) + '\062' + '\062', 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110011) + '\061' + chr(51), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x33' + '\062' + chr(204 - 151), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b100000 + 0o117) + '\x31' + '\x32' + chr(0b110010), 8), ehT0Px3KOsy9('\x30' + '\157' + '\062', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(4053 - 3942) + chr(54) + '\x37', 61947 - 61939), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\062' + chr(0b110011), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1001 + 0o146) + chr(815 - 765) + chr(2356 - 2305) + chr(930 - 877), 0o10), ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(0b1101111) + chr(293 - 243) + chr(270 - 216) + '\x35', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b1 + 0o63) + chr(0b100011 + 0o17), 38942 - 38934), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110010) + chr(1289 - 1240) + chr(0b101111 + 0o3), 8), ehT0Px3KOsy9('\060' + chr(0b1000 + 0o147) + '\061' + chr(0b1 + 0o60), 0o10), ehT0Px3KOsy9(chr(1113 - 1065) + '\157' + chr(0b101 + 0o60) + chr(48), 0o10), ehT0Px3KOsy9(chr(0b10110 + 0o32) + '\x6f' + '\x32' + chr(0b110101) + chr(48), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1010101 + 0o32) + '\067' + chr(285 - 237), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + '\x32' + chr(794 - 746) + '\065', 9473 - 9465), ehT0Px3KOsy9(chr(227 - 179) + '\x6f' + '\067' + chr(0b110101), 0b1000), ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(0b1101111) + '\x32' + '\065' + chr(0b11 + 0o57), ord("\x08")), ehT0Px3KOsy9(chr(0b0 + 0o60) + chr(7370 - 7259) + '\x33' + '\x34' + chr(1608 - 1554), ord("\x08")), ehT0Px3KOsy9(chr(0b11110 + 0o22) + chr(111) + chr(0b110 + 0o55) + chr(0b110010) + chr(0b101111 + 0o2), 52325 - 52317), ehT0Px3KOsy9(chr(0b110000) + chr(0b1110 + 0o141) + chr(0b110001) + chr(54), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110001) + '\x32' + chr(48), 58028 - 58020), ehT0Px3KOsy9('\x30' + '\x6f' + '\x31' + chr(1258 - 1203) + '\x34', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(12082 - 11971) + chr(0b101000 + 0o12) + chr(1798 - 1746) + '\062', 0b1000), ehT0Px3KOsy9('\060' + chr(0b11000 + 0o127) + chr(0b110001) + '\x34' + chr(103 - 53), 6472 - 6464), ehT0Px3KOsy9(chr(0b100010 + 0o16) + chr(0b1101111 + 0o0) + '\061' + '\x32' + chr(0b1010 + 0o51), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(3784 - 3673) + chr(0b110100) + chr(1483 - 1435), 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(0b101010 + 0o7) + chr(54) + '\063', 0b1000), ehT0Px3KOsy9(chr(1143 - 1095) + '\x6f' + chr(0b11 + 0o63) + chr(0b101000 + 0o11), ord("\x08")), ehT0Px3KOsy9(chr(0b1111 + 0o41) + chr(0b1101111) + chr(0b110011) + '\x34' + chr(0b110001), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b1110 + 0o42) + chr(111) + chr(53) + chr(0b110000), 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x03'), chr(0b100111 + 0o75) + chr(0b1100101) + '\x63' + chr(0b1101111) + '\x64' + '\145')(chr(117) + chr(0b1100001 + 0o23) + chr(0b1100110) + chr(0b1010 + 0o43) + chr(0b10 + 0o66)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def Q7IKiRWSu9En(GWXd4kBaViZK, nEbJZ4wfte2w):
kJDRfRhcZHjS = [GWXd4kBaViZK]
if nEbJZ4wfte2w is not None:
if lot1PSoAwYhj(nEbJZ4wfte2w, xafqLlk3kkUe(SXOLrMavuUCe(b'F::\xf9'), '\144' + chr(0b110101 + 0o60) + chr(812 - 713) + chr(0b1111 + 0o140) + chr(0b1100100) + '\145')(chr(117) + chr(0b101000 + 0o114) + '\x66' + '\x2d' + chr(2942 - 2886))):
kJDRfRhcZHjS += [nEbJZ4wfte2w]
else:
kJDRfRhcZHjS += [YyaZ4tpXu4lf(nEbJZ4wfte2w)]
return kJDRfRhcZHjS
|
pandas-dev/pandas
|
pandas/io/sql.py
|
_process_parse_dates_argument
|
def _process_parse_dates_argument(parse_dates):
"""Process parse_dates argument for read_sql functions"""
# handle non-list entries for parse_dates gracefully
if parse_dates is True or parse_dates is None or parse_dates is False:
parse_dates = []
elif not hasattr(parse_dates, '__iter__'):
parse_dates = [parse_dates]
return parse_dates
|
python
|
def _process_parse_dates_argument(parse_dates):
"""Process parse_dates argument for read_sql functions"""
# handle non-list entries for parse_dates gracefully
if parse_dates is True or parse_dates is None or parse_dates is False:
parse_dates = []
elif not hasattr(parse_dates, '__iter__'):
parse_dates = [parse_dates]
return parse_dates
|
[
"def",
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"(",
"parse_dates",
")",
":",
"# handle non-list entries for parse_dates gracefully",
"if",
"parse_dates",
"is",
"True",
"or",
"parse_dates",
"is",
"None",
"or",
"parse_dates",
"is",
"False",
":",
"parse_dates",
"=",
"[",
"]",
"elif",
"not",
"hasattr",
"(",
"parse_dates",
",",
"'__iter__'",
")",
":",
"parse_dates",
"=",
"[",
"parse_dates",
"]",
"return",
"parse_dates"
] |
Process parse_dates argument for read_sql functions
|
[
"Process",
"parse_dates",
"argument",
"for",
"read_sql",
"functions"
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/io/sql.py#L68-L76
|
train
|
Process parse_dates argument for read_sql functions.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(437 - 389) + chr(111) + chr(84 - 34) + '\x35' + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(6017 - 5906) + chr(50) + '\062' + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x33' + chr(48) + chr(0b110100), 0o10), ehT0Px3KOsy9(chr(0b0 + 0o60) + chr(0b11101 + 0o122) + chr(0b10001 + 0o40) + chr(0b110100) + chr(230 - 178), 62365 - 62357), ehT0Px3KOsy9(chr(0b101 + 0o53) + '\157' + chr(50) + '\063' + chr(50), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\063' + chr(51) + chr(49), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(50) + '\x35' + chr(54), 30510 - 30502), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110110 + 0o0) + chr(49), 43446 - 43438), ehT0Px3KOsy9(chr(0b111 + 0o51) + '\157' + '\061' + chr(0b110001) + '\064', 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(417 - 364) + chr(0b100010 + 0o25), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + '\x33' + chr(0b11011 + 0o33) + '\060', 0o10), ehT0Px3KOsy9(chr(0b1011 + 0o45) + chr(0b1101111) + '\x31' + chr(460 - 412) + chr(0b1101 + 0o45), ord("\x08")), ehT0Px3KOsy9(chr(2032 - 1984) + chr(2216 - 2105) + chr(0b100001 + 0o20) + chr(52) + chr(0b110111), 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110010) + chr(0b100110 + 0o13) + '\065', 0o10), ehT0Px3KOsy9(chr(1658 - 1610) + chr(0b1101111) + chr(2170 - 2119) + '\x36' + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(505 - 457) + chr(0b1101010 + 0o5) + chr(0b110001) + '\x35' + chr(0b110111), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(1716 - 1668) + chr(10805 - 10694) + chr(0b100 + 0o55) + '\x31' + chr(55), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1011110 + 0o21) + '\061' + chr(50) + chr(318 - 269), 10679 - 10671), ehT0Px3KOsy9(chr(0b110000) + chr(0b1001011 + 0o44) + '\062' + chr(0b1011 + 0o45) + '\063', 0o10), ehT0Px3KOsy9(chr(1935 - 1887) + '\157' + chr(1351 - 1300) + '\067' + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(2056 - 2008) + chr(0b1101111) + chr(2480 - 2430) + '\064' + chr(1878 - 1828), 0o10), ehT0Px3KOsy9('\060' + '\157' + '\061' + '\x34' + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(49) + chr(50) + chr(50), 29564 - 29556), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110001) + chr(0b110011) + chr(0b100011 + 0o21), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101101 + 0o2) + chr(0b1000 + 0o52) + chr(0b110011) + '\x36', 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110010 + 0o5), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b101010 + 0o7) + '\x35' + '\060', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101010 + 0o5) + chr(0b110 + 0o54) + chr(54), 4738 - 4730), ehT0Px3KOsy9(chr(48) + chr(111) + chr(51), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\063' + chr(0b110100) + '\060', 5767 - 5759), ehT0Px3KOsy9('\060' + chr(111) + chr(1137 - 1087) + '\061' + chr(51), 0b1000), ehT0Px3KOsy9(chr(1822 - 1774) + chr(0b1011011 + 0o24) + '\x32' + '\x35' + chr(48), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(3294 - 3183) + chr(97 - 45) + '\x36', 0b1000), ehT0Px3KOsy9(chr(48) + chr(8655 - 8544) + chr(0b110001) + chr(50) + chr(0b110011), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b101111 + 0o100) + chr(0b110001) + chr(0b110111) + '\065', 14316 - 14308), ehT0Px3KOsy9('\x30' + chr(0b11111 + 0o120) + chr(0b10100 + 0o36) + chr(2786 - 2733) + chr(50), 55130 - 55122), ehT0Px3KOsy9(chr(0b110000) + chr(8221 - 8110) + chr(0b110001) + chr(997 - 948) + '\060', 49509 - 49501), ehT0Px3KOsy9('\060' + chr(0b11000 + 0o127) + '\065' + '\x37', 8), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(49) + '\x34', 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110100 + 0o1) + chr(0b11000 + 0o30), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x85'), chr(2338 - 2238) + '\x65' + chr(0b1100011) + chr(111) + '\144' + chr(101))(chr(117) + chr(0b1110100) + chr(0b1100110) + '\055' + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def Vdob_8esVEbU(T1brfYV34pPD):
if T1brfYV34pPD is ehT0Px3KOsy9('\060' + '\x6f' + chr(0b100101 + 0o14), 0o10) or T1brfYV34pPD is None or T1brfYV34pPD is ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110000), 0b1000):
T1brfYV34pPD = []
elif not lot1PSoAwYhj(T1brfYV34pPD, xafqLlk3kkUe(SXOLrMavuUCe(b'\xf4\xcc\xad\x10\xff\xab\xf1n'), chr(0b1100100) + chr(0b110011 + 0o62) + chr(99) + chr(3636 - 3525) + chr(0b101100 + 0o70) + chr(101))(chr(5125 - 5008) + '\164' + chr(0b1010000 + 0o26) + chr(0b101101) + '\070')):
T1brfYV34pPD = [T1brfYV34pPD]
return T1brfYV34pPD
|
pandas-dev/pandas
|
pandas/io/sql.py
|
_parse_date_columns
|
def _parse_date_columns(data_frame, parse_dates):
"""
Force non-datetime columns to be read as such.
Supports both string formatted and integer timestamp columns.
"""
parse_dates = _process_parse_dates_argument(parse_dates)
# we want to coerce datetime64_tz dtypes for now to UTC
# we could in theory do a 'nice' conversion from a FixedOffset tz
# GH11216
for col_name, df_col in data_frame.iteritems():
if is_datetime64tz_dtype(df_col) or col_name in parse_dates:
try:
fmt = parse_dates[col_name]
except TypeError:
fmt = None
data_frame[col_name] = _handle_date_column(df_col, format=fmt)
return data_frame
|
python
|
def _parse_date_columns(data_frame, parse_dates):
"""
Force non-datetime columns to be read as such.
Supports both string formatted and integer timestamp columns.
"""
parse_dates = _process_parse_dates_argument(parse_dates)
# we want to coerce datetime64_tz dtypes for now to UTC
# we could in theory do a 'nice' conversion from a FixedOffset tz
# GH11216
for col_name, df_col in data_frame.iteritems():
if is_datetime64tz_dtype(df_col) or col_name in parse_dates:
try:
fmt = parse_dates[col_name]
except TypeError:
fmt = None
data_frame[col_name] = _handle_date_column(df_col, format=fmt)
return data_frame
|
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] |
Force non-datetime columns to be read as such.
Supports both string formatted and integer timestamp columns.
|
[
"Force",
"non",
"-",
"datetime",
"columns",
"to",
"be",
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"as",
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".",
"Supports",
"both",
"string",
"formatted",
"and",
"integer",
"timestamp",
"columns",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/io/sql.py#L98-L116
|
train
|
Convert datetime columns to datetime columns.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b110000) + chr(670 - 559) + '\x32' + chr(0b10001 + 0o43), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(51) + '\x34' + '\x37', ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(1480 - 1431) + chr(53) + chr(1838 - 1789), 5396 - 5388), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110011) + chr(320 - 267) + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(0b1000 + 0o50) + chr(0b1101111) + '\066' + chr(629 - 580), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + '\x31' + '\x30' + '\x30', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110010) + chr(0b10100 + 0o43) + '\x37', 56026 - 56018), ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(111) + '\x31' + chr(0b0 + 0o63) + '\064', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(3343 - 3232) + '\x31' + '\062' + chr(0b101110 + 0o7), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + '\063' + chr(0b110001), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(51) + chr(1312 - 1257) + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1011111 + 0o20) + chr(0b110001) + '\x30' + '\x37', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(4611 - 4500) + chr(0b110010) + chr(932 - 881) + chr(2547 - 2493), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(53) + chr(49), 24712 - 24704), ehT0Px3KOsy9(chr(0b11000 + 0o30) + chr(10997 - 10886) + '\061' + chr(2201 - 2153) + '\062', 51523 - 51515), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(51) + chr(0b110010) + chr(1826 - 1772), ord("\x08")), ehT0Px3KOsy9(chr(2183 - 2135) + '\157' + chr(0b110110) + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(0b100011 + 0o15) + '\x6f' + chr(0b101011 + 0o10) + chr(1011 - 963) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(0b110 + 0o52) + chr(111) + chr(920 - 871) + '\x33' + '\066', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x31' + chr(0b100010 + 0o17) + chr(0b110100), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(180 - 131) + '\x36' + '\x30', 0b1000), ehT0Px3KOsy9(chr(612 - 564) + chr(0b1101111) + '\x32' + chr(0b110100 + 0o1) + chr(1413 - 1358), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(306 - 257) + chr(0b1010 + 0o51) + '\x33', 0b1000), ehT0Px3KOsy9(chr(516 - 468) + '\157' + chr(50) + '\x31' + chr(2304 - 2253), ord("\x08")), ehT0Px3KOsy9(chr(1721 - 1673) + chr(111) + '\062' + '\x33' + '\060', 0b1000), ehT0Px3KOsy9(chr(1335 - 1287) + chr(5810 - 5699) + chr(0b110011) + chr(50), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(49) + chr(52) + '\062', 47943 - 47935), ehT0Px3KOsy9('\060' + chr(5793 - 5682) + chr(2209 - 2158) + chr(50) + chr(0b110100), ord("\x08")), ehT0Px3KOsy9('\060' + chr(1344 - 1233) + '\063' + chr(0b101110 + 0o7) + chr(1773 - 1724), 8), ehT0Px3KOsy9(chr(0b100111 + 0o11) + chr(0b10110 + 0o131) + chr(2338 - 2288) + chr(50) + '\x31', 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\061' + chr(0b110001) + '\064', 8), ehT0Px3KOsy9('\060' + chr(0b10011 + 0o134) + chr(54) + chr(262 - 210), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\062' + chr(51) + chr(53), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110011) + '\065' + '\065', 59762 - 59754), ehT0Px3KOsy9('\060' + '\x6f' + chr(2587 - 2536) + chr(0b101000 + 0o12) + '\x31', 19087 - 19079), ehT0Px3KOsy9(chr(0b110000 + 0o0) + chr(3133 - 3022) + '\066' + chr(56 - 7), 8), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b10100 + 0o36) + chr(0b110110) + chr(0b1011 + 0o53), 35461 - 35453), ehT0Px3KOsy9(chr(1272 - 1224) + chr(0b1101111) + chr(0b1110 + 0o45) + chr(0b110001) + '\065', ord("\x08")), ehT0Px3KOsy9(chr(2120 - 2072) + chr(0b1101111) + chr(0b110011) + chr(49) + chr(155 - 101), ord("\x08")), ehT0Px3KOsy9('\060' + chr(3392 - 3281) + chr(0b110011) + chr(53) + chr(0b100101 + 0o20), 8)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(1859 - 1811) + chr(8500 - 8389) + '\x35' + chr(48), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b':'), '\144' + chr(0b100000 + 0o105) + chr(3729 - 3630) + '\x6f' + chr(100) + chr(0b1100101))(chr(13147 - 13030) + chr(0b100110 + 0o116) + chr(102) + chr(45) + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def uaSIiXgQwR6N(LjRoUgiSNWXh, T1brfYV34pPD):
T1brfYV34pPD = Vdob_8esVEbU(T1brfYV34pPD)
for (W93rymQCbozJ, lhzRzl6zabVS) in xafqLlk3kkUe(LjRoUgiSNWXh, xafqLlk3kkUe(SXOLrMavuUCe(b'}\x93\x0c\x9bX4\xda1&'), chr(0b1100100) + chr(5366 - 5265) + chr(0b1100011) + chr(111) + chr(100) + '\145')(chr(0b1110101) + chr(1376 - 1260) + chr(3118 - 3016) + chr(0b101101) + chr(56)))():
if WU585kKowDKQ(lhzRzl6zabVS) or W93rymQCbozJ in T1brfYV34pPD:
try:
EwDuvMM18jq4 = T1brfYV34pPD[W93rymQCbozJ]
except sznFqDbNBHlx:
EwDuvMM18jq4 = None
LjRoUgiSNWXh[W93rymQCbozJ] = XJ3YiAnKRkOa(lhzRzl6zabVS, format=EwDuvMM18jq4)
return LjRoUgiSNWXh
|
pandas-dev/pandas
|
pandas/io/sql.py
|
_wrap_result
|
def _wrap_result(data, columns, index_col=None, coerce_float=True,
parse_dates=None):
"""Wrap result set of query in a DataFrame."""
frame = DataFrame.from_records(data, columns=columns,
coerce_float=coerce_float)
frame = _parse_date_columns(frame, parse_dates)
if index_col is not None:
frame.set_index(index_col, inplace=True)
return frame
|
python
|
def _wrap_result(data, columns, index_col=None, coerce_float=True,
parse_dates=None):
"""Wrap result set of query in a DataFrame."""
frame = DataFrame.from_records(data, columns=columns,
coerce_float=coerce_float)
frame = _parse_date_columns(frame, parse_dates)
if index_col is not None:
frame.set_index(index_col, inplace=True)
return frame
|
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"parse_dates",
"=",
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")",
":",
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"=",
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"(",
"data",
",",
"columns",
"=",
"columns",
",",
"coerce_float",
"=",
"coerce_float",
")",
"frame",
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"_parse_date_columns",
"(",
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",",
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")",
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":",
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".",
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"(",
"index_col",
",",
"inplace",
"=",
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")",
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"frame"
] |
Wrap result set of query in a DataFrame.
|
[
"Wrap",
"result",
"set",
"of",
"query",
"in",
"a",
"DataFrame",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/io/sql.py#L119-L131
|
train
|
Wrap result set of query in a DataFrame.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b100000 + 0o20) + chr(0b1101111) + '\063' + chr(0b110111) + chr(0b101 + 0o53), 31517 - 31509), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110001) + chr(0b10 + 0o63) + chr(0b110001), 7393 - 7385), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110010) + '\x31', 23799 - 23791), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\061' + chr(1085 - 1032) + '\x31', 8), ehT0Px3KOsy9(chr(48) + chr(0b1011111 + 0o20) + chr(0b110011) + chr(0b110000) + chr(294 - 245), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1010011 + 0o34) + chr(49) + chr(1104 - 1051) + chr(50), 0o10), ehT0Px3KOsy9(chr(636 - 588) + '\x6f' + chr(830 - 776) + '\061', 0o10), ehT0Px3KOsy9(chr(48) + chr(12228 - 12117) + chr(691 - 642) + '\x31', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110001 + 0o0) + '\064' + '\x35', 0b1000), ehT0Px3KOsy9(chr(1090 - 1042) + '\157' + chr(0b10 + 0o61) + '\062' + '\063', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x31', 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b100110 + 0o13) + chr(2324 - 2269) + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(172 - 124) + chr(0b110001 + 0o76) + '\x36' + '\066', 19621 - 19613), ehT0Px3KOsy9(chr(48) + chr(111) + '\x33' + chr(53), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(677 - 628) + chr(0b110000) + chr(49), 0o10), ehT0Px3KOsy9(chr(48) + chr(8031 - 7920) + '\061' + chr(51) + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(1131 - 1083) + '\157' + chr(0b1100 + 0o46) + chr(0b11010 + 0o31), ord("\x08")), ehT0Px3KOsy9(chr(1965 - 1917) + chr(4266 - 4155) + chr(51) + chr(50) + chr(0b110110), 0b1000), ehT0Px3KOsy9(chr(2079 - 2031) + '\157' + chr(0b110011) + '\x30' + '\062', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(6348 - 6237) + chr(50) + chr(0b10110 + 0o32) + chr(52), 60978 - 60970), ehT0Px3KOsy9(chr(48) + chr(111) + chr(733 - 682) + chr(0b110011) + chr(979 - 924), 30213 - 30205), ehT0Px3KOsy9(chr(48) + '\157' + '\x31' + chr(52) + chr(0b110100), ord("\x08")), ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(0b1101111) + '\x33' + '\x33', 0b1000), ehT0Px3KOsy9(chr(1080 - 1032) + chr(0b1101111) + chr(0b110011) + chr(0b101110 + 0o5) + chr(1850 - 1795), 8), ehT0Px3KOsy9(chr(2020 - 1972) + chr(0b1101111) + chr(49) + chr(0b100011 + 0o24) + chr(1214 - 1161), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + '\062' + chr(0b1001 + 0o56) + chr(2041 - 1991), 50138 - 50130), ehT0Px3KOsy9(chr(2252 - 2204) + chr(111) + '\061' + chr(53) + chr(0b11010 + 0o35), 0o10), ehT0Px3KOsy9('\060' + chr(0b11 + 0o154) + '\x33' + '\x33' + '\x36', 0b1000), ehT0Px3KOsy9(chr(0b1100 + 0o44) + chr(0b10111 + 0o130) + chr(0b100100 + 0o15) + chr(0b11011 + 0o34) + chr(814 - 765), 24301 - 24293), ehT0Px3KOsy9(chr(266 - 218) + chr(0b11000 + 0o127) + chr(0b11101 + 0o26) + '\x37' + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(1990 - 1942) + chr(8259 - 8148) + chr(1880 - 1829) + chr(0b110110), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(0b1010 + 0o50) + '\063' + '\063', ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(191 - 141) + chr(300 - 250) + chr(229 - 177), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110010) + chr(1527 - 1475) + chr(2065 - 2016), 0b1000), ehT0Px3KOsy9('\060' + chr(9853 - 9742) + '\061' + chr(52) + '\064', 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b1100010 + 0o15) + chr(0b110001) + chr(0b110010) + '\062', 0b1000), ehT0Px3KOsy9(chr(0b10111 + 0o31) + chr(111) + '\062' + chr(0b100111 + 0o16) + chr(2246 - 2197), 0o10), ehT0Px3KOsy9(chr(0b101100 + 0o4) + '\x6f' + chr(0b1 + 0o62) + chr(0b110100) + chr(2160 - 2110), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(51) + chr(52), 0o10), ehT0Px3KOsy9('\060' + chr(0b1011110 + 0o21) + chr(1162 - 1111) + chr(0b110000 + 0o3) + '\x33', ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b100001 + 0o17) + chr(0b110100 + 0o73) + '\065' + chr(48), 8319 - 8311)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xd6'), chr(100) + chr(9141 - 9040) + chr(8314 - 8215) + '\157' + chr(0b1100100) + chr(0b1100101))(chr(0b1000001 + 0o64) + '\x74' + chr(0b1100110) + chr(657 - 612) + chr(1254 - 1198)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def jDdYdl3hJF1x(ULnjp6D6efFH, qKlXBtn3PKy4, o90TMYhFhMm_=None, hyGdBsLYkQVS=ehT0Px3KOsy9(chr(48) + chr(0b101000 + 0o107) + '\x31', 8), T1brfYV34pPD=None):
C4IqNNmLfHXB = TTWbaLX2VikC.from_records(ULnjp6D6efFH, columns=qKlXBtn3PKy4, coerce_float=hyGdBsLYkQVS)
C4IqNNmLfHXB = uaSIiXgQwR6N(C4IqNNmLfHXB, T1brfYV34pPD)
if o90TMYhFhMm_ is not None:
xafqLlk3kkUe(C4IqNNmLfHXB, xafqLlk3kkUe(SXOLrMavuUCe(b'\x8b\x0ce6\xa8\x04Ul\x1d'), '\144' + chr(1813 - 1712) + chr(0b101101 + 0o66) + '\157' + chr(2975 - 2875) + '\x65')('\165' + '\164' + chr(102) + chr(0b11010 + 0o23) + chr(0b111000)))(o90TMYhFhMm_, inplace=ehT0Px3KOsy9(chr(0b110000) + chr(1621 - 1510) + chr(0b11 + 0o56), 8))
return C4IqNNmLfHXB
|
pandas-dev/pandas
|
pandas/io/sql.py
|
execute
|
def execute(sql, con, cur=None, params=None):
"""
Execute the given SQL query using the provided connection object.
Parameters
----------
sql : string
SQL query to be executed.
con : SQLAlchemy connectable(engine/connection) or sqlite3 connection
Using SQLAlchemy makes it possible to use any DB supported by the
library.
If a DBAPI2 object, only sqlite3 is supported.
cur : deprecated, cursor is obtained from connection, default: None
params : list or tuple, optional, default: None
List of parameters to pass to execute method.
Returns
-------
Results Iterable
"""
if cur is None:
pandas_sql = pandasSQL_builder(con)
else:
pandas_sql = pandasSQL_builder(cur, is_cursor=True)
args = _convert_params(sql, params)
return pandas_sql.execute(*args)
|
python
|
def execute(sql, con, cur=None, params=None):
"""
Execute the given SQL query using the provided connection object.
Parameters
----------
sql : string
SQL query to be executed.
con : SQLAlchemy connectable(engine/connection) or sqlite3 connection
Using SQLAlchemy makes it possible to use any DB supported by the
library.
If a DBAPI2 object, only sqlite3 is supported.
cur : deprecated, cursor is obtained from connection, default: None
params : list or tuple, optional, default: None
List of parameters to pass to execute method.
Returns
-------
Results Iterable
"""
if cur is None:
pandas_sql = pandasSQL_builder(con)
else:
pandas_sql = pandasSQL_builder(cur, is_cursor=True)
args = _convert_params(sql, params)
return pandas_sql.execute(*args)
|
[
"def",
"execute",
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"sql",
",",
"con",
",",
"cur",
"=",
"None",
",",
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":",
"if",
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"None",
":",
"pandas_sql",
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"(",
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"(",
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",",
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"=",
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"_convert_params",
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"sql",
",",
"params",
")",
"return",
"pandas_sql",
".",
"execute",
"(",
"*",
"args",
")"
] |
Execute the given SQL query using the provided connection object.
Parameters
----------
sql : string
SQL query to be executed.
con : SQLAlchemy connectable(engine/connection) or sqlite3 connection
Using SQLAlchemy makes it possible to use any DB supported by the
library.
If a DBAPI2 object, only sqlite3 is supported.
cur : deprecated, cursor is obtained from connection, default: None
params : list or tuple, optional, default: None
List of parameters to pass to execute method.
Returns
-------
Results Iterable
|
[
"Execute",
"the",
"given",
"SQL",
"query",
"using",
"the",
"provided",
"connection",
"object",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/io/sql.py#L134-L159
|
train
|
Execute a SQL query using the provided connection object.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b101 + 0o53) + chr(111) + '\x33' + chr(0b1010 + 0o55) + chr(0b110001), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + '\063' + '\062', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(3550 - 3439) + chr(2429 - 2378) + chr(0b110110 + 0o0) + chr(51), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(49) + chr(53) + '\066', 0b1000), ehT0Px3KOsy9(chr(48) + chr(11760 - 11649) + chr(50) + chr(0b110011) + chr(0b10110 + 0o35), 15766 - 15758), ehT0Px3KOsy9('\060' + chr(597 - 486) + '\062' + chr(0b101101 + 0o11) + '\x36', 0o10), ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(0b1101111) + chr(447 - 397) + chr(743 - 694) + chr(0b110011), 0b1000), ehT0Px3KOsy9(chr(0b11111 + 0o21) + chr(0b1101111) + chr(226 - 177) + '\060' + chr(52), 0o10), ehT0Px3KOsy9('\x30' + chr(6775 - 6664) + '\x31' + '\060' + '\063', 0b1000), ehT0Px3KOsy9(chr(0b1110 + 0o42) + chr(0b1101 + 0o142) + chr(0b110001) + chr(48) + chr(0b110010), 18237 - 18229), ehT0Px3KOsy9('\x30' + '\x6f' + '\063' + chr(911 - 862) + chr(0b110111), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101001 + 0o6) + chr(0b11000 + 0o34) + chr(227 - 172), 0o10), ehT0Px3KOsy9('\060' + chr(5591 - 5480) + chr(1012 - 962) + chr(52) + chr(48), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110 + 0o57) + chr(529 - 480), 0o10), ehT0Px3KOsy9(chr(578 - 530) + '\x6f' + chr(49) + chr(49) + '\x33', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b100110 + 0o15) + chr(490 - 439) + '\067', ord("\x08")), ehT0Px3KOsy9(chr(574 - 526) + chr(0b1101000 + 0o7) + '\063' + chr(0b100101 + 0o17) + chr(1209 - 1156), 45518 - 45510), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b10011 + 0o36) + '\064' + chr(50), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1100001 + 0o16) + chr(51) + chr(820 - 765) + '\067', 0b1000), ehT0Px3KOsy9('\060' + chr(2560 - 2449) + '\063' + chr(0b100110 + 0o14), 8), ehT0Px3KOsy9(chr(0b110000) + chr(11155 - 11044) + '\063' + chr(2085 - 2037) + chr(54), 0o10), ehT0Px3KOsy9(chr(0b10010 + 0o36) + chr(0b1101111) + chr(0b1110 + 0o45) + chr(1881 - 1833), 20888 - 20880), ehT0Px3KOsy9(chr(1043 - 995) + chr(0b1101111) + chr(51) + '\x35' + chr(0b11010 + 0o27), 0b1000), ehT0Px3KOsy9(chr(0b100100 + 0o14) + '\157' + chr(2357 - 2306) + chr(417 - 367) + chr(0b110110), 48990 - 48982), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x31' + chr(0b110101) + chr(0b110010), 0b1000), ehT0Px3KOsy9('\060' + chr(0b0 + 0o157) + chr(51) + chr(55) + '\060', 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + '\065' + chr(51), 64136 - 64128), ehT0Px3KOsy9(chr(0b110000) + chr(0b1100101 + 0o12) + chr(1981 - 1931) + '\x36' + chr(82 - 29), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + '\x31' + '\064' + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(166 - 118) + chr(2754 - 2643) + '\x31' + chr(55) + chr(0b1011 + 0o53), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x31' + chr(53) + '\x36', 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b1100000 + 0o17) + '\x36' + '\065', ord("\x08")), ehT0Px3KOsy9(chr(0b1111 + 0o41) + '\157' + chr(1896 - 1847) + chr(51) + '\x30', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b101001 + 0o10) + '\x32' + '\060', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(51) + chr(48) + chr(2459 - 2408), 27491 - 27483), ehT0Px3KOsy9(chr(861 - 813) + '\x6f' + '\061' + chr(0b110111) + chr(0b11010 + 0o26), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110101) + '\065', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1100110 + 0o11) + '\x32' + chr(50) + '\061', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(49) + chr(0b110010) + chr(48), 8), ehT0Px3KOsy9(chr(1781 - 1733) + chr(4114 - 4003) + chr(0b10111 + 0o34) + '\x34' + chr(0b10011 + 0o40), 21054 - 21046)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + chr(0b1101011 + 0o4) + chr(1209 - 1156) + chr(0b110000), 34091 - 34083)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xd7'), chr(3760 - 3660) + chr(101) + chr(99) + chr(4474 - 4363) + chr(185 - 85) + chr(0b1011011 + 0o12))(chr(5155 - 5038) + '\x74' + chr(7226 - 7124) + chr(0b101101) + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def TaiENS9_ww2W(GWXd4kBaViZK, _sqfVuM76EP3, wL6S4kgnTowq=None, nEbJZ4wfte2w=None):
if wL6S4kgnTowq is None:
Re4ydlckRnKx = Hm7TAp8orHi4(_sqfVuM76EP3)
else:
Re4ydlckRnKx = Hm7TAp8orHi4(wL6S4kgnTowq, is_cursor=ehT0Px3KOsy9(chr(994 - 946) + chr(111) + '\061', 0b1000))
kJDRfRhcZHjS = Q7IKiRWSu9En(GWXd4kBaViZK, nEbJZ4wfte2w)
return xafqLlk3kkUe(Re4ydlckRnKx, xafqLlk3kkUe(SXOLrMavuUCe(b'\x9cb\x96\r\xee\xc2\xee'), chr(0b1001 + 0o133) + '\145' + chr(5468 - 5369) + '\x6f' + '\144' + chr(101))('\165' + chr(116) + '\x66' + '\055' + chr(0b101101 + 0o13)))(*kJDRfRhcZHjS)
|
pandas-dev/pandas
|
pandas/io/sql.py
|
read_sql_table
|
def read_sql_table(table_name, con, schema=None, index_col=None,
coerce_float=True, parse_dates=None, columns=None,
chunksize=None):
"""
Read SQL database table into a DataFrame.
Given a table name and a SQLAlchemy connectable, returns a DataFrame.
This function does not support DBAPI connections.
Parameters
----------
table_name : str
Name of SQL table in database.
con : SQLAlchemy connectable or str
A database URI could be provided as as str.
SQLite DBAPI connection mode not supported.
schema : str, default None
Name of SQL schema in database to query (if database flavor
supports this). Uses default schema if None (default).
index_col : str or list of str, optional, default: None
Column(s) to set as index(MultiIndex).
coerce_float : bool, default True
Attempts to convert values of non-string, non-numeric objects (like
decimal.Decimal) to floating point. Can result in loss of Precision.
parse_dates : list or dict, default None
- List of column names to parse as dates.
- Dict of ``{column_name: format string}`` where format string is
strftime compatible in case of parsing string times or is one of
(D, s, ns, ms, us) in case of parsing integer timestamps.
- Dict of ``{column_name: arg dict}``, where the arg dict corresponds
to the keyword arguments of :func:`pandas.to_datetime`
Especially useful with databases without native Datetime support,
such as SQLite.
columns : list, default None
List of column names to select from SQL table.
chunksize : int, default None
If specified, returns an iterator where `chunksize` is the number of
rows to include in each chunk.
Returns
-------
DataFrame
A SQL table is returned as two-dimensional data structure with labeled
axes.
See Also
--------
read_sql_query : Read SQL query into a DataFrame.
read_sql : Read SQL query or database table into a DataFrame.
Notes
-----
Any datetime values with time zone information will be converted to UTC.
Examples
--------
>>> pd.read_sql_table('table_name', 'postgres:///db_name') # doctest:+SKIP
"""
con = _engine_builder(con)
if not _is_sqlalchemy_connectable(con):
raise NotImplementedError("read_sql_table only supported for "
"SQLAlchemy connectable.")
import sqlalchemy
from sqlalchemy.schema import MetaData
meta = MetaData(con, schema=schema)
try:
meta.reflect(only=[table_name], views=True)
except sqlalchemy.exc.InvalidRequestError:
raise ValueError("Table {name} not found".format(name=table_name))
pandas_sql = SQLDatabase(con, meta=meta)
table = pandas_sql.read_table(
table_name, index_col=index_col, coerce_float=coerce_float,
parse_dates=parse_dates, columns=columns, chunksize=chunksize)
if table is not None:
return table
else:
raise ValueError("Table {name} not found".format(name=table_name), con)
|
python
|
def read_sql_table(table_name, con, schema=None, index_col=None,
coerce_float=True, parse_dates=None, columns=None,
chunksize=None):
"""
Read SQL database table into a DataFrame.
Given a table name and a SQLAlchemy connectable, returns a DataFrame.
This function does not support DBAPI connections.
Parameters
----------
table_name : str
Name of SQL table in database.
con : SQLAlchemy connectable or str
A database URI could be provided as as str.
SQLite DBAPI connection mode not supported.
schema : str, default None
Name of SQL schema in database to query (if database flavor
supports this). Uses default schema if None (default).
index_col : str or list of str, optional, default: None
Column(s) to set as index(MultiIndex).
coerce_float : bool, default True
Attempts to convert values of non-string, non-numeric objects (like
decimal.Decimal) to floating point. Can result in loss of Precision.
parse_dates : list or dict, default None
- List of column names to parse as dates.
- Dict of ``{column_name: format string}`` where format string is
strftime compatible in case of parsing string times or is one of
(D, s, ns, ms, us) in case of parsing integer timestamps.
- Dict of ``{column_name: arg dict}``, where the arg dict corresponds
to the keyword arguments of :func:`pandas.to_datetime`
Especially useful with databases without native Datetime support,
such as SQLite.
columns : list, default None
List of column names to select from SQL table.
chunksize : int, default None
If specified, returns an iterator where `chunksize` is the number of
rows to include in each chunk.
Returns
-------
DataFrame
A SQL table is returned as two-dimensional data structure with labeled
axes.
See Also
--------
read_sql_query : Read SQL query into a DataFrame.
read_sql : Read SQL query or database table into a DataFrame.
Notes
-----
Any datetime values with time zone information will be converted to UTC.
Examples
--------
>>> pd.read_sql_table('table_name', 'postgres:///db_name') # doctest:+SKIP
"""
con = _engine_builder(con)
if not _is_sqlalchemy_connectable(con):
raise NotImplementedError("read_sql_table only supported for "
"SQLAlchemy connectable.")
import sqlalchemy
from sqlalchemy.schema import MetaData
meta = MetaData(con, schema=schema)
try:
meta.reflect(only=[table_name], views=True)
except sqlalchemy.exc.InvalidRequestError:
raise ValueError("Table {name} not found".format(name=table_name))
pandas_sql = SQLDatabase(con, meta=meta)
table = pandas_sql.read_table(
table_name, index_col=index_col, coerce_float=coerce_float,
parse_dates=parse_dates, columns=columns, chunksize=chunksize)
if table is not None:
return table
else:
raise ValueError("Table {name} not found".format(name=table_name), con)
|
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] |
Read SQL database table into a DataFrame.
Given a table name and a SQLAlchemy connectable, returns a DataFrame.
This function does not support DBAPI connections.
Parameters
----------
table_name : str
Name of SQL table in database.
con : SQLAlchemy connectable or str
A database URI could be provided as as str.
SQLite DBAPI connection mode not supported.
schema : str, default None
Name of SQL schema in database to query (if database flavor
supports this). Uses default schema if None (default).
index_col : str or list of str, optional, default: None
Column(s) to set as index(MultiIndex).
coerce_float : bool, default True
Attempts to convert values of non-string, non-numeric objects (like
decimal.Decimal) to floating point. Can result in loss of Precision.
parse_dates : list or dict, default None
- List of column names to parse as dates.
- Dict of ``{column_name: format string}`` where format string is
strftime compatible in case of parsing string times or is one of
(D, s, ns, ms, us) in case of parsing integer timestamps.
- Dict of ``{column_name: arg dict}``, where the arg dict corresponds
to the keyword arguments of :func:`pandas.to_datetime`
Especially useful with databases without native Datetime support,
such as SQLite.
columns : list, default None
List of column names to select from SQL table.
chunksize : int, default None
If specified, returns an iterator where `chunksize` is the number of
rows to include in each chunk.
Returns
-------
DataFrame
A SQL table is returned as two-dimensional data structure with labeled
axes.
See Also
--------
read_sql_query : Read SQL query into a DataFrame.
read_sql : Read SQL query or database table into a DataFrame.
Notes
-----
Any datetime values with time zone information will be converted to UTC.
Examples
--------
>>> pd.read_sql_table('table_name', 'postgres:///db_name') # doctest:+SKIP
|
[
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"DataFrame",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/io/sql.py#L165-L244
|
train
|
Reads a SQL table into a DataFrame.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\x30' + chr(0b101 + 0o152) + chr(0b110010) + chr(1314 - 1266), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\061' + chr(0b110000) + chr(0b1011 + 0o52), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b100011 + 0o114) + '\x33' + chr(2344 - 2289) + '\062', 0b1000), ehT0Px3KOsy9('\060' + chr(0b10101 + 0o132) + '\061' + '\x33' + chr(54), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b101010 + 0o12) + chr(0b110110), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\063' + chr(52) + chr(0b110000 + 0o0), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(1828 - 1777) + '\x33' + chr(1851 - 1798), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(808 - 753), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b110000 + 0o77) + '\063' + chr(0b10001 + 0o42) + '\x32', 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(934 - 880) + chr(0b100010 + 0o22), 61365 - 61357), ehT0Px3KOsy9(chr(0b1101 + 0o43) + chr(0b1100101 + 0o12) + '\062' + chr(0b110011) + '\x31', 0b1000), ehT0Px3KOsy9(chr(671 - 623) + '\157' + chr(50) + chr(558 - 504) + chr(0b0 + 0o66), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x33' + chr(52) + '\x32', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x34' + chr(0b110100), ord("\x08")), ehT0Px3KOsy9(chr(2292 - 2244) + chr(0b100110 + 0o111) + chr(462 - 413) + chr(1722 - 1671) + '\x36', 8), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110001) + chr(0b110011) + chr(0b110000), 56434 - 56426), ehT0Px3KOsy9(chr(48) + chr(111) + chr(352 - 303) + chr(51) + chr(50), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110010 + 0o1) + chr(0b100100 + 0o16) + '\061', 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(0b110001), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + '\063' + '\063' + '\x32', 8), ehT0Px3KOsy9(chr(0b11110 + 0o22) + chr(0b1101111) + chr(0b10100 + 0o36) + chr(0b110001) + chr(2469 - 2418), 61066 - 61058), ehT0Px3KOsy9(chr(48) + chr(2433 - 2322) + chr(0b110000 + 0o6) + chr(0b100001 + 0o23), 8), ehT0Px3KOsy9(chr(0b11100 + 0o24) + chr(0b1101 + 0o142) + chr(0b110011) + '\x32' + chr(55), 48686 - 48678), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\061' + chr(51) + '\060', 8), ehT0Px3KOsy9(chr(48) + chr(111) + chr(1176 - 1127) + chr(51) + chr(48), 8), ehT0Px3KOsy9(chr(0b11111 + 0o21) + '\x6f' + '\x31' + '\062', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110001) + chr(2005 - 1952) + chr(588 - 536), 0b1000), ehT0Px3KOsy9(chr(1957 - 1909) + chr(7503 - 7392) + '\x33' + chr(0b110001) + '\063', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110011) + '\066', 0b1000), ehT0Px3KOsy9(chr(1976 - 1928) + chr(0b111 + 0o150) + chr(51) + chr(0b101011 + 0o10) + '\067', 0b1000), ehT0Px3KOsy9(chr(190 - 142) + chr(1083 - 972) + '\x32' + '\x31' + '\064', 0b1000), ehT0Px3KOsy9(chr(0b100101 + 0o13) + chr(111) + chr(51) + '\x31' + chr(304 - 250), 0o10), ehT0Px3KOsy9(chr(2203 - 2155) + '\157' + chr(0b110011) + chr(52) + '\063', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(10304 - 10193) + chr(263 - 214) + '\x32' + '\x36', 0b1000), ehT0Px3KOsy9(chr(0b101110 + 0o2) + '\x6f' + chr(0b11010 + 0o34) + '\067', ord("\x08")), ehT0Px3KOsy9(chr(2045 - 1997) + chr(0b1101111) + chr(0b110010) + chr(193 - 139), ord("\x08")), ehT0Px3KOsy9(chr(1009 - 961) + chr(111) + '\063' + chr(0b1 + 0o61) + '\063', 0o10), ehT0Px3KOsy9(chr(814 - 766) + chr(5063 - 4952) + '\x33' + '\x30' + chr(48), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b10110 + 0o41) + chr(2804 - 2749), 25285 - 25277), ehT0Px3KOsy9('\x30' + chr(111) + chr(51) + '\062' + '\x33', 8)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + chr(111) + chr(53) + '\x30', 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'>'), chr(100) + chr(101) + '\143' + chr(0b1000101 + 0o52) + chr(0b1100100) + chr(6073 - 5972))('\165' + chr(0b1001100 + 0o50) + '\146' + chr(0b11110 + 0o17) + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def M3E5bfIV8rX_(NKKFbr2Z4sr1, _sqfVuM76EP3, P7DmIFVRivx6=None, o90TMYhFhMm_=None, hyGdBsLYkQVS=ehT0Px3KOsy9('\x30' + chr(3554 - 3443) + chr(0b110001), 8), T1brfYV34pPD=None, qKlXBtn3PKy4=None, op94qe_Rdjul=None):
_sqfVuM76EP3 = NcAk05ebjpoG(_sqfVuM76EP3)
if not Q1dJV0ss0eny(_sqfVuM76EP3):
raise _zJ24Vce7wp0(xafqLlk3kkUe(SXOLrMavuUCe(b"b \x9b:y\x93\xack\x85@\xf8\xd4\x8eA~74\xbdx\xfa\xf8A\xa7(7x\x18\xaez\xff\xea\xa1\x91vdG\x9f\x81S\xb0x \x97'\x06\x83\xb2i\xb4Q\xfa\xc2\x83F2=t"), '\144' + chr(2482 - 2381) + chr(8723 - 8624) + chr(0b1101111) + chr(100) + '\145')(chr(5529 - 5412) + chr(0b1110100) + '\146' + chr(879 - 834) + chr(0b111000)))
(PiAb9sTkjfM_,) = (jFWsnpHpAUWz(xafqLlk3kkUe(SXOLrMavuUCe(b'c4\x96?J\x83\xb5b\xb7M'), '\x64' + chr(5531 - 5430) + '\143' + chr(0b1101111) + chr(168 - 68) + chr(0b100 + 0o141))(chr(117) + chr(116) + chr(0b101010 + 0o74) + chr(45) + chr(1475 - 1419))),)
(cIx8kvPtdxPd,) = (xafqLlk3kkUe(xafqLlk3kkUe(NPPHb59961Bv(xafqLlk3kkUe(SXOLrMavuUCe(b'c4\x96?J\x83\xb5b\xb7M\xb7\xc5\x81L;5;'), chr(3416 - 3316) + chr(0b1100101) + '\x63' + chr(111) + chr(0b1100100) + chr(101))('\x75' + '\x74' + chr(0b1100110) + chr(1395 - 1350) + chr(0b100001 + 0o27)), xafqLlk3kkUe(SXOLrMavuUCe(b'] \x8e?b\x81\xa9f'), chr(100) + chr(3122 - 3021) + chr(99) + chr(0b1101111) + chr(2596 - 2496) + '\x65')(chr(0b1110101) + '\164' + chr(0b100000 + 0o106) + chr(961 - 916) + '\x38')), xafqLlk3kkUe(SXOLrMavuUCe(b'c&\x92;K\x81'), '\144' + chr(1834 - 1733) + chr(99) + '\x6f' + chr(100) + chr(0b111011 + 0o52))(chr(0b1110101) + chr(0b1110100) + chr(0b1001111 + 0o27) + chr(1287 - 1242) + '\070')), xafqLlk3kkUe(SXOLrMavuUCe(b'] \x8e?b\x81\xa9f'), chr(0b1011110 + 0o6) + chr(101) + chr(0b1100011) + chr(0b1101111) + chr(100) + '\145')(chr(2819 - 2702) + '\x74' + '\x66' + chr(45) + '\x38')),)
Ddxy_ihdYXS3 = cIx8kvPtdxPd(_sqfVuM76EP3, schema=P7DmIFVRivx6)
try:
xafqLlk3kkUe(Ddxy_ihdYXS3, xafqLlk3kkUe(SXOLrMavuUCe(b'b \x9c2C\x83\xa9'), chr(0b11011 + 0o111) + '\x65' + '\143' + chr(111) + chr(0b1110 + 0o126) + '\145')('\165' + chr(0b1110100) + chr(0b100011 + 0o103) + '\x2d' + '\x38'))(only=[NKKFbr2Z4sr1], views=ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\061', 8))
except xafqLlk3kkUe(PiAb9sTkjfM_.exc, xafqLlk3kkUe(SXOLrMavuUCe(b'Y+\x8c?J\x89\xb9U\xbfE\xec\xd3\x91P\x1b*(\xbes'), '\144' + chr(0b101100 + 0o71) + chr(0b1100011) + chr(10983 - 10872) + chr(100) + chr(0b11 + 0o142))(chr(12058 - 11941) + chr(826 - 710) + chr(0b10011 + 0o123) + chr(270 - 225) + chr(0b111000))):
raise q1QCh3W88sgk(xafqLlk3kkUe(xafqLlk3kkUe(SXOLrMavuUCe(b'D$\x982C\xc0\xa6i\xbbY\xfc\xcb\xc2J1,z\xb7n\xaf\xe5P'), chr(100) + chr(101) + '\143' + chr(111) + '\144' + '\145')(chr(3440 - 3323) + chr(0b1110100) + chr(102) + chr(45) + chr(0b110101 + 0o3)), xafqLlk3kkUe(SXOLrMavuUCe(b'v*\x883G\x94'), chr(3702 - 3602) + '\x65' + chr(99) + chr(0b1100001 + 0o16) + '\x64' + '\145')(chr(117) + '\164' + chr(102) + chr(591 - 546) + chr(0b11 + 0o65)))(name=NKKFbr2Z4sr1))
Re4ydlckRnKx = APbCRgLa2CC0(_sqfVuM76EP3, meta=Ddxy_ihdYXS3)
YbLi4ide0_3E = Re4ydlckRnKx.read_table(NKKFbr2Z4sr1, index_col=o90TMYhFhMm_, coerce_float=hyGdBsLYkQVS, parse_dates=T1brfYV34pPD, columns=qKlXBtn3PKy4, chunksize=op94qe_Rdjul)
if YbLi4ide0_3E is not None:
return YbLi4ide0_3E
else:
raise q1QCh3W88sgk(xafqLlk3kkUe(xafqLlk3kkUe(SXOLrMavuUCe(b'D$\x982C\xc0\xa6i\xbbY\xfc\xcb\xc2J1,z\xb7n\xaf\xe5P'), chr(100) + chr(0b1100101) + chr(0b1100011) + '\157' + chr(0b1100100) + chr(0b1100101))(chr(0b1110101) + '\164' + chr(0b110101 + 0o61) + chr(0b101101) + '\070'), xafqLlk3kkUe(SXOLrMavuUCe(b'v*\x883G\x94'), '\144' + '\x65' + chr(0b1010111 + 0o14) + chr(111) + chr(0b1100100) + chr(0b101110 + 0o67))(chr(2349 - 2232) + chr(0b111101 + 0o67) + chr(9665 - 9563) + chr(1085 - 1040) + chr(0b110101 + 0o3)))(name=NKKFbr2Z4sr1), _sqfVuM76EP3)
|
pandas-dev/pandas
|
pandas/io/sql.py
|
read_sql_query
|
def read_sql_query(sql, con, index_col=None, coerce_float=True, params=None,
parse_dates=None, chunksize=None):
"""Read SQL query into a DataFrame.
Returns a DataFrame corresponding to the result set of the query
string. Optionally provide an `index_col` parameter to use one of the
columns as the index, otherwise default integer index will be used.
Parameters
----------
sql : string SQL query or SQLAlchemy Selectable (select or text object)
SQL query to be executed.
con : SQLAlchemy connectable(engine/connection), database string URI,
or sqlite3 DBAPI2 connection
Using SQLAlchemy makes it possible to use any DB supported by that
library.
If a DBAPI2 object, only sqlite3 is supported.
index_col : string or list of strings, optional, default: None
Column(s) to set as index(MultiIndex).
coerce_float : boolean, default True
Attempts to convert values of non-string, non-numeric objects (like
decimal.Decimal) to floating point. Useful for SQL result sets.
params : list, tuple or dict, optional, default: None
List of parameters to pass to execute method. The syntax used
to pass parameters is database driver dependent. Check your
database driver documentation for which of the five syntax styles,
described in PEP 249's paramstyle, is supported.
Eg. for psycopg2, uses %(name)s so use params={'name' : 'value'}
parse_dates : list or dict, default: None
- List of column names to parse as dates.
- Dict of ``{column_name: format string}`` where format string is
strftime compatible in case of parsing string times, or is one of
(D, s, ns, ms, us) in case of parsing integer timestamps.
- Dict of ``{column_name: arg dict}``, where the arg dict corresponds
to the keyword arguments of :func:`pandas.to_datetime`
Especially useful with databases without native Datetime support,
such as SQLite.
chunksize : int, default None
If specified, return an iterator where `chunksize` is the number of
rows to include in each chunk.
Returns
-------
DataFrame
See Also
--------
read_sql_table : Read SQL database table into a DataFrame.
read_sql
Notes
-----
Any datetime values with time zone information parsed via the `parse_dates`
parameter will be converted to UTC.
"""
pandas_sql = pandasSQL_builder(con)
return pandas_sql.read_query(
sql, index_col=index_col, params=params, coerce_float=coerce_float,
parse_dates=parse_dates, chunksize=chunksize)
|
python
|
def read_sql_query(sql, con, index_col=None, coerce_float=True, params=None,
parse_dates=None, chunksize=None):
"""Read SQL query into a DataFrame.
Returns a DataFrame corresponding to the result set of the query
string. Optionally provide an `index_col` parameter to use one of the
columns as the index, otherwise default integer index will be used.
Parameters
----------
sql : string SQL query or SQLAlchemy Selectable (select or text object)
SQL query to be executed.
con : SQLAlchemy connectable(engine/connection), database string URI,
or sqlite3 DBAPI2 connection
Using SQLAlchemy makes it possible to use any DB supported by that
library.
If a DBAPI2 object, only sqlite3 is supported.
index_col : string or list of strings, optional, default: None
Column(s) to set as index(MultiIndex).
coerce_float : boolean, default True
Attempts to convert values of non-string, non-numeric objects (like
decimal.Decimal) to floating point. Useful for SQL result sets.
params : list, tuple or dict, optional, default: None
List of parameters to pass to execute method. The syntax used
to pass parameters is database driver dependent. Check your
database driver documentation for which of the five syntax styles,
described in PEP 249's paramstyle, is supported.
Eg. for psycopg2, uses %(name)s so use params={'name' : 'value'}
parse_dates : list or dict, default: None
- List of column names to parse as dates.
- Dict of ``{column_name: format string}`` where format string is
strftime compatible in case of parsing string times, or is one of
(D, s, ns, ms, us) in case of parsing integer timestamps.
- Dict of ``{column_name: arg dict}``, where the arg dict corresponds
to the keyword arguments of :func:`pandas.to_datetime`
Especially useful with databases without native Datetime support,
such as SQLite.
chunksize : int, default None
If specified, return an iterator where `chunksize` is the number of
rows to include in each chunk.
Returns
-------
DataFrame
See Also
--------
read_sql_table : Read SQL database table into a DataFrame.
read_sql
Notes
-----
Any datetime values with time zone information parsed via the `parse_dates`
parameter will be converted to UTC.
"""
pandas_sql = pandasSQL_builder(con)
return pandas_sql.read_query(
sql, index_col=index_col, params=params, coerce_float=coerce_float,
parse_dates=parse_dates, chunksize=chunksize)
|
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"(",
"con",
")",
"return",
"pandas_sql",
".",
"read_query",
"(",
"sql",
",",
"index_col",
"=",
"index_col",
",",
"params",
"=",
"params",
",",
"coerce_float",
"=",
"coerce_float",
",",
"parse_dates",
"=",
"parse_dates",
",",
"chunksize",
"=",
"chunksize",
")"
] |
Read SQL query into a DataFrame.
Returns a DataFrame corresponding to the result set of the query
string. Optionally provide an `index_col` parameter to use one of the
columns as the index, otherwise default integer index will be used.
Parameters
----------
sql : string SQL query or SQLAlchemy Selectable (select or text object)
SQL query to be executed.
con : SQLAlchemy connectable(engine/connection), database string URI,
or sqlite3 DBAPI2 connection
Using SQLAlchemy makes it possible to use any DB supported by that
library.
If a DBAPI2 object, only sqlite3 is supported.
index_col : string or list of strings, optional, default: None
Column(s) to set as index(MultiIndex).
coerce_float : boolean, default True
Attempts to convert values of non-string, non-numeric objects (like
decimal.Decimal) to floating point. Useful for SQL result sets.
params : list, tuple or dict, optional, default: None
List of parameters to pass to execute method. The syntax used
to pass parameters is database driver dependent. Check your
database driver documentation for which of the five syntax styles,
described in PEP 249's paramstyle, is supported.
Eg. for psycopg2, uses %(name)s so use params={'name' : 'value'}
parse_dates : list or dict, default: None
- List of column names to parse as dates.
- Dict of ``{column_name: format string}`` where format string is
strftime compatible in case of parsing string times, or is one of
(D, s, ns, ms, us) in case of parsing integer timestamps.
- Dict of ``{column_name: arg dict}``, where the arg dict corresponds
to the keyword arguments of :func:`pandas.to_datetime`
Especially useful with databases without native Datetime support,
such as SQLite.
chunksize : int, default None
If specified, return an iterator where `chunksize` is the number of
rows to include in each chunk.
Returns
-------
DataFrame
See Also
--------
read_sql_table : Read SQL database table into a DataFrame.
read_sql
Notes
-----
Any datetime values with time zone information parsed via the `parse_dates`
parameter will be converted to UTC.
|
[
"Read",
"SQL",
"query",
"into",
"a",
"DataFrame",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/io/sql.py#L247-L305
|
train
|
Read a SQL query into a DataFrame.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + chr(0b1001110 + 0o41) + '\x33' + chr(0b100100 + 0o22) + chr(1968 - 1920), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(6810 - 6699) + chr(0b110010) + chr(2072 - 2022) + '\x32', 0o10), ehT0Px3KOsy9('\060' + '\157' + '\x34' + chr(48), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + '\063' + '\066' + '\064', ord("\x08")), ehT0Px3KOsy9(chr(459 - 411) + chr(0b1101111) + chr(0b110011) + '\x34' + chr(434 - 382), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(5617 - 5506) + chr(1401 - 1350) + '\060' + '\062', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(563 - 452) + chr(54) + chr(0b100001 + 0o23), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b1011 + 0o50) + chr(1870 - 1818) + '\x32', ord("\x08")), ehT0Px3KOsy9(chr(0b100010 + 0o16) + chr(0b111010 + 0o65) + chr(0b11011 + 0o26) + chr(0b10100 + 0o35) + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1001101 + 0o42) + chr(0b110011) + chr(0b110001 + 0o5) + '\x35', 38256 - 38248), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110010) + chr(1138 - 1083) + chr(954 - 906), ord("\x08")), ehT0Px3KOsy9('\060' + chr(8514 - 8403) + '\062' + '\062' + chr(2539 - 2484), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(1893 - 1844) + chr(0b110100) + chr(1607 - 1557), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + '\063' + chr(0b101100 + 0o10) + chr(0b110000), 0o10), ehT0Px3KOsy9(chr(1566 - 1518) + chr(111) + chr(0b110010) + '\x31' + chr(0b110110), ord("\x08")), ehT0Px3KOsy9(chr(1607 - 1559) + '\157' + chr(1015 - 965) + '\x34' + chr(648 - 600), 11439 - 11431), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110011) + chr(55) + chr(0b101110 + 0o11), 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(50) + '\060' + chr(596 - 547), ord("\x08")), ehT0Px3KOsy9(chr(1456 - 1408) + '\157' + '\061' + chr(55) + chr(909 - 860), 0o10), ehT0Px3KOsy9(chr(0b110 + 0o52) + chr(0b1101111) + chr(0b1010 + 0o51) + chr(0b110100) + '\066', ord("\x08")), ehT0Px3KOsy9(chr(2082 - 2034) + chr(0b1101111) + '\x33' + '\x30' + '\x31', 27057 - 27049), ehT0Px3KOsy9('\x30' + '\157' + '\x32' + chr(49) + chr(0b10001 + 0o37), 34720 - 34712), ehT0Px3KOsy9(chr(48) + '\157' + '\x33' + '\066' + chr(1005 - 950), 38998 - 38990), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b11001 + 0o36) + '\067', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(3513 - 3402) + chr(0b110001) + chr(0b110111 + 0o0) + chr(86 - 36), 0b1000), ehT0Px3KOsy9(chr(2273 - 2225) + '\x6f' + '\063' + chr(0b110001) + chr(0b10111 + 0o32), 59237 - 59229), ehT0Px3KOsy9('\x30' + chr(0b1001110 + 0o41) + '\x33' + chr(1971 - 1923) + chr(0b101 + 0o54), 8), ehT0Px3KOsy9(chr(1174 - 1126) + chr(111) + '\x32' + chr(0b110010) + chr(2227 - 2174), ord("\x08")), ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(0b110111 + 0o70) + chr(51) + '\x35' + chr(50), 1699 - 1691), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110010) + chr(0b110000) + '\063', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1011101 + 0o22) + chr(0b100000 + 0o22) + '\064' + chr(0b101010 + 0o11), 0b1000), ehT0Px3KOsy9(chr(590 - 542) + chr(111) + chr(972 - 922) + chr(0b110011), 10637 - 10629), ehT0Px3KOsy9(chr(48) + chr(0b10100 + 0o133) + chr(53) + chr(49), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b10010 + 0o135) + chr(0b110101) + chr(52), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(11590 - 11479) + '\x31' + '\x34', 0o10), ehT0Px3KOsy9('\x30' + chr(2491 - 2380) + '\062' + chr(462 - 407), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(1773 - 1720) + chr(49), 8), ehT0Px3KOsy9(chr(2245 - 2197) + chr(0b1101111) + chr(1854 - 1803) + chr(2566 - 2514) + chr(0b100010 + 0o21), ord("\x08")), ehT0Px3KOsy9(chr(0b1100 + 0o44) + chr(0b1101111) + chr(0b111 + 0o54) + '\x30' + '\x31', 8), ehT0Px3KOsy9('\060' + '\157' + '\x31' + chr(135 - 87) + chr(52), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(261 - 213) + chr(0b11101 + 0o122) + chr(53) + '\060', 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xde'), chr(0b1011010 + 0o12) + chr(0b100000 + 0o105) + chr(0b1100011) + chr(0b1001011 + 0o44) + chr(0b1100100) + '\145')(chr(0b1011101 + 0o30) + chr(116) + chr(0b1100110) + chr(45) + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def bMr2VbgfAxiV(GWXd4kBaViZK, _sqfVuM76EP3, o90TMYhFhMm_=None, hyGdBsLYkQVS=ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(5217 - 5106) + chr(0b110001), 0b1000), nEbJZ4wfte2w=None, T1brfYV34pPD=None, op94qe_Rdjul=None):
Re4ydlckRnKx = Hm7TAp8orHi4(_sqfVuM76EP3)
return xafqLlk3kkUe(Re4ydlckRnKx, xafqLlk3kkUe(SXOLrMavuUCe(b'\x82\xf7A\x90\xbb\xb3A\x878\x8c'), chr(3091 - 2991) + '\145' + chr(99) + chr(0b1101111) + '\x64' + chr(0b110101 + 0o60))(chr(0b1010111 + 0o36) + '\164' + chr(0b11000 + 0o116) + '\x2d' + chr(0b10010 + 0o46)))(GWXd4kBaViZK, index_col=o90TMYhFhMm_, params=nEbJZ4wfte2w, coerce_float=hyGdBsLYkQVS, parse_dates=T1brfYV34pPD, chunksize=op94qe_Rdjul)
|
pandas-dev/pandas
|
pandas/io/sql.py
|
read_sql
|
def read_sql(sql, con, index_col=None, coerce_float=True, params=None,
parse_dates=None, columns=None, chunksize=None):
"""
Read SQL query or database table into a DataFrame.
This function is a convenience wrapper around ``read_sql_table`` and
``read_sql_query`` (for backward compatibility). It will delegate
to the specific function depending on the provided input. A SQL query
will be routed to ``read_sql_query``, while a database table name will
be routed to ``read_sql_table``. Note that the delegated function might
have more specific notes about their functionality not listed here.
Parameters
----------
sql : string or SQLAlchemy Selectable (select or text object)
SQL query to be executed or a table name.
con : SQLAlchemy connectable (engine/connection) or database string URI
or DBAPI2 connection (fallback mode)
Using SQLAlchemy makes it possible to use any DB supported by that
library. If a DBAPI2 object, only sqlite3 is supported.
index_col : string or list of strings, optional, default: None
Column(s) to set as index(MultiIndex).
coerce_float : boolean, default True
Attempts to convert values of non-string, non-numeric objects (like
decimal.Decimal) to floating point, useful for SQL result sets.
params : list, tuple or dict, optional, default: None
List of parameters to pass to execute method. The syntax used
to pass parameters is database driver dependent. Check your
database driver documentation for which of the five syntax styles,
described in PEP 249's paramstyle, is supported.
Eg. for psycopg2, uses %(name)s so use params={'name' : 'value'}
parse_dates : list or dict, default: None
- List of column names to parse as dates.
- Dict of ``{column_name: format string}`` where format string is
strftime compatible in case of parsing string times, or is one of
(D, s, ns, ms, us) in case of parsing integer timestamps.
- Dict of ``{column_name: arg dict}``, where the arg dict corresponds
to the keyword arguments of :func:`pandas.to_datetime`
Especially useful with databases without native Datetime support,
such as SQLite.
columns : list, default: None
List of column names to select from SQL table (only used when reading
a table).
chunksize : int, default None
If specified, return an iterator where `chunksize` is the
number of rows to include in each chunk.
Returns
-------
DataFrame
See Also
--------
read_sql_table : Read SQL database table into a DataFrame.
read_sql_query : Read SQL query into a DataFrame.
"""
pandas_sql = pandasSQL_builder(con)
if isinstance(pandas_sql, SQLiteDatabase):
return pandas_sql.read_query(
sql, index_col=index_col, params=params,
coerce_float=coerce_float, parse_dates=parse_dates,
chunksize=chunksize)
try:
_is_table_name = pandas_sql.has_table(sql)
except Exception:
# using generic exception to catch errors from sql drivers (GH24988)
_is_table_name = False
if _is_table_name:
pandas_sql.meta.reflect(only=[sql])
return pandas_sql.read_table(
sql, index_col=index_col, coerce_float=coerce_float,
parse_dates=parse_dates, columns=columns, chunksize=chunksize)
else:
return pandas_sql.read_query(
sql, index_col=index_col, params=params,
coerce_float=coerce_float, parse_dates=parse_dates,
chunksize=chunksize)
|
python
|
def read_sql(sql, con, index_col=None, coerce_float=True, params=None,
parse_dates=None, columns=None, chunksize=None):
"""
Read SQL query or database table into a DataFrame.
This function is a convenience wrapper around ``read_sql_table`` and
``read_sql_query`` (for backward compatibility). It will delegate
to the specific function depending on the provided input. A SQL query
will be routed to ``read_sql_query``, while a database table name will
be routed to ``read_sql_table``. Note that the delegated function might
have more specific notes about their functionality not listed here.
Parameters
----------
sql : string or SQLAlchemy Selectable (select or text object)
SQL query to be executed or a table name.
con : SQLAlchemy connectable (engine/connection) or database string URI
or DBAPI2 connection (fallback mode)
Using SQLAlchemy makes it possible to use any DB supported by that
library. If a DBAPI2 object, only sqlite3 is supported.
index_col : string or list of strings, optional, default: None
Column(s) to set as index(MultiIndex).
coerce_float : boolean, default True
Attempts to convert values of non-string, non-numeric objects (like
decimal.Decimal) to floating point, useful for SQL result sets.
params : list, tuple or dict, optional, default: None
List of parameters to pass to execute method. The syntax used
to pass parameters is database driver dependent. Check your
database driver documentation for which of the five syntax styles,
described in PEP 249's paramstyle, is supported.
Eg. for psycopg2, uses %(name)s so use params={'name' : 'value'}
parse_dates : list or dict, default: None
- List of column names to parse as dates.
- Dict of ``{column_name: format string}`` where format string is
strftime compatible in case of parsing string times, or is one of
(D, s, ns, ms, us) in case of parsing integer timestamps.
- Dict of ``{column_name: arg dict}``, where the arg dict corresponds
to the keyword arguments of :func:`pandas.to_datetime`
Especially useful with databases without native Datetime support,
such as SQLite.
columns : list, default: None
List of column names to select from SQL table (only used when reading
a table).
chunksize : int, default None
If specified, return an iterator where `chunksize` is the
number of rows to include in each chunk.
Returns
-------
DataFrame
See Also
--------
read_sql_table : Read SQL database table into a DataFrame.
read_sql_query : Read SQL query into a DataFrame.
"""
pandas_sql = pandasSQL_builder(con)
if isinstance(pandas_sql, SQLiteDatabase):
return pandas_sql.read_query(
sql, index_col=index_col, params=params,
coerce_float=coerce_float, parse_dates=parse_dates,
chunksize=chunksize)
try:
_is_table_name = pandas_sql.has_table(sql)
except Exception:
# using generic exception to catch errors from sql drivers (GH24988)
_is_table_name = False
if _is_table_name:
pandas_sql.meta.reflect(only=[sql])
return pandas_sql.read_table(
sql, index_col=index_col, coerce_float=coerce_float,
parse_dates=parse_dates, columns=columns, chunksize=chunksize)
else:
return pandas_sql.read_query(
sql, index_col=index_col, params=params,
coerce_float=coerce_float, parse_dates=parse_dates,
chunksize=chunksize)
|
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"pandas_sql",
".",
"has_table",
"(",
"sql",
")",
"except",
"Exception",
":",
"# using generic exception to catch errors from sql drivers (GH24988)",
"_is_table_name",
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"_is_table_name",
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"read_table",
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"index_col",
"=",
"index_col",
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"=",
"coerce_float",
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"coerce_float",
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"coerce_float",
",",
"parse_dates",
"=",
"parse_dates",
",",
"chunksize",
"=",
"chunksize",
")"
] |
Read SQL query or database table into a DataFrame.
This function is a convenience wrapper around ``read_sql_table`` and
``read_sql_query`` (for backward compatibility). It will delegate
to the specific function depending on the provided input. A SQL query
will be routed to ``read_sql_query``, while a database table name will
be routed to ``read_sql_table``. Note that the delegated function might
have more specific notes about their functionality not listed here.
Parameters
----------
sql : string or SQLAlchemy Selectable (select or text object)
SQL query to be executed or a table name.
con : SQLAlchemy connectable (engine/connection) or database string URI
or DBAPI2 connection (fallback mode)
Using SQLAlchemy makes it possible to use any DB supported by that
library. If a DBAPI2 object, only sqlite3 is supported.
index_col : string or list of strings, optional, default: None
Column(s) to set as index(MultiIndex).
coerce_float : boolean, default True
Attempts to convert values of non-string, non-numeric objects (like
decimal.Decimal) to floating point, useful for SQL result sets.
params : list, tuple or dict, optional, default: None
List of parameters to pass to execute method. The syntax used
to pass parameters is database driver dependent. Check your
database driver documentation for which of the five syntax styles,
described in PEP 249's paramstyle, is supported.
Eg. for psycopg2, uses %(name)s so use params={'name' : 'value'}
parse_dates : list or dict, default: None
- List of column names to parse as dates.
- Dict of ``{column_name: format string}`` where format string is
strftime compatible in case of parsing string times, or is one of
(D, s, ns, ms, us) in case of parsing integer timestamps.
- Dict of ``{column_name: arg dict}``, where the arg dict corresponds
to the keyword arguments of :func:`pandas.to_datetime`
Especially useful with databases without native Datetime support,
such as SQLite.
columns : list, default: None
List of column names to select from SQL table (only used when reading
a table).
chunksize : int, default None
If specified, return an iterator where `chunksize` is the
number of rows to include in each chunk.
Returns
-------
DataFrame
See Also
--------
read_sql_table : Read SQL database table into a DataFrame.
read_sql_query : Read SQL query into a DataFrame.
|
[
"Read",
"SQL",
"query",
"or",
"database",
"table",
"into",
"a",
"DataFrame",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/io/sql.py#L308-L388
|
train
|
Read a SQL query or database table into a DataFrame.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + chr(0b1011010 + 0o25) + '\063' + chr(1031 - 980) + chr(0b10110 + 0o41), 0b1000), ehT0Px3KOsy9('\x30' + '\157' + '\x33' + '\x30' + chr(0b110011), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(415 - 364) + chr(0b100011 + 0o16) + chr(2267 - 2217), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b10001 + 0o42) + '\x36' + chr(2903 - 2848), ord("\x08")), ehT0Px3KOsy9(chr(617 - 569) + chr(0b1101111) + '\063' + chr(0b1111 + 0o46) + '\x33', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1001110 + 0o41) + '\061' + '\x35' + chr(48), ord("\x08")), ehT0Px3KOsy9(chr(1591 - 1543) + chr(9852 - 9741) + chr(0b1011 + 0o46) + '\x32' + chr(2571 - 2517), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(525 - 474) + chr(0b100 + 0o57), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + '\062' + '\067' + '\x30', 0o10), ehT0Px3KOsy9(chr(876 - 828) + chr(6818 - 6707) + chr(0b10110 + 0o33) + '\x31' + '\x30', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b11001 + 0o126) + chr(1851 - 1802) + chr(55) + chr(54), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + '\066' + chr(1135 - 1084), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(667 - 615) + chr(0b110010), 20982 - 20974), ehT0Px3KOsy9(chr(48) + chr(9276 - 9165) + chr(2059 - 2010) + chr(0b110101) + chr(0b110 + 0o60), ord("\x08")), ehT0Px3KOsy9(chr(2061 - 2013) + '\157' + chr(0b110001) + chr(974 - 921) + chr(53), 39203 - 39195), ehT0Px3KOsy9('\060' + chr(3830 - 3719) + chr(0b10010 + 0o37) + chr(0b110100), 40620 - 40612), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b10111 + 0o34) + chr(2040 - 1992) + chr(0b10011 + 0o41), 17085 - 17077), ehT0Px3KOsy9(chr(0b110000) + chr(4967 - 4856) + '\x31' + chr(0b110101), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110001) + chr(0b101010 + 0o6) + '\x32', 23564 - 23556), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x33' + chr(0b110011), 8), ehT0Px3KOsy9('\060' + '\157' + '\063' + chr(50) + chr(1132 - 1081), 0b1000), ehT0Px3KOsy9('\060' + chr(0b101000 + 0o107) + chr(0b100011 + 0o17) + chr(0b110000) + chr(51), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(1624 - 1574) + chr(0b110111) + chr(48), 8), ehT0Px3KOsy9(chr(1782 - 1734) + '\x6f' + chr(752 - 701) + '\061' + chr(0b100000 + 0o22), 8), ehT0Px3KOsy9(chr(48) + chr(0b1011110 + 0o21) + '\x32' + '\067', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(408 - 358) + chr(0b110001) + chr(0b101110 + 0o10), 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(578 - 528) + '\067' + '\x33', 0b1000), ehT0Px3KOsy9('\x30' + chr(8724 - 8613) + '\065' + chr(0b110010 + 0o1), 41435 - 41427), ehT0Px3KOsy9('\060' + chr(0b111110 + 0o61) + chr(0b10111 + 0o33) + chr(48), 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(1645 - 1595) + '\067' + chr(913 - 859), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(4468 - 4357) + chr(570 - 520) + chr(1788 - 1740) + chr(0b100101 + 0o20), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(2042 - 1993) + chr(0b110110) + chr(0b11000 + 0o34), 6474 - 6466), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x36' + chr(55), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\061' + '\x35' + chr(0b101010 + 0o13), 8), ehT0Px3KOsy9(chr(0b100101 + 0o13) + chr(10397 - 10286) + chr(0b110010) + chr(196 - 148) + '\x36', 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(1564 - 1514) + '\x32' + chr(0b10001 + 0o40), 39343 - 39335), ehT0Px3KOsy9(chr(784 - 736) + '\x6f' + chr(0b110010) + '\x31' + chr(1033 - 980), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(50) + chr(0b110011) + chr(0b10010 + 0o36), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(50) + chr(1493 - 1443) + '\x35', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b1100 + 0o46) + chr(52) + chr(51), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b100010 + 0o16) + chr(111) + chr(2044 - 1991) + '\x30', 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xf1'), '\144' + '\145' + '\143' + '\157' + chr(100) + chr(0b1010 + 0o133))('\x75' + chr(0b1110100) + chr(1228 - 1126) + chr(0b101101) + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def mdHxN4Ui7iXg(GWXd4kBaViZK, _sqfVuM76EP3, o90TMYhFhMm_=None, hyGdBsLYkQVS=ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b1011 + 0o46), 0o10), nEbJZ4wfte2w=None, T1brfYV34pPD=None, qKlXBtn3PKy4=None, op94qe_Rdjul=None):
Re4ydlckRnKx = Hm7TAp8orHi4(_sqfVuM76EP3)
if PlSM16l2KDPD(Re4ydlckRnKx, bPxPu_8gzhG3):
return xafqLlk3kkUe(Re4ydlckRnKx, xafqLlk3kkUe(SXOLrMavuUCe(b'\xad\xa6\xab\x93\xb4\x19#~\xca1'), '\144' + '\x65' + '\x63' + chr(0b1101111) + '\144' + chr(0b1100101))(chr(0b1011 + 0o152) + '\x74' + '\x66' + '\x2d' + chr(56)))(GWXd4kBaViZK, index_col=o90TMYhFhMm_, params=nEbJZ4wfte2w, coerce_float=hyGdBsLYkQVS, parse_dates=T1brfYV34pPD, chunksize=op94qe_Rdjul)
try:
_4DO_IUDToiS = Re4ydlckRnKx.has_table(GWXd4kBaViZK)
except jLmadlzMdunT:
_4DO_IUDToiS = ehT0Px3KOsy9(chr(0b100010 + 0o16) + chr(111) + chr(0b0 + 0o60), ord("\x08"))
if _4DO_IUDToiS:
xafqLlk3kkUe(Re4ydlckRnKx.meta, xafqLlk3kkUe(SXOLrMavuUCe(b'\xad\xa6\xac\x9b\x8e\x0b"'), chr(0b1100100) + '\x65' + chr(99) + chr(111) + '\x64' + chr(0b1100101))(chr(117) + chr(0b1100010 + 0o22) + chr(102) + '\055' + chr(0b111000)))(only=[GWXd4kBaViZK])
return xafqLlk3kkUe(Re4ydlckRnKx, xafqLlk3kkUe(SXOLrMavuUCe(b'\xad\xa6\xab\x93\xb4\x1c7y\xd4-'), chr(100) + '\x65' + chr(6737 - 6638) + '\157' + chr(1540 - 1440) + chr(0b1100101))(chr(117) + chr(0b1110100) + chr(102) + chr(245 - 200) + chr(56)))(GWXd4kBaViZK, index_col=o90TMYhFhMm_, coerce_float=hyGdBsLYkQVS, parse_dates=T1brfYV34pPD, columns=qKlXBtn3PKy4, chunksize=op94qe_Rdjul)
else:
return xafqLlk3kkUe(Re4ydlckRnKx, xafqLlk3kkUe(SXOLrMavuUCe(b'\xad\xa6\xab\x93\xb4\x19#~\xca1'), chr(4894 - 4794) + chr(4295 - 4194) + '\143' + chr(0b1101111) + '\144' + chr(0b110 + 0o137))(chr(117) + '\x74' + chr(0b1100110) + chr(0b101100 + 0o1) + chr(1978 - 1922)))(GWXd4kBaViZK, index_col=o90TMYhFhMm_, params=nEbJZ4wfte2w, coerce_float=hyGdBsLYkQVS, parse_dates=T1brfYV34pPD, chunksize=op94qe_Rdjul)
|
pandas-dev/pandas
|
pandas/io/sql.py
|
to_sql
|
def to_sql(frame, name, con, schema=None, if_exists='fail', index=True,
index_label=None, chunksize=None, dtype=None, method=None):
"""
Write records stored in a DataFrame to a SQL database.
Parameters
----------
frame : DataFrame, Series
name : string
Name of SQL table.
con : SQLAlchemy connectable(engine/connection) or database string URI
or sqlite3 DBAPI2 connection
Using SQLAlchemy makes it possible to use any DB supported by that
library.
If a DBAPI2 object, only sqlite3 is supported.
schema : string, default None
Name of SQL schema in database to write to (if database flavor
supports this). If None, use default schema (default).
if_exists : {'fail', 'replace', 'append'}, default 'fail'
- fail: If table exists, do nothing.
- replace: If table exists, drop it, recreate it, and insert data.
- append: If table exists, insert data. Create if does not exist.
index : boolean, default True
Write DataFrame index as a column.
index_label : string or sequence, default None
Column label for index column(s). If None is given (default) and
`index` is True, then the index names are used.
A sequence should be given if the DataFrame uses MultiIndex.
chunksize : int, default None
If not None, then rows will be written in batches of this size at a
time. If None, all rows will be written at once.
dtype : single SQLtype or dict of column name to SQL type, default None
Optional specifying the datatype for columns. The SQL type should
be a SQLAlchemy type, or a string for sqlite3 fallback connection.
If all columns are of the same type, one single value can be used.
method : {None, 'multi', callable}, default None
Controls the SQL insertion clause used:
- None : Uses standard SQL ``INSERT`` clause (one per row).
- 'multi': Pass multiple values in a single ``INSERT`` clause.
- callable with signature ``(pd_table, conn, keys, data_iter)``.
Details and a sample callable implementation can be found in the
section :ref:`insert method <io.sql.method>`.
.. versionadded:: 0.24.0
"""
if if_exists not in ('fail', 'replace', 'append'):
raise ValueError("'{0}' is not valid for if_exists".format(if_exists))
pandas_sql = pandasSQL_builder(con, schema=schema)
if isinstance(frame, Series):
frame = frame.to_frame()
elif not isinstance(frame, DataFrame):
raise NotImplementedError("'frame' argument should be either a "
"Series or a DataFrame")
pandas_sql.to_sql(frame, name, if_exists=if_exists, index=index,
index_label=index_label, schema=schema,
chunksize=chunksize, dtype=dtype, method=method)
|
python
|
def to_sql(frame, name, con, schema=None, if_exists='fail', index=True,
index_label=None, chunksize=None, dtype=None, method=None):
"""
Write records stored in a DataFrame to a SQL database.
Parameters
----------
frame : DataFrame, Series
name : string
Name of SQL table.
con : SQLAlchemy connectable(engine/connection) or database string URI
or sqlite3 DBAPI2 connection
Using SQLAlchemy makes it possible to use any DB supported by that
library.
If a DBAPI2 object, only sqlite3 is supported.
schema : string, default None
Name of SQL schema in database to write to (if database flavor
supports this). If None, use default schema (default).
if_exists : {'fail', 'replace', 'append'}, default 'fail'
- fail: If table exists, do nothing.
- replace: If table exists, drop it, recreate it, and insert data.
- append: If table exists, insert data. Create if does not exist.
index : boolean, default True
Write DataFrame index as a column.
index_label : string or sequence, default None
Column label for index column(s). If None is given (default) and
`index` is True, then the index names are used.
A sequence should be given if the DataFrame uses MultiIndex.
chunksize : int, default None
If not None, then rows will be written in batches of this size at a
time. If None, all rows will be written at once.
dtype : single SQLtype or dict of column name to SQL type, default None
Optional specifying the datatype for columns. The SQL type should
be a SQLAlchemy type, or a string for sqlite3 fallback connection.
If all columns are of the same type, one single value can be used.
method : {None, 'multi', callable}, default None
Controls the SQL insertion clause used:
- None : Uses standard SQL ``INSERT`` clause (one per row).
- 'multi': Pass multiple values in a single ``INSERT`` clause.
- callable with signature ``(pd_table, conn, keys, data_iter)``.
Details and a sample callable implementation can be found in the
section :ref:`insert method <io.sql.method>`.
.. versionadded:: 0.24.0
"""
if if_exists not in ('fail', 'replace', 'append'):
raise ValueError("'{0}' is not valid for if_exists".format(if_exists))
pandas_sql = pandasSQL_builder(con, schema=schema)
if isinstance(frame, Series):
frame = frame.to_frame()
elif not isinstance(frame, DataFrame):
raise NotImplementedError("'frame' argument should be either a "
"Series or a DataFrame")
pandas_sql.to_sql(frame, name, if_exists=if_exists, index=index,
index_label=index_label, schema=schema,
chunksize=chunksize, dtype=dtype, method=method)
|
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",",
"index",
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",",
"method",
"=",
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")"
] |
Write records stored in a DataFrame to a SQL database.
Parameters
----------
frame : DataFrame, Series
name : string
Name of SQL table.
con : SQLAlchemy connectable(engine/connection) or database string URI
or sqlite3 DBAPI2 connection
Using SQLAlchemy makes it possible to use any DB supported by that
library.
If a DBAPI2 object, only sqlite3 is supported.
schema : string, default None
Name of SQL schema in database to write to (if database flavor
supports this). If None, use default schema (default).
if_exists : {'fail', 'replace', 'append'}, default 'fail'
- fail: If table exists, do nothing.
- replace: If table exists, drop it, recreate it, and insert data.
- append: If table exists, insert data. Create if does not exist.
index : boolean, default True
Write DataFrame index as a column.
index_label : string or sequence, default None
Column label for index column(s). If None is given (default) and
`index` is True, then the index names are used.
A sequence should be given if the DataFrame uses MultiIndex.
chunksize : int, default None
If not None, then rows will be written in batches of this size at a
time. If None, all rows will be written at once.
dtype : single SQLtype or dict of column name to SQL type, default None
Optional specifying the datatype for columns. The SQL type should
be a SQLAlchemy type, or a string for sqlite3 fallback connection.
If all columns are of the same type, one single value can be used.
method : {None, 'multi', callable}, default None
Controls the SQL insertion clause used:
- None : Uses standard SQL ``INSERT`` clause (one per row).
- 'multi': Pass multiple values in a single ``INSERT`` clause.
- callable with signature ``(pd_table, conn, keys, data_iter)``.
Details and a sample callable implementation can be found in the
section :ref:`insert method <io.sql.method>`.
.. versionadded:: 0.24.0
|
[
"Write",
"records",
"stored",
"in",
"a",
"DataFrame",
"to",
"a",
"SQL",
"database",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/io/sql.py#L391-L451
|
train
|
Writes records stored in a DataFrame to a SQL database.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\x30' + '\157' + '\067' + chr(335 - 284), 25849 - 25841), ehT0Px3KOsy9(chr(1142 - 1094) + '\157' + chr(50) + chr(0b101110 + 0o7) + chr(0b110000), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b11111 + 0o24) + '\063' + chr(51), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(0b1111 + 0o43) + chr(0b110001 + 0o6) + chr(53), 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(0b101110 + 0o5) + chr(49) + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(540 - 490) + chr(0b110001) + chr(0b110100), ord("\x08")), ehT0Px3KOsy9(chr(0b10100 + 0o34) + chr(111) + '\x33' + chr(0b110110) + chr(1214 - 1165), 0b1000), ehT0Px3KOsy9(chr(0b101 + 0o53) + chr(0b1101111) + '\063' + chr(0b110010) + chr(0b110 + 0o57), ord("\x08")), ehT0Px3KOsy9(chr(613 - 565) + chr(2524 - 2413) + chr(51) + chr(0b110010) + '\061', 10705 - 10697), ehT0Px3KOsy9(chr(0b11011 + 0o25) + chr(0b1 + 0o156) + chr(1841 - 1790) + chr(0b10111 + 0o34) + chr(48), ord("\x08")), ehT0Px3KOsy9(chr(198 - 150) + chr(111) + '\061' + chr(0b110101) + chr(478 - 427), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(7259 - 7148) + chr(481 - 431) + chr(0b110011) + '\062', 0o10), ehT0Px3KOsy9(chr(555 - 507) + chr(454 - 343) + '\x33' + '\062' + chr(0b101001 + 0o15), 33266 - 33258), ehT0Px3KOsy9('\060' + chr(0b1101110 + 0o1) + '\x31' + '\060' + chr(53), 1251 - 1243), ehT0Px3KOsy9(chr(0b11 + 0o55) + chr(111) + chr(49) + '\065' + chr(0b10 + 0o61), 8), ehT0Px3KOsy9(chr(0b100010 + 0o16) + '\x6f' + chr(471 - 420) + chr(54) + chr(0b110011), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110100) + chr(1448 - 1399), 47035 - 47027), ehT0Px3KOsy9('\x30' + chr(111) + '\063' + chr(1875 - 1823) + chr(51), 0b1000), ehT0Px3KOsy9(chr(48) + chr(4546 - 4435) + chr(483 - 432) + chr(54) + chr(53), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b10000 + 0o43) + chr(1719 - 1671) + chr(2710 - 2655), 45298 - 45290), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\061' + '\x32' + '\062', 0o10), ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(0b1010000 + 0o37) + chr(1956 - 1901) + '\x30', 12409 - 12401), ehT0Px3KOsy9('\060' + chr(2444 - 2333) + '\063' + chr(0b100000 + 0o23) + '\067', 55026 - 55018), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\062' + '\064' + '\065', 0b1000), ehT0Px3KOsy9(chr(1487 - 1439) + chr(111) + chr(0b1000 + 0o53) + chr(52) + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b101110 + 0o4) + '\x32' + chr(0b110110), ord("\x08")), ehT0Px3KOsy9(chr(1489 - 1441) + chr(0b1101111) + '\062' + chr(1533 - 1478) + chr(0b110000 + 0o3), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(11814 - 11703) + '\x32' + chr(0b10 + 0o65) + chr(55), 20152 - 20144), ehT0Px3KOsy9(chr(1492 - 1444) + chr(111) + chr(50) + chr(55) + '\x35', 8), ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(111) + chr(0b1110 + 0o44) + chr(432 - 383) + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(1819 - 1770) + '\065' + chr(0b110110), 10146 - 10138), ehT0Px3KOsy9(chr(0b110000) + chr(3026 - 2915) + chr(0b110011) + chr(53) + chr(0b110100), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + '\x33' + chr(0b110110) + chr(0b110111), ord("\x08")), ehT0Px3KOsy9(chr(829 - 781) + chr(0b1101111) + chr(2000 - 1949) + '\x32', 42716 - 42708), ehT0Px3KOsy9(chr(533 - 485) + chr(0b1011111 + 0o20) + chr(0b100011 + 0o17) + chr(1814 - 1764) + chr(49), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b1101 + 0o50) + chr(0b1111 + 0o45), 0o10), ehT0Px3KOsy9(chr(1252 - 1204) + chr(0b10110 + 0o131) + chr(51) + chr(0b110000) + chr(0b1010 + 0o46), 35970 - 35962), ehT0Px3KOsy9(chr(0b1110 + 0o42) + chr(0b1101111) + '\x32' + '\x33', 50149 - 50141), ehT0Px3KOsy9(chr(2094 - 2046) + '\157' + chr(0b1010 + 0o47) + '\064' + chr(0b110000), 0o10), ehT0Px3KOsy9(chr(48) + chr(6177 - 6066) + chr(0b101100 + 0o5) + chr(1144 - 1089) + '\x33', 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + chr(0b1101111 + 0o0) + chr(2808 - 2755) + chr(1413 - 1365), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x15'), chr(100) + '\x65' + chr(0b100010 + 0o101) + chr(0b1001010 + 0o45) + chr(100) + chr(101))('\165' + '\x74' + chr(7629 - 7527) + '\x2d' + chr(0b110 + 0o62)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def b6tBeYOjJJGT(C4IqNNmLfHXB, AIvJRzLdDfgF, _sqfVuM76EP3, P7DmIFVRivx6=None, zZFPtODM90fp=xafqLlk3kkUe(SXOLrMavuUCe(b']\xc9\xb2\xd1'), chr(0b1100100) + chr(0b1100101) + chr(1308 - 1209) + '\x6f' + chr(0b111101 + 0o47) + chr(0b1001100 + 0o31))(chr(0b1010100 + 0o41) + chr(0b1110100) + chr(2260 - 2158) + chr(0b101101) + chr(56)), XdowRbJKZWL9=ehT0Px3KOsy9('\060' + chr(0b11000 + 0o127) + chr(0b110001), 15577 - 15569), Rj5_q03bvJPB=None, op94qe_Rdjul=None, jSV9IKnemH7K=None, CVRCXTcnOnH6=None):
if zZFPtODM90fp not in (xafqLlk3kkUe(SXOLrMavuUCe(b']\xc9\xb2\xd1'), chr(0b1100100) + chr(5959 - 5858) + chr(2503 - 2404) + chr(111) + chr(0b101011 + 0o71) + '\145')(chr(117) + chr(0b11100 + 0o130) + '\x66' + chr(0b101101) + chr(214 - 158)), xafqLlk3kkUe(SXOLrMavuUCe(b'I\xcd\xab\xd1\xad\xef\x94'), chr(0b1100100) + chr(7426 - 7325) + '\x63' + '\x6f' + chr(2559 - 2459) + '\x65')(chr(0b1110101) + chr(116) + chr(5314 - 5212) + chr(0b101101) + chr(0b111000)), xafqLlk3kkUe(SXOLrMavuUCe(b'Z\xd8\xab\xd8\xa2\xe8'), chr(0b1100100) + '\x65' + chr(0b100 + 0o137) + chr(3083 - 2972) + chr(0b1000111 + 0o35) + '\x65')(chr(0b10010 + 0o143) + chr(0b1110100) + chr(0b1011100 + 0o12) + chr(0b101101) + chr(56))):
raise q1QCh3W88sgk(xafqLlk3kkUe(xafqLlk3kkUe(SXOLrMavuUCe(b'\x1c\xd3\xeb\xc0\xeb\xac\x98\xa6\xf1\xb6\x04\xee\xf63\n\x9fH\x87\xd5\xa1=J\xff\xcc\x80\xc9\xde\xc7\xd4\xf9\x1a\x9f'), '\x64' + chr(0b1100101) + chr(0b1000 + 0o133) + chr(2606 - 2495) + '\144' + chr(6903 - 6802))(chr(0b1110101) + '\164' + '\x66' + chr(1601 - 1556) + chr(1954 - 1898)), xafqLlk3kkUe(SXOLrMavuUCe(b']\xc7\xa9\xd0\xad\xf8'), chr(0b110011 + 0o61) + chr(101) + chr(0b110101 + 0o56) + chr(0b1101111) + '\x64' + chr(6940 - 6839))(chr(0b110100 + 0o101) + chr(0b1110100) + chr(102) + '\x2d' + '\070'))(zZFPtODM90fp))
Re4ydlckRnKx = Hm7TAp8orHi4(_sqfVuM76EP3, schema=P7DmIFVRivx6)
if PlSM16l2KDPD(C4IqNNmLfHXB, I9PbrFvU4NYI):
C4IqNNmLfHXB = C4IqNNmLfHXB.to_frame()
elif not PlSM16l2KDPD(C4IqNNmLfHXB, TTWbaLX2VikC):
raise _zJ24Vce7wp0(xafqLlk3kkUe(SXOLrMavuUCe(b"\x1c\xce\xa9\xdc\xa1\xe9\xd6\xf5\xb0\xaa\x0c\xef\xbb \x05\x87\x01\x90\x9d\xa8'T\xbb\x85\x84\xf3\x9b\xda\xd4\xfe\x06\x89\x85:\xf0\x0c\x93v\x12\x12^\xdb\xfb\xd2\xbe\xac\x90\xf5\x95\xb9\x1f\xfb\x907\n\x9eD"), '\144' + chr(0b111100 + 0o51) + chr(7983 - 7884) + chr(111) + chr(100) + '\x65')('\165' + '\164' + '\146' + chr(1163 - 1118) + '\x38'))
xafqLlk3kkUe(Re4ydlckRnKx, xafqLlk3kkUe(SXOLrMavuUCe(b'O\xc7\x84\xce\xbd\xe0'), chr(5364 - 5264) + chr(101) + chr(0b1011110 + 0o5) + chr(111) + '\144' + '\145')(chr(0b1000111 + 0o56) + chr(3055 - 2939) + chr(0b1100110) + chr(0b101101) + chr(969 - 913)))(C4IqNNmLfHXB, AIvJRzLdDfgF, if_exists=zZFPtODM90fp, index=XdowRbJKZWL9, index_label=Rj5_q03bvJPB, schema=P7DmIFVRivx6, chunksize=op94qe_Rdjul, dtype=jSV9IKnemH7K, method=CVRCXTcnOnH6)
|
pandas-dev/pandas
|
pandas/io/sql.py
|
has_table
|
def has_table(table_name, con, schema=None):
"""
Check if DataBase has named table.
Parameters
----------
table_name: string
Name of SQL table.
con: SQLAlchemy connectable(engine/connection) or sqlite3 DBAPI2 connection
Using SQLAlchemy makes it possible to use any DB supported by that
library.
If a DBAPI2 object, only sqlite3 is supported.
schema : string, default None
Name of SQL schema in database to write to (if database flavor supports
this). If None, use default schema (default).
Returns
-------
boolean
"""
pandas_sql = pandasSQL_builder(con, schema=schema)
return pandas_sql.has_table(table_name)
|
python
|
def has_table(table_name, con, schema=None):
"""
Check if DataBase has named table.
Parameters
----------
table_name: string
Name of SQL table.
con: SQLAlchemy connectable(engine/connection) or sqlite3 DBAPI2 connection
Using SQLAlchemy makes it possible to use any DB supported by that
library.
If a DBAPI2 object, only sqlite3 is supported.
schema : string, default None
Name of SQL schema in database to write to (if database flavor supports
this). If None, use default schema (default).
Returns
-------
boolean
"""
pandas_sql = pandasSQL_builder(con, schema=schema)
return pandas_sql.has_table(table_name)
|
[
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Check if DataBase has named table.
Parameters
----------
table_name: string
Name of SQL table.
con: SQLAlchemy connectable(engine/connection) or sqlite3 DBAPI2 connection
Using SQLAlchemy makes it possible to use any DB supported by that
library.
If a DBAPI2 object, only sqlite3 is supported.
schema : string, default None
Name of SQL schema in database to write to (if database flavor supports
this). If None, use default schema (default).
Returns
-------
boolean
|
[
"Check",
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"has",
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"table",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/io/sql.py#L454-L475
|
train
|
Check if DataBase has named table.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x34' + '\063', 0b1000), ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(1944 - 1833) + chr(0b100100 + 0o16) + '\x32', ord("\x08")), ehT0Px3KOsy9('\060' + chr(637 - 526) + chr(1472 - 1423) + chr(49) + chr(320 - 266), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b10 + 0o60) + chr(0b110101) + chr(55), 44408 - 44400), ehT0Px3KOsy9(chr(0b100001 + 0o17) + '\157' + chr(593 - 544) + chr(1489 - 1435) + '\062', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1100100 + 0o13) + chr(53) + '\x36', 1951 - 1943), ehT0Px3KOsy9(chr(889 - 841) + chr(11823 - 11712) + chr(51) + '\x35' + chr(0b110010), 20784 - 20776), ehT0Px3KOsy9(chr(48) + chr(0b1100000 + 0o17) + '\062' + chr(0b100101 + 0o16) + '\065', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x32' + '\x35' + '\x32', 36997 - 36989), ehT0Px3KOsy9(chr(0b11000 + 0o30) + chr(7980 - 7869) + chr(51) + chr(48) + chr(2405 - 2350), 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(0b100000 + 0o22) + '\065' + chr(0b101110 + 0o10), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + '\062' + chr(0b110110) + chr(2341 - 2291), 34849 - 34841), ehT0Px3KOsy9(chr(0b10000 + 0o40) + '\x6f' + chr(0b1 + 0o60) + chr(0b110100) + '\062', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b110100 + 0o73) + chr(552 - 499), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1011000 + 0o27) + '\061' + chr(0b110010) + '\x33', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110001 + 0o1) + '\063' + chr(2235 - 2183), 3293 - 3285), ehT0Px3KOsy9('\060' + '\157' + chr(0b110 + 0o53) + chr(0b110101) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(2268 - 2220) + chr(6303 - 6192) + chr(0b110011) + '\x35' + chr(0b110001), ord("\x08")), ehT0Px3KOsy9(chr(0b100 + 0o54) + chr(0b1101111) + chr(0b10000 + 0o42) + chr(0b110110), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b11000 + 0o32) + chr(55) + chr(0b1100 + 0o45), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110010) + chr(0b110110), 8), ehT0Px3KOsy9(chr(691 - 643) + '\x6f' + chr(51) + chr(0b110010) + chr(0b11 + 0o60), 50072 - 50064), ehT0Px3KOsy9(chr(1236 - 1188) + chr(0b1101111) + chr(50) + chr(2472 - 2422) + chr(0b110111), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b10000 + 0o137) + chr(53) + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1000101 + 0o52) + chr(0b110010) + chr(842 - 787) + '\x32', ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110010) + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(1776 - 1726) + chr(0b110011) + chr(50), ord("\x08")), ehT0Px3KOsy9(chr(1894 - 1846) + chr(111) + chr(0b110011) + chr(0b1110 + 0o45) + '\065', 0b1000), ehT0Px3KOsy9(chr(1804 - 1756) + chr(0b1101100 + 0o3) + '\062' + '\066' + '\x32', 8), ehT0Px3KOsy9('\x30' + '\x6f' + '\061' + '\x36' + chr(1834 - 1785), ord("\x08")), ehT0Px3KOsy9(chr(1711 - 1663) + '\157' + chr(0b101111 + 0o3) + chr(0b110110) + chr(0b10100 + 0o42), ord("\x08")), ehT0Px3KOsy9(chr(0b1101 + 0o43) + '\x6f' + '\x33' + '\x37' + chr(0b110101), 14347 - 14339), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x36', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b11011 + 0o124) + chr(51) + '\062' + chr(0b10001 + 0o40), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(51), ord("\x08")), ehT0Px3KOsy9(chr(1476 - 1428) + chr(0b1001010 + 0o45) + chr(49) + '\x33' + chr(622 - 573), 0b1000), ehT0Px3KOsy9(chr(0b101111 + 0o1) + '\x6f' + chr(0b110011) + chr(50) + '\067', ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + '\x31' + chr(55) + '\060', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(51) + chr(50) + chr(48), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110010) + chr(1958 - 1905) + chr(0b110101 + 0o0), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(53) + chr(1389 - 1341), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\r'), chr(100) + chr(0b1011101 + 0o10) + chr(99) + chr(111) + '\x64' + '\145')(chr(0b1110101) + chr(5532 - 5416) + '\x66' + chr(0b101101) + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def Qd97IG25xIDy(NKKFbr2Z4sr1, _sqfVuM76EP3, P7DmIFVRivx6=None):
Re4ydlckRnKx = Hm7TAp8orHi4(_sqfVuM76EP3, schema=P7DmIFVRivx6)
return xafqLlk3kkUe(Re4ydlckRnKx, xafqLlk3kkUe(SXOLrMavuUCe(b'Ks=\xf0\x06O\x88\xf1\xcf'), '\144' + '\x65' + chr(5589 - 5490) + chr(6705 - 6594) + chr(0b1100100) + '\145')('\x75' + '\x74' + '\x66' + chr(0b101101) + '\070'))(NKKFbr2Z4sr1)
|
pandas-dev/pandas
|
pandas/io/sql.py
|
_engine_builder
|
def _engine_builder(con):
"""
Returns a SQLAlchemy engine from a URI (if con is a string)
else it just return con without modifying it.
"""
global _SQLALCHEMY_INSTALLED
if isinstance(con, str):
try:
import sqlalchemy
except ImportError:
_SQLALCHEMY_INSTALLED = False
else:
con = sqlalchemy.create_engine(con)
return con
return con
|
python
|
def _engine_builder(con):
"""
Returns a SQLAlchemy engine from a URI (if con is a string)
else it just return con without modifying it.
"""
global _SQLALCHEMY_INSTALLED
if isinstance(con, str):
try:
import sqlalchemy
except ImportError:
_SQLALCHEMY_INSTALLED = False
else:
con = sqlalchemy.create_engine(con)
return con
return con
|
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] |
Returns a SQLAlchemy engine from a URI (if con is a string)
else it just return con without modifying it.
|
[
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] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/io/sql.py#L481-L496
|
train
|
Returns a SQLAlchemy engine from a URI if con is a string else it just return con without modifying it.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b11100 + 0o24) + '\x6f' + chr(2096 - 2045) + '\x33' + chr(0b100101 + 0o20), 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110011) + chr(0b101000 + 0o16) + '\066', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110011) + chr(0b101001 + 0o15) + chr(53), 2446 - 2438), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101010 + 0o5) + '\x32' + '\x36' + chr(48), 43153 - 43145), ehT0Px3KOsy9(chr(48) + chr(4502 - 4391) + chr(2552 - 2497) + chr(51), 0o10), ehT0Px3KOsy9(chr(0b10010 + 0o36) + '\x6f' + chr(0b110001) + chr(0b110100) + chr(2113 - 2064), 0o10), ehT0Px3KOsy9(chr(0b100100 + 0o14) + '\x6f' + chr(1416 - 1367) + '\x32' + chr(48), ord("\x08")), ehT0Px3KOsy9('\060' + chr(10779 - 10668) + '\063' + '\064' + chr(0b110001), 0o10), ehT0Px3KOsy9('\060' + chr(928 - 817) + chr(2587 - 2533) + chr(0b10001 + 0o40), 16580 - 16572), ehT0Px3KOsy9(chr(0b110000) + chr(2869 - 2758) + chr(952 - 902) + chr(52) + chr(1497 - 1442), 25389 - 25381), ehT0Px3KOsy9('\x30' + chr(0b11100 + 0o123) + chr(0b101110 + 0o5) + chr(0b100110 + 0o21), 0o10), ehT0Px3KOsy9(chr(1797 - 1749) + '\x6f' + '\062' + '\063' + '\x30', 43487 - 43479), ehT0Px3KOsy9(chr(48) + '\157' + chr(116 - 66) + chr(55) + '\x33', 42662 - 42654), ehT0Px3KOsy9(chr(248 - 200) + chr(0b11010 + 0o125) + chr(0b100000 + 0o23) + chr(53) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1100111 + 0o10) + chr(49) + chr(0b110001) + chr(54), 37144 - 37136), ehT0Px3KOsy9(chr(1602 - 1554) + '\x6f' + chr(0b110001 + 0o4) + '\x36', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1011011 + 0o24) + '\063' + chr(55) + '\x33', ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(0b10 + 0o61) + chr(1741 - 1686) + '\x31', ord("\x08")), ehT0Px3KOsy9(chr(534 - 486) + chr(0b1101111) + chr(50) + chr(1919 - 1864) + '\x34', 30135 - 30127), ehT0Px3KOsy9(chr(0b110000) + chr(8123 - 8012) + '\061' + chr(0b110011) + '\061', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1010101 + 0o32) + chr(49) + chr(406 - 354) + chr(54), 46154 - 46146), ehT0Px3KOsy9(chr(1139 - 1091) + '\x6f' + chr(0b110010) + chr(49) + chr(0b110100), 0o10), ehT0Px3KOsy9(chr(498 - 450) + chr(0b1100 + 0o143) + chr(1707 - 1659), 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(0b101010 + 0o10) + '\x35' + '\x35', 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(87 - 38) + '\063' + chr(52), 55318 - 55310), ehT0Px3KOsy9(chr(0b110000) + chr(5455 - 5344) + chr(49) + chr(0b110011) + chr(1952 - 1901), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + '\x33' + '\060' + '\063', 0o10), ehT0Px3KOsy9('\060' + chr(0b1101011 + 0o4) + chr(0b11010 + 0o31) + chr(52) + chr(0b100001 + 0o22), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(51) + '\x37' + '\x36', 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(49) + '\064' + chr(51), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b1 + 0o61) + chr(55) + chr(53), 57401 - 57393), ehT0Px3KOsy9(chr(48) + '\157' + '\062' + chr(0b110001 + 0o6) + chr(128 - 78), 0b1000), ehT0Px3KOsy9('\x30' + chr(10888 - 10777) + chr(0b110001) + '\x37' + '\x34', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(51) + chr(876 - 828) + chr(0b110010), 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(0b110011 + 0o4) + chr(48), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + '\x33' + '\x31' + chr(0b101011 + 0o13), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b101101 + 0o10) + chr(922 - 872), 0o10), ehT0Px3KOsy9('\060' + chr(877 - 766) + chr(49) + chr(2054 - 2001) + chr(1429 - 1381), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(49) + chr(0b111 + 0o54), 44899 - 44891), ehT0Px3KOsy9(chr(0b110000) + chr(3527 - 3416) + chr(0b110011) + chr(0b110100), 28227 - 28219)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + '\x6f' + chr(53) + chr(0b11100 + 0o24), 52144 - 52136)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xf3'), chr(0b110000 + 0o64) + chr(0b1100101) + chr(4301 - 4202) + chr(6000 - 5889) + '\144' + chr(101))('\165' + chr(116) + chr(102) + chr(0b11011 + 0o22) + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def NcAk05ebjpoG(_sqfVuM76EP3):
global raxlEYdyOWpM
if PlSM16l2KDPD(_sqfVuM76EP3, M8_cKLkHVB2V):
try:
(PiAb9sTkjfM_,) = (jFWsnpHpAUWz(xafqLlk3kkUe(SXOLrMavuUCe(b'\xae\x87\x99\xd1W\x028\x84\\\xde'), chr(0b1100100) + chr(0b111010 + 0o53) + '\143' + '\157' + '\144' + '\145')(chr(117) + '\164' + '\146' + '\x2d' + '\x38')),)
except yROw0HWBk0Qc:
raxlEYdyOWpM = ehT0Px3KOsy9(chr(0b110000) + chr(0b111000 + 0o67) + chr(0b110000), 8)
else:
_sqfVuM76EP3 = PiAb9sTkjfM_.create_engine(_sqfVuM76EP3)
return _sqfVuM76EP3
return _sqfVuM76EP3
|
pandas-dev/pandas
|
pandas/io/sql.py
|
pandasSQL_builder
|
def pandasSQL_builder(con, schema=None, meta=None,
is_cursor=False):
"""
Convenience function to return the correct PandasSQL subclass based on the
provided parameters.
"""
# When support for DBAPI connections is removed,
# is_cursor should not be necessary.
con = _engine_builder(con)
if _is_sqlalchemy_connectable(con):
return SQLDatabase(con, schema=schema, meta=meta)
elif isinstance(con, str):
raise ImportError("Using URI string without sqlalchemy installed.")
else:
return SQLiteDatabase(con, is_cursor=is_cursor)
|
python
|
def pandasSQL_builder(con, schema=None, meta=None,
is_cursor=False):
"""
Convenience function to return the correct PandasSQL subclass based on the
provided parameters.
"""
# When support for DBAPI connections is removed,
# is_cursor should not be necessary.
con = _engine_builder(con)
if _is_sqlalchemy_connectable(con):
return SQLDatabase(con, schema=schema, meta=meta)
elif isinstance(con, str):
raise ImportError("Using URI string without sqlalchemy installed.")
else:
return SQLiteDatabase(con, is_cursor=is_cursor)
|
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] |
Convenience function to return the correct PandasSQL subclass based on the
provided parameters.
|
[
"Convenience",
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"correct",
"PandasSQL",
"subclass",
"based",
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"parameters",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/io/sql.py#L499-L513
|
train
|
Convenience function to return the correct PandasSQL subclass based on the provided parameters.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\063' + '\x37' + chr(426 - 377), 22196 - 22188), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(497 - 448) + chr(0b10001 + 0o41) + chr(0b110111), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110001) + chr(408 - 356) + '\061', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1001000 + 0o47) + chr(0b11001 + 0o33) + chr(0b110110), ord("\x08")), ehT0Px3KOsy9(chr(292 - 244) + chr(6631 - 6520) + chr(738 - 688) + chr(0b101100 + 0o6) + '\062', 0o10), ehT0Px3KOsy9(chr(285 - 237) + chr(111) + '\x33' + chr(0b111 + 0o54) + '\060', 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110011) + chr(0b1100 + 0o50), 0b1000), ehT0Px3KOsy9(chr(0b101011 + 0o5) + '\x6f' + chr(0b10011 + 0o44) + chr(2434 - 2380), 0o10), ehT0Px3KOsy9(chr(1486 - 1438) + chr(0b1010010 + 0o35) + '\061' + chr(1570 - 1515) + '\x34', 0o10), ehT0Px3KOsy9(chr(0b10011 + 0o35) + '\x6f' + '\x31', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(11488 - 11377) + chr(49) + chr(0b110110) + chr(0b11100 + 0o33), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1100111 + 0o10) + chr(661 - 612) + chr(53) + chr(0b110110), ord("\x08")), ehT0Px3KOsy9(chr(0b100001 + 0o17) + chr(3409 - 3298) + chr(50) + '\064' + chr(0b110110), ord("\x08")), ehT0Px3KOsy9(chr(1954 - 1906) + chr(0b1101111) + '\x32' + chr(2701 - 2646), 0b1000), ehT0Px3KOsy9('\060' + '\157' + '\x31' + '\x33' + chr(1700 - 1651), 15011 - 15003), ehT0Px3KOsy9(chr(0b1110 + 0o42) + chr(0b11100 + 0o123) + chr(0b110011) + chr(2095 - 2042) + chr(0b11010 + 0o35), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(814 - 763) + '\061' + chr(0b100010 + 0o25), 0o10), ehT0Px3KOsy9('\060' + chr(6142 - 6031) + chr(0b1011 + 0o47) + '\063' + chr(0b1100 + 0o51), 0b1000), ehT0Px3KOsy9(chr(0b101010 + 0o6) + chr(111) + chr(0b11001 + 0o32) + chr(49) + chr(52), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1011100 + 0o23) + '\061' + chr(0b101111 + 0o2) + chr(0b110001), 0o10), ehT0Px3KOsy9('\060' + chr(10078 - 9967) + '\064' + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(933 - 885) + '\x6f' + chr(0b10010 + 0o40) + '\x33' + chr(0b1 + 0o64), 8), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(1671 - 1622) + chr(0b10110 + 0o33) + chr(0b110010 + 0o4), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b101101 + 0o11), 27863 - 27855), ehT0Px3KOsy9(chr(0b10111 + 0o31) + '\157' + chr(0b110110) + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(1986 - 1938) + chr(0b1101111) + chr(0b101010 + 0o11) + chr(1106 - 1058) + chr(0b110 + 0o61), 0b1000), ehT0Px3KOsy9('\060' + '\157' + '\062' + '\065', ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + '\x31' + '\x35' + chr(0b100010 + 0o16), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\062' + chr(534 - 484) + chr(0b10110 + 0o32), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + '\x31' + chr(0b110101) + '\x35', 50852 - 50844), ehT0Px3KOsy9(chr(0b10000 + 0o40) + '\157' + '\x31' + chr(2110 - 2058), 0b1000), ehT0Px3KOsy9(chr(0b101111 + 0o1) + chr(10235 - 10124) + '\x32' + '\x37', 8), ehT0Px3KOsy9(chr(1843 - 1795) + '\x6f' + chr(0b11001 + 0o30) + '\x32', 60018 - 60010), ehT0Px3KOsy9(chr(0b10001 + 0o37) + chr(410 - 299) + chr(0b110010) + chr(52) + chr(0b11010 + 0o35), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + '\062' + chr(0b101011 + 0o7) + chr(1648 - 1596), 0o10), ehT0Px3KOsy9('\060' + chr(9141 - 9030) + '\x31' + chr(54) + chr(0b110000 + 0o6), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(5594 - 5483) + chr(0b110001) + chr(0b1011 + 0o52) + '\064', 0b1000), ehT0Px3KOsy9('\060' + chr(2932 - 2821) + '\x31' + chr(1514 - 1461) + chr(0b101001 + 0o16), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + '\063' + chr(0b110011) + '\x37', 27344 - 27336), ehT0Px3KOsy9('\x30' + '\157' + chr(51) + chr(52) + chr(54), 17593 - 17585)][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + chr(111) + chr(53) + '\060', 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xd7'), chr(4620 - 4520) + '\145' + chr(99) + chr(1563 - 1452) + '\144' + chr(5130 - 5029))('\x75' + chr(3784 - 3668) + '\x66' + chr(1053 - 1008) + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def Hm7TAp8orHi4(_sqfVuM76EP3, P7DmIFVRivx6=None, Ddxy_ihdYXS3=None, XZeymUwWp6JJ=ehT0Px3KOsy9(chr(1334 - 1286) + chr(0b1101111) + '\x30', 0o10)):
_sqfVuM76EP3 = NcAk05ebjpoG(_sqfVuM76EP3)
if Q1dJV0ss0eny(_sqfVuM76EP3):
return APbCRgLa2CC0(_sqfVuM76EP3, schema=P7DmIFVRivx6, meta=Ddxy_ihdYXS3)
elif PlSM16l2KDPD(_sqfVuM76EP3, M8_cKLkHVB2V):
raise yROw0HWBk0Qc(xafqLlk3kkUe(SXOLrMavuUCe(b'\xac$\x08H\xf5\xf8Il5!\x04\x1a\xd4~7\x88\xef\xea\xa5=H\xf2;r\x10\xb4d\x04\xf1\x01o\x7fo\xca\xedV\x05\x01\xac\x92\x98;\rC\xf6\xf6'), chr(0b101111 + 0o65) + chr(101) + '\x63' + '\157' + chr(100) + chr(101))(chr(0b1110101) + chr(116) + chr(0b1100110) + chr(0b0 + 0o55) + chr(0b111000)))
else:
return bPxPu_8gzhG3(_sqfVuM76EP3, is_cursor=XZeymUwWp6JJ)
|
pandas-dev/pandas
|
pandas/io/sql.py
|
get_schema
|
def get_schema(frame, name, keys=None, con=None, dtype=None):
"""
Get the SQL db table schema for the given frame.
Parameters
----------
frame : DataFrame
name : string
name of SQL table
keys : string or sequence, default: None
columns to use a primary key
con: an open SQL database connection object or a SQLAlchemy connectable
Using SQLAlchemy makes it possible to use any DB supported by that
library, default: None
If a DBAPI2 object, only sqlite3 is supported.
dtype : dict of column name to SQL type, default None
Optional specifying the datatype for columns. The SQL type should
be a SQLAlchemy type, or a string for sqlite3 fallback connection.
"""
pandas_sql = pandasSQL_builder(con=con)
return pandas_sql._create_sql_schema(frame, name, keys=keys, dtype=dtype)
|
python
|
def get_schema(frame, name, keys=None, con=None, dtype=None):
"""
Get the SQL db table schema for the given frame.
Parameters
----------
frame : DataFrame
name : string
name of SQL table
keys : string or sequence, default: None
columns to use a primary key
con: an open SQL database connection object or a SQLAlchemy connectable
Using SQLAlchemy makes it possible to use any DB supported by that
library, default: None
If a DBAPI2 object, only sqlite3 is supported.
dtype : dict of column name to SQL type, default None
Optional specifying the datatype for columns. The SQL type should
be a SQLAlchemy type, or a string for sqlite3 fallback connection.
"""
pandas_sql = pandasSQL_builder(con=con)
return pandas_sql._create_sql_schema(frame, name, keys=keys, dtype=dtype)
|
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",",
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",",
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"=",
"keys",
",",
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"dtype",
")"
] |
Get the SQL db table schema for the given frame.
Parameters
----------
frame : DataFrame
name : string
name of SQL table
keys : string or sequence, default: None
columns to use a primary key
con: an open SQL database connection object or a SQLAlchemy connectable
Using SQLAlchemy makes it possible to use any DB supported by that
library, default: None
If a DBAPI2 object, only sqlite3 is supported.
dtype : dict of column name to SQL type, default None
Optional specifying the datatype for columns. The SQL type should
be a SQLAlchemy type, or a string for sqlite3 fallback connection.
|
[
"Get",
"the",
"SQL",
"db",
"table",
"schema",
"for",
"the",
"given",
"frame",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/io/sql.py#L1564-L1586
|
train
|
Returns the SQL db table schema for the given DataFrame.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(1958 - 1910) + chr(0b1101111) + '\x33' + '\x32' + chr(0b100011 + 0o16), 0b1000), ehT0Px3KOsy9(chr(0b11100 + 0o24) + chr(0b1010111 + 0o30) + chr(0b101110 + 0o3) + '\065' + '\061', ord("\x08")), ehT0Px3KOsy9(chr(0b11110 + 0o22) + '\157' + chr(50) + chr(0b10011 + 0o44) + chr(0b110110), ord("\x08")), ehT0Px3KOsy9(chr(979 - 931) + chr(0b1010101 + 0o32) + chr(0b110010) + chr(50) + chr(0b10101 + 0o36), 0o10), ehT0Px3KOsy9(chr(99 - 51) + chr(0b1101111) + chr(53) + chr(0b11100 + 0o27), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + '\x32' + '\x35', 0o10), ehT0Px3KOsy9(chr(0b111 + 0o51) + chr(711 - 600) + chr(1302 - 1252) + '\x33' + chr(0b110001), 31714 - 31706), ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(924 - 813) + '\063' + chr(457 - 402), 43976 - 43968), ehT0Px3KOsy9('\060' + chr(111) + '\061' + chr(418 - 368) + chr(0b110101), 0b1000), ehT0Px3KOsy9('\060' + '\157' + '\063' + '\066' + '\x36', 0b1000), ehT0Px3KOsy9(chr(0b110000 + 0o0) + '\x6f' + chr(0b110010) + '\063' + '\066', 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(1908 - 1857) + '\x31' + chr(125 - 76), 27464 - 27456), ehT0Px3KOsy9(chr(0b101000 + 0o10) + chr(3043 - 2932) + '\x33' + chr(0b101 + 0o53) + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(51) + chr(0b110011), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b1101 + 0o44) + '\064' + '\x37', 0b1000), ehT0Px3KOsy9('\x30' + chr(10105 - 9994) + chr(0b11111 + 0o30) + chr(989 - 936), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + '\x32' + '\066' + chr(48), 63324 - 63316), ehT0Px3KOsy9('\x30' + '\157' + '\062' + chr(0b110100 + 0o1) + '\061', 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + '\061' + '\062' + chr(0b110110), 0b1000), ehT0Px3KOsy9(chr(2010 - 1962) + '\x6f' + chr(0b110001) + chr(0b10100 + 0o34) + chr(798 - 746), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b11110 + 0o121) + '\062' + chr(0b101011 + 0o14) + '\067', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(9278 - 9167) + chr(50) + '\x36' + '\061', 44565 - 44557), ehT0Px3KOsy9(chr(48) + chr(0b1100101 + 0o12) + chr(191 - 141) + chr(2808 - 2753) + chr(0b110100), ord("\x08")), ehT0Px3KOsy9(chr(0b1010 + 0o46) + chr(111) + chr(1107 - 1055) + '\061', ord("\x08")), ehT0Px3KOsy9(chr(0b1 + 0o57) + chr(111) + chr(49) + chr(0b100010 + 0o24) + chr(1490 - 1441), ord("\x08")), ehT0Px3KOsy9('\060' + chr(2697 - 2586) + '\x31' + '\x31' + chr(0b101010 + 0o7), 52792 - 52784), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110010) + chr(52) + chr(0b11110 + 0o23), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + '\066' + chr(0b110100), ord("\x08")), ehT0Px3KOsy9(chr(0b111 + 0o51) + chr(0b1000101 + 0o52) + chr(2202 - 2152) + chr(0b100011 + 0o15) + chr(1502 - 1454), 0o10), ehT0Px3KOsy9(chr(0b101010 + 0o6) + '\x6f' + chr(305 - 254) + chr(521 - 472) + '\062', ord("\x08")), ehT0Px3KOsy9(chr(824 - 776) + '\x6f' + '\x34' + chr(0b11100 + 0o26), 0b1000), ehT0Px3KOsy9(chr(0b11111 + 0o21) + chr(111) + chr(50) + '\x34' + chr(0b110001), 8), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\063' + '\x36' + chr(0b10000 + 0o46), 8), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b10011 + 0o44) + '\x30', 30082 - 30074), ehT0Px3KOsy9(chr(0b10 + 0o56) + chr(0b110100 + 0o73) + chr(0b110010) + chr(0b110110) + chr(596 - 542), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\063' + chr(1262 - 1209), 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110001) + '\064' + '\x35', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(1590 - 1540) + '\067', 55962 - 55954), ehT0Px3KOsy9('\x30' + '\x6f' + chr(2339 - 2288) + '\x36' + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\066', ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110101) + chr(1823 - 1775), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xff'), chr(4678 - 4578) + chr(101) + chr(5740 - 5641) + chr(0b1101111) + chr(6787 - 6687) + '\145')(chr(0b1110101) + chr(8708 - 8592) + chr(0b1100110) + chr(45) + chr(2905 - 2849)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def QMSANZNiT5L0(C4IqNNmLfHXB, AIvJRzLdDfgF, w8H8C9ec5BO1=None, _sqfVuM76EP3=None, jSV9IKnemH7K=None):
Re4ydlckRnKx = Hm7TAp8orHi4(con=_sqfVuM76EP3)
return xafqLlk3kkUe(Re4ydlckRnKx, xafqLlk3kkUe(SXOLrMavuUCe(b'\x8e\n\xcc\xf6Ja\xfc@&\x87\xf2\x96\xb0x\x0fX\xdd\xc8'), chr(7677 - 7577) + '\145' + '\x63' + chr(9040 - 8929) + chr(0b1100100) + chr(0b1100100 + 0o1))(chr(0b1110101) + chr(0b1110100) + chr(0b1100110) + '\x2d' + chr(0b111000)))(C4IqNNmLfHXB, AIvJRzLdDfgF, keys=w8H8C9ec5BO1, dtype=jSV9IKnemH7K)
|
pandas-dev/pandas
|
pandas/io/sql.py
|
SQLTable._execute_insert
|
def _execute_insert(self, conn, keys, data_iter):
"""Execute SQL statement inserting data
Parameters
----------
conn : sqlalchemy.engine.Engine or sqlalchemy.engine.Connection
keys : list of str
Column names
data_iter : generator of list
Each item contains a list of values to be inserted
"""
data = [dict(zip(keys, row)) for row in data_iter]
conn.execute(self.table.insert(), data)
|
python
|
def _execute_insert(self, conn, keys, data_iter):
"""Execute SQL statement inserting data
Parameters
----------
conn : sqlalchemy.engine.Engine or sqlalchemy.engine.Connection
keys : list of str
Column names
data_iter : generator of list
Each item contains a list of values to be inserted
"""
data = [dict(zip(keys, row)) for row in data_iter]
conn.execute(self.table.insert(), data)
|
[
"def",
"_execute_insert",
"(",
"self",
",",
"conn",
",",
"keys",
",",
"data_iter",
")",
":",
"data",
"=",
"[",
"dict",
"(",
"zip",
"(",
"keys",
",",
"row",
")",
")",
"for",
"row",
"in",
"data_iter",
"]",
"conn",
".",
"execute",
"(",
"self",
".",
"table",
".",
"insert",
"(",
")",
",",
"data",
")"
] |
Execute SQL statement inserting data
Parameters
----------
conn : sqlalchemy.engine.Engine or sqlalchemy.engine.Connection
keys : list of str
Column names
data_iter : generator of list
Each item contains a list of values to be inserted
|
[
"Execute",
"SQL",
"statement",
"inserting",
"data"
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/io/sql.py#L578-L590
|
train
|
Execute SQL statement inserting data
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(614 - 566) + '\x6f' + '\061' + chr(51) + '\x33', 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110010) + chr(0b110110 + 0o0) + '\063', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x33' + '\x30' + chr(51), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b11101 + 0o122) + '\x32' + chr(0b111 + 0o60) + '\060', 0o10), ehT0Px3KOsy9(chr(0b100010 + 0o16) + chr(0b1101111) + chr(50) + '\060' + '\x36', 65387 - 65379), ehT0Px3KOsy9(chr(48) + chr(0b1100110 + 0o11) + chr(0b101011 + 0o6) + '\061' + '\x37', 6110 - 6102), ehT0Px3KOsy9(chr(48) + chr(378 - 267) + chr(0b110100 + 0o2) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(111) + chr(775 - 726) + chr(902 - 848) + chr(0b110110), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(51) + '\064' + chr(0b110010), 55728 - 55720), ehT0Px3KOsy9('\x30' + '\157' + chr(51) + chr(0b110001) + chr(0b10101 + 0o41), 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b101101 + 0o6) + chr(1662 - 1607) + '\064', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(2860 - 2749) + chr(850 - 801) + chr(0b10 + 0o65), 25156 - 25148), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(55) + chr(0b110100), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + '\x35' + chr(0b11000 + 0o33), 57750 - 57742), ehT0Px3KOsy9(chr(0b1100 + 0o44) + chr(0b1101111) + chr(532 - 480) + chr(0b110111), 4334 - 4326), ehT0Px3KOsy9('\060' + '\157' + chr(0b1111 + 0o43) + chr(0b110010) + '\063', 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110001) + chr(0b110100) + '\064', ord("\x08")), ehT0Px3KOsy9(chr(1993 - 1945) + chr(111) + chr(2239 - 2190) + chr(0b110101) + chr(0b1110 + 0o50), ord("\x08")), ehT0Px3KOsy9(chr(1192 - 1144) + chr(0b1101111) + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b100101 + 0o112) + '\063' + chr(1879 - 1829) + chr(227 - 174), 37900 - 37892), ehT0Px3KOsy9('\x30' + chr(111) + '\x33' + chr(2304 - 2255) + '\063', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\062' + '\062' + chr(2304 - 2256), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(2214 - 2164) + chr(53) + chr(0b110111), ord("\x08")), ehT0Px3KOsy9(chr(0b111 + 0o51) + chr(4242 - 4131) + chr(0b1111 + 0o44) + chr(1110 - 1056) + chr(55), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(835 - 785) + chr(0b110101) + chr(1552 - 1501), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b10 + 0o57) + chr(1962 - 1914) + chr(0b100001 + 0o23), 0b1000), ehT0Px3KOsy9(chr(48) + chr(620 - 509) + chr(0b10100 + 0o36) + chr(0b110100 + 0o2) + chr(0b10101 + 0o40), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110100) + chr(0b110101), 0b1000), ehT0Px3KOsy9(chr(0b10100 + 0o34) + chr(111) + chr(718 - 667) + chr(0b111 + 0o55) + chr(50), 8), ehT0Px3KOsy9(chr(432 - 384) + chr(0b101 + 0o152) + '\063' + chr(0b11101 + 0o23) + chr(0b11010 + 0o34), 0b1000), ehT0Px3KOsy9(chr(0b111 + 0o51) + chr(11712 - 11601) + '\063' + chr(2225 - 2171) + chr(51), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\061' + '\x32' + '\065', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x32' + chr(0b110100) + chr(0b10000 + 0o43), 0b1000), ehT0Px3KOsy9('\x30' + chr(8231 - 8120) + chr(1497 - 1448) + '\063' + chr(0b110100), ord("\x08")), ehT0Px3KOsy9(chr(0b101001 + 0o7) + '\157' + chr(0b10 + 0o61) + chr(2169 - 2115) + chr(0b101010 + 0o12), 0b1000), ehT0Px3KOsy9('\060' + chr(0b111100 + 0o63) + '\x33' + chr(641 - 592) + '\062', 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + '\x33' + chr(0b110011 + 0o1) + chr(0b10100 + 0o43), 17055 - 17047), ehT0Px3KOsy9('\x30' + chr(111) + '\062' + '\x35' + chr(0b100 + 0o61), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1000000 + 0o57) + '\x33' + chr(2227 - 2177) + '\061', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(53) + chr(0b10110 + 0o37), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x35' + chr(1120 - 1072), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'u'), '\x64' + '\145' + chr(0b100101 + 0o76) + chr(111) + chr(5556 - 5456) + chr(0b1100101))(chr(11910 - 11793) + '\x74' + '\x66' + '\055' + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def blQ6hN2LG7pV(oVre8I6UXc3b, npwjCV10gdob, w8H8C9ec5BO1, Qlm2mKMkeI3e):
ULnjp6D6efFH = [wLqBDw8l0eIm(pZ0NK2y6HRbn(w8H8C9ec5BO1, TAK9K32TkBdA)) for TAK9K32TkBdA in Qlm2mKMkeI3e]
xafqLlk3kkUe(npwjCV10gdob, xafqLlk3kkUe(SXOLrMavuUCe(b'>\xcb\xa6\xdb\xf3;P'), chr(0b1100100) + chr(0b1100101) + '\143' + chr(0b1010000 + 0o37) + chr(0b10110 + 0o116) + chr(5748 - 5647))('\165' + chr(679 - 563) + '\146' + chr(936 - 891) + chr(0b10000 + 0o50)))(xafqLlk3kkUe(oVre8I6UXc3b.table, xafqLlk3kkUe(SXOLrMavuUCe(b'2\xdd\xb0\xdd\xf4;'), '\x64' + '\x65' + '\143' + '\x6f' + chr(6107 - 6007) + '\x65')(chr(0b1110101) + chr(116) + chr(7422 - 7320) + '\x2d' + chr(2619 - 2563)))(), ULnjp6D6efFH)
|
pandas-dev/pandas
|
pandas/io/sql.py
|
SQLTable._query_iterator
|
def _query_iterator(self, result, chunksize, columns, coerce_float=True,
parse_dates=None):
"""Return generator through chunked result set."""
while True:
data = result.fetchmany(chunksize)
if not data:
break
else:
self.frame = DataFrame.from_records(
data, columns=columns, coerce_float=coerce_float)
self._harmonize_columns(parse_dates=parse_dates)
if self.index is not None:
self.frame.set_index(self.index, inplace=True)
yield self.frame
|
python
|
def _query_iterator(self, result, chunksize, columns, coerce_float=True,
parse_dates=None):
"""Return generator through chunked result set."""
while True:
data = result.fetchmany(chunksize)
if not data:
break
else:
self.frame = DataFrame.from_records(
data, columns=columns, coerce_float=coerce_float)
self._harmonize_columns(parse_dates=parse_dates)
if self.index is not None:
self.frame.set_index(self.index, inplace=True)
yield self.frame
|
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")",
":",
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"data",
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"(",
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":",
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",",
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",",
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"=",
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")",
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"(",
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")",
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",",
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")",
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"self",
".",
"frame"
] |
Return generator through chunked result set.
|
[
"Return",
"generator",
"through",
"chunked",
"result",
"set",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/io/sql.py#L679-L696
|
train
|
Return generator through chunked result set.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\x30' + chr(0b1111 + 0o140) + chr(51) + chr(0b110100) + '\061', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x32' + '\066' + '\x36', 64303 - 64295), ehT0Px3KOsy9(chr(0b10011 + 0o35) + chr(0b101000 + 0o107) + chr(671 - 620) + chr(55) + '\062', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1 + 0o156) + chr(0b110010) + '\x36', 0o10), ehT0Px3KOsy9(chr(1580 - 1532) + '\157' + chr(0b10001 + 0o42) + '\x32' + chr(55), 11363 - 11355), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(51) + chr(0b1101 + 0o47) + '\066', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x33' + '\067' + chr(0b10000 + 0o44), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1100010 + 0o15) + '\062' + chr(0b11001 + 0o27) + '\x33', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + '\x35' + chr(0b1011 + 0o51), 0b1000), ehT0Px3KOsy9(chr(0b1001 + 0o47) + chr(6183 - 6072) + chr(0b11011 + 0o27) + '\x31' + chr(0b10010 + 0o44), 19357 - 19349), ehT0Px3KOsy9('\x30' + '\157' + chr(50) + '\x32' + chr(53), 33457 - 33449), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b100000 + 0o21) + chr(0b110010), 31034 - 31026), ehT0Px3KOsy9('\x30' + chr(111) + '\x33' + '\064' + chr(0b11010 + 0o33), 29263 - 29255), ehT0Px3KOsy9('\x30' + chr(3344 - 3233) + chr(0b110 + 0o54) + chr(0b11 + 0o57) + chr(0b100001 + 0o23), 0b1000), ehT0Px3KOsy9(chr(683 - 635) + chr(1752 - 1641) + '\x32' + '\x37' + '\066', 2955 - 2947), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110001) + '\x34' + chr(0b101111 + 0o5), ord("\x08")), ehT0Px3KOsy9(chr(1326 - 1278) + '\157' + '\063' + chr(0b110101) + chr(0b101000 + 0o16), 0b1000), ehT0Px3KOsy9(chr(2131 - 2083) + '\157' + '\061' + chr(1398 - 1349) + chr(0b1001 + 0o56), 43863 - 43855), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110001) + chr(0b110100) + '\x37', 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b100010 + 0o21) + chr(0b1 + 0o57) + chr(0b100011 + 0o15), 0b1000), ehT0Px3KOsy9(chr(667 - 619) + chr(7706 - 7595) + chr(285 - 236) + chr(0b110100) + chr(0b1100 + 0o44), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\061' + chr(0b110100 + 0o3), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(843 - 793) + chr(0b110100) + chr(0b10101 + 0o37), 20510 - 20502), ehT0Px3KOsy9('\060' + chr(6130 - 6019) + chr(0b110001) + '\x37' + chr(0b100011 + 0o23), 49309 - 49301), ehT0Px3KOsy9(chr(0b110000) + chr(0b11010 + 0o125) + chr(0b110011) + chr(0b110111), 0o10), ehT0Px3KOsy9('\x30' + chr(0b11000 + 0o127) + chr(50) + '\x33' + chr(50), 0b1000), ehT0Px3KOsy9(chr(97 - 49) + chr(0b101100 + 0o103) + chr(1665 - 1612) + chr(50), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b1000 + 0o51) + chr(0b11000 + 0o36) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(277 - 226) + '\060' + chr(2489 - 2438), 43608 - 43600), ehT0Px3KOsy9(chr(1080 - 1032) + chr(0b1000001 + 0o56) + '\x33' + chr(0b1100 + 0o53) + chr(50), 8), ehT0Px3KOsy9(chr(0b1111 + 0o41) + chr(111) + chr(0b11001 + 0o31) + chr(0b110000) + chr(0b10001 + 0o44), 51300 - 51292), ehT0Px3KOsy9(chr(0b110 + 0o52) + chr(0b1101111) + chr(0b110010) + '\060' + chr(0b111 + 0o51), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + '\063' + chr(0b110010) + chr(48), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b100111 + 0o12) + chr(1421 - 1366) + '\x32', 0b1000), ehT0Px3KOsy9(chr(0b110000 + 0o0) + chr(111) + '\x31' + '\065' + chr(0b110110), 37307 - 37299), ehT0Px3KOsy9(chr(1401 - 1353) + chr(0b1101111) + chr(0b101101 + 0o7) + '\x32', 0o10), ehT0Px3KOsy9(chr(0b1 + 0o57) + chr(6905 - 6794) + chr(49) + chr(0b110011) + chr(2129 - 2075), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(2276 - 2226) + '\064' + chr(53), ord("\x08")), ehT0Px3KOsy9(chr(393 - 345) + chr(0b1101111) + '\062' + chr(0b101111 + 0o5), 43653 - 43645), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110011) + chr(54) + chr(0b1010 + 0o47), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + chr(0b1100110 + 0o11) + chr(0b11101 + 0o30) + chr(0b10000 + 0o40), 29503 - 29495)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xcf'), chr(391 - 291) + '\x65' + '\x63' + chr(6302 - 6191) + chr(100) + chr(9866 - 9765))(chr(0b1110101) + '\x74' + chr(0b1100110) + '\055' + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def ysyuhdWchnZj(oVre8I6UXc3b, ShZmEKfTkAOZ, op94qe_Rdjul, qKlXBtn3PKy4, hyGdBsLYkQVS=ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110001), 43550 - 43542), T1brfYV34pPD=None):
while ehT0Px3KOsy9(chr(48) + '\x6f' + '\x31', 8):
ULnjp6D6efFH = ShZmEKfTkAOZ.fetchmany(op94qe_Rdjul)
if not ULnjp6D6efFH:
break
else:
oVre8I6UXc3b.C4IqNNmLfHXB = TTWbaLX2VikC.from_records(ULnjp6D6efFH, columns=qKlXBtn3PKy4, coerce_float=hyGdBsLYkQVS)
xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\xbe\xde\x9bd\xba\x89\x92\xeaV\xeb\xcai\x8a\xf8\xcb\t\x80<'), '\x64' + chr(0b1100101) + '\x63' + chr(0b101100 + 0o103) + chr(0b1100100) + chr(0b1100101))(chr(1235 - 1118) + chr(116) + '\146' + chr(0b101101) + chr(0b101100 + 0o14)))(parse_dates=T1brfYV34pPD)
if xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\xb9\xd2\x95a\x85\x84\xb6\xc8v\xd9\xd93'), chr(100) + chr(8601 - 8500) + chr(3902 - 3803) + '\157' + chr(0b1 + 0o143) + chr(1733 - 1632))('\x75' + '\x74' + '\x66' + '\055' + '\070')) is not None:
xafqLlk3kkUe(oVre8I6UXc3b.frame, xafqLlk3kkUe(SXOLrMavuUCe(b'\x92\xd3\x8eI\xbe\x88\x98\xe6T'), chr(100) + '\x65' + '\143' + '\x6f' + chr(0b10001 + 0o123) + '\145')(chr(6749 - 6632) + '\x74' + chr(0b1100110) + chr(1537 - 1492) + chr(0b101001 + 0o17)))(xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\xb9\xd2\x95a\x85\x84\xb6\xc8v\xd9\xd93'), '\144' + chr(2170 - 2069) + chr(0b1000110 + 0o35) + chr(0b1101111) + '\144' + '\x65')(chr(0b110001 + 0o104) + '\164' + chr(0b1100110) + chr(45) + '\070')), inplace=ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b10000 + 0o41), 8))
yield xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\xa2\x82\xb3g\x99\xa8\x91\xcfJ\xc6\xcdH'), chr(0b100111 + 0o75) + chr(1616 - 1515) + chr(0b0 + 0o143) + '\x6f' + chr(0b1100100) + chr(1372 - 1271))(chr(0b11011 + 0o132) + chr(0b1101011 + 0o11) + chr(0b101001 + 0o75) + chr(741 - 696) + chr(56)))
|
pandas-dev/pandas
|
pandas/io/sql.py
|
SQLTable._harmonize_columns
|
def _harmonize_columns(self, parse_dates=None):
"""
Make the DataFrame's column types align with the SQL table
column types.
Need to work around limited NA value support. Floats are always
fine, ints must always be floats if there are Null values.
Booleans are hard because converting bool column with None replaces
all Nones with false. Therefore only convert bool if there are no
NA values.
Datetimes should already be converted to np.datetime64 if supported,
but here we also force conversion if required.
"""
parse_dates = _process_parse_dates_argument(parse_dates)
for sql_col in self.table.columns:
col_name = sql_col.name
try:
df_col = self.frame[col_name]
# Handle date parsing upfront; don't try to convert columns
# twice
if col_name in parse_dates:
try:
fmt = parse_dates[col_name]
except TypeError:
fmt = None
self.frame[col_name] = _handle_date_column(
df_col, format=fmt)
continue
# the type the dataframe column should have
col_type = self._get_dtype(sql_col.type)
if (col_type is datetime or col_type is date or
col_type is DatetimeTZDtype):
# Convert tz-aware Datetime SQL columns to UTC
utc = col_type is DatetimeTZDtype
self.frame[col_name] = _handle_date_column(df_col, utc=utc)
elif col_type is float:
# floats support NA, can always convert!
self.frame[col_name] = df_col.astype(col_type, copy=False)
elif len(df_col) == df_col.count():
# No NA values, can convert ints and bools
if col_type is np.dtype('int64') or col_type is bool:
self.frame[col_name] = df_col.astype(
col_type, copy=False)
except KeyError:
pass
|
python
|
def _harmonize_columns(self, parse_dates=None):
"""
Make the DataFrame's column types align with the SQL table
column types.
Need to work around limited NA value support. Floats are always
fine, ints must always be floats if there are Null values.
Booleans are hard because converting bool column with None replaces
all Nones with false. Therefore only convert bool if there are no
NA values.
Datetimes should already be converted to np.datetime64 if supported,
but here we also force conversion if required.
"""
parse_dates = _process_parse_dates_argument(parse_dates)
for sql_col in self.table.columns:
col_name = sql_col.name
try:
df_col = self.frame[col_name]
# Handle date parsing upfront; don't try to convert columns
# twice
if col_name in parse_dates:
try:
fmt = parse_dates[col_name]
except TypeError:
fmt = None
self.frame[col_name] = _handle_date_column(
df_col, format=fmt)
continue
# the type the dataframe column should have
col_type = self._get_dtype(sql_col.type)
if (col_type is datetime or col_type is date or
col_type is DatetimeTZDtype):
# Convert tz-aware Datetime SQL columns to UTC
utc = col_type is DatetimeTZDtype
self.frame[col_name] = _handle_date_column(df_col, utc=utc)
elif col_type is float:
# floats support NA, can always convert!
self.frame[col_name] = df_col.astype(col_type, copy=False)
elif len(df_col) == df_col.count():
# No NA values, can convert ints and bools
if col_type is np.dtype('int64') or col_type is bool:
self.frame[col_name] = df_col.astype(
col_type, copy=False)
except KeyError:
pass
|
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] |
Make the DataFrame's column types align with the SQL table
column types.
Need to work around limited NA value support. Floats are always
fine, ints must always be floats if there are Null values.
Booleans are hard because converting bool column with None replaces
all Nones with false. Therefore only convert bool if there are no
NA values.
Datetimes should already be converted to np.datetime64 if supported,
but here we also force conversion if required.
|
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"are",
"no",
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"values",
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"Datetimes",
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"conversion",
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"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/io/sql.py#L803-L851
|
train
|
Harmonize the columns of the DataFrame.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(1308 - 1260) + chr(0b1101111) + chr(0b1 + 0o60) + '\061' + chr(54), 1318 - 1310), ehT0Px3KOsy9(chr(667 - 619) + '\157' + chr(0b11010 + 0o31) + '\064' + chr(51), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b101 + 0o57) + chr(0b1011 + 0o50), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(2165 - 2114) + '\x34' + chr(0b101010 + 0o13), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + '\x31' + chr(1006 - 954) + '\062', 56528 - 56520), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b101110 + 0o3) + '\060' + '\x37', 0o10), ehT0Px3KOsy9(chr(1566 - 1518) + chr(111) + '\x31' + chr(0b110010) + chr(0b110110), 44558 - 44550), ehT0Px3KOsy9(chr(1898 - 1850) + '\x6f' + '\062' + chr(49) + chr(0b110011 + 0o4), 0b1000), ehT0Px3KOsy9(chr(1407 - 1359) + chr(0b1101111) + '\x32' + '\x33' + '\x34', 4948 - 4940), ehT0Px3KOsy9(chr(2129 - 2081) + '\x6f' + '\x33' + '\065', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x36' + '\061', 0b1000), ehT0Px3KOsy9(chr(1164 - 1116) + chr(0b1000101 + 0o52) + '\062' + '\062' + chr(55), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x32' + chr(55) + chr(55), 0b1000), ehT0Px3KOsy9(chr(0b10101 + 0o33) + chr(0b11 + 0o154) + '\x31' + chr(0b110001), 0b1000), ehT0Px3KOsy9(chr(0b100010 + 0o16) + chr(0b1101111) + '\062' + '\x34' + '\x32', 58303 - 58295), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110001) + chr(0b110101) + chr(0b110111), 45101 - 45093), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x31' + chr(1249 - 1200) + '\067', 31018 - 31010), ehT0Px3KOsy9(chr(1786 - 1738) + '\x6f' + chr(0b1110 + 0o43) + chr(0b1011 + 0o52) + chr(538 - 489), 0o10), ehT0Px3KOsy9(chr(0b10100 + 0o34) + chr(5795 - 5684) + chr(2393 - 2344) + '\x36' + '\x30', 14244 - 14236), ehT0Px3KOsy9(chr(110 - 62) + chr(111) + chr(2002 - 1952) + chr(0b110000) + chr(0b1101 + 0o45), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110010) + chr(54) + '\x37', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110001) + chr(0b110010) + '\x33', 45043 - 45035), ehT0Px3KOsy9('\x30' + '\x6f' + chr(727 - 678) + chr(1200 - 1148) + chr(802 - 753), 47863 - 47855), ehT0Px3KOsy9('\060' + chr(0b1100001 + 0o16) + '\x31' + chr(0b110000) + chr(1677 - 1625), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(8982 - 8871) + chr(720 - 669) + chr(877 - 824) + chr(54), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110010) + '\066' + chr(0b101110 + 0o2), ord("\x08")), ehT0Px3KOsy9(chr(966 - 918) + chr(0b1101111) + chr(50) + '\x35' + '\064', ord("\x08")), ehT0Px3KOsy9(chr(0b11 + 0o55) + '\x6f' + '\x33' + chr(0b110101) + '\x32', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(2058 - 2009) + chr(51), ord("\x08")), ehT0Px3KOsy9(chr(0b11111 + 0o21) + chr(0b101100 + 0o103) + chr(1464 - 1415) + '\x36' + chr(49), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110001) + chr(0b100001 + 0o25) + chr(1785 - 1733), 0o10), ehT0Px3KOsy9(chr(1862 - 1814) + chr(0b1101111) + chr(54) + '\067', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\067' + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(0b110 + 0o52) + chr(9294 - 9183) + chr(0b110000 + 0o2) + chr(0b11001 + 0o32) + '\x36', ord("\x08")), ehT0Px3KOsy9(chr(0b100010 + 0o16) + '\x6f' + chr(50) + chr(0b110001) + '\064', 0o10), ehT0Px3KOsy9(chr(0b10010 + 0o36) + chr(111) + chr(51) + '\x30' + chr(50), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x32' + '\x31' + chr(2231 - 2179), 8), ehT0Px3KOsy9(chr(0b10100 + 0o34) + '\157' + chr(0b100110 + 0o13) + '\x33', 8), ehT0Px3KOsy9(chr(0b1110 + 0o42) + '\157' + chr(0b111 + 0o54) + chr(0b110000) + chr(50), 8), ehT0Px3KOsy9(chr(48) + '\157' + chr(50) + chr(53) + '\x36', 6627 - 6619)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(2236 - 2188) + chr(0b1100100 + 0o13) + chr(0b1001 + 0o54) + chr(0b110000), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'`'), chr(7646 - 7546) + '\x65' + chr(0b1100011) + chr(8172 - 8061) + chr(786 - 686) + chr(5255 - 5154))(chr(117) + chr(116) + '\x66' + chr(1051 - 1006) + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def OZR_pQymANGD(oVre8I6UXc3b, T1brfYV34pPD=None):
T1brfYV34pPD = Vdob_8esVEbU(T1brfYV34pPD)
for THhoCIGuUw2T in xafqLlk3kkUe(oVre8I6UXc3b.table, xafqLlk3kkUe(SXOLrMavuUCe(b'?\xa8O\xbd 38\xbc\xccVH\xa3'), chr(100) + chr(9644 - 9543) + chr(0b1010011 + 0o20) + chr(0b1000100 + 0o53) + chr(0b1100100) + chr(2298 - 2197))(chr(0b1110101) + chr(0b1110100) + chr(0b101011 + 0o73) + '\x2d' + chr(56))):
W93rymQCbozJ = THhoCIGuUw2T.AIvJRzLdDfgF
try:
lhzRzl6zabVS = oVre8I6UXc3b.C4IqNNmLfHXB[W93rymQCbozJ]
if W93rymQCbozJ in T1brfYV34pPD:
try:
EwDuvMM18jq4 = T1brfYV34pPD[W93rymQCbozJ]
except sznFqDbNBHlx:
EwDuvMM18jq4 = None
oVre8I6UXc3b.C4IqNNmLfHXB[W93rymQCbozJ] = XJ3YiAnKRkOa(lhzRzl6zabVS, format=EwDuvMM18jq4)
continue
tsawQFQB3tvJ = oVre8I6UXc3b._get_dtype(THhoCIGuUw2T.type)
if tsawQFQB3tvJ is zKdiQFzuryNR or tsawQFQB3tvJ is J4aeFOr3sjPo or tsawQFQB3tvJ is KOjhPpkKZCOh:
FvivsEIKa897 = tsawQFQB3tvJ is KOjhPpkKZCOh
oVre8I6UXc3b.C4IqNNmLfHXB[W93rymQCbozJ] = XJ3YiAnKRkOa(lhzRzl6zabVS, utc=FvivsEIKa897)
elif tsawQFQB3tvJ is kkSX4ccExqw4:
oVre8I6UXc3b.C4IqNNmLfHXB[W93rymQCbozJ] = lhzRzl6zabVS.astype(tsawQFQB3tvJ, copy=ehT0Px3KOsy9(chr(0b110000) + chr(7673 - 7562) + chr(48), 12055 - 12047))
elif c2A0yzQpDQB3(lhzRzl6zabVS) == xafqLlk3kkUe(lhzRzl6zabVS, xafqLlk3kkUe(SXOLrMavuUCe(b'-\x8cV\x8b\x16'), '\x64' + chr(1659 - 1558) + chr(99) + chr(7805 - 7694) + chr(100) + chr(7710 - 7609))('\165' + chr(0b1101 + 0o147) + '\x66' + chr(373 - 328) + '\070'))():
if tsawQFQB3tvJ is xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'*\x97Z\x95\x07'), chr(0b111110 + 0o46) + chr(101) + '\143' + chr(111) + chr(6385 - 6285) + '\x65')(chr(0b1110101) + chr(8865 - 8749) + '\x66' + chr(0b10110 + 0o27) + '\x38'))(xafqLlk3kkUe(SXOLrMavuUCe(b"'\x8dW\xd3V"), chr(100) + '\145' + chr(0b111100 + 0o47) + chr(4918 - 4807) + '\x64' + '\145')('\165' + chr(0b1100111 + 0o15) + '\146' + chr(0b101 + 0o50) + chr(56))) or tsawQFQB3tvJ is WbBjf8Y7v9VN:
oVre8I6UXc3b.C4IqNNmLfHXB[W93rymQCbozJ] = lhzRzl6zabVS.astype(tsawQFQB3tvJ, copy=ehT0Px3KOsy9(chr(0b11110 + 0o22) + '\x6f' + chr(48), 8))
except RQ6CSRrFArYB:
pass
|
pandas-dev/pandas
|
pandas/io/sql.py
|
SQLDatabase.read_table
|
def read_table(self, table_name, index_col=None, coerce_float=True,
parse_dates=None, columns=None, schema=None,
chunksize=None):
"""Read SQL database table into a DataFrame.
Parameters
----------
table_name : string
Name of SQL table in database.
index_col : string, optional, default: None
Column to set as index.
coerce_float : boolean, default True
Attempts to convert values of non-string, non-numeric objects
(like decimal.Decimal) to floating point. This can result in
loss of precision.
parse_dates : list or dict, default: None
- List of column names to parse as dates.
- Dict of ``{column_name: format string}`` where format string is
strftime compatible in case of parsing string times, or is one of
(D, s, ns, ms, us) in case of parsing integer timestamps.
- Dict of ``{column_name: arg}``, where the arg corresponds
to the keyword arguments of :func:`pandas.to_datetime`.
Especially useful with databases without native Datetime support,
such as SQLite.
columns : list, default: None
List of column names to select from SQL table.
schema : string, default None
Name of SQL schema in database to query (if database flavor
supports this). If specified, this overwrites the default
schema of the SQL database object.
chunksize : int, default None
If specified, return an iterator where `chunksize` is the number
of rows to include in each chunk.
Returns
-------
DataFrame
See Also
--------
pandas.read_sql_table
SQLDatabase.read_query
"""
table = SQLTable(table_name, self, index=index_col, schema=schema)
return table.read(coerce_float=coerce_float,
parse_dates=parse_dates, columns=columns,
chunksize=chunksize)
|
python
|
def read_table(self, table_name, index_col=None, coerce_float=True,
parse_dates=None, columns=None, schema=None,
chunksize=None):
"""Read SQL database table into a DataFrame.
Parameters
----------
table_name : string
Name of SQL table in database.
index_col : string, optional, default: None
Column to set as index.
coerce_float : boolean, default True
Attempts to convert values of non-string, non-numeric objects
(like decimal.Decimal) to floating point. This can result in
loss of precision.
parse_dates : list or dict, default: None
- List of column names to parse as dates.
- Dict of ``{column_name: format string}`` where format string is
strftime compatible in case of parsing string times, or is one of
(D, s, ns, ms, us) in case of parsing integer timestamps.
- Dict of ``{column_name: arg}``, where the arg corresponds
to the keyword arguments of :func:`pandas.to_datetime`.
Especially useful with databases without native Datetime support,
such as SQLite.
columns : list, default: None
List of column names to select from SQL table.
schema : string, default None
Name of SQL schema in database to query (if database flavor
supports this). If specified, this overwrites the default
schema of the SQL database object.
chunksize : int, default None
If specified, return an iterator where `chunksize` is the number
of rows to include in each chunk.
Returns
-------
DataFrame
See Also
--------
pandas.read_sql_table
SQLDatabase.read_query
"""
table = SQLTable(table_name, self, index=index_col, schema=schema)
return table.read(coerce_float=coerce_float,
parse_dates=parse_dates, columns=columns,
chunksize=chunksize)
|
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"=",
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",",
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"=",
"columns",
",",
"chunksize",
"=",
"chunksize",
")"
] |
Read SQL database table into a DataFrame.
Parameters
----------
table_name : string
Name of SQL table in database.
index_col : string, optional, default: None
Column to set as index.
coerce_float : boolean, default True
Attempts to convert values of non-string, non-numeric objects
(like decimal.Decimal) to floating point. This can result in
loss of precision.
parse_dates : list or dict, default: None
- List of column names to parse as dates.
- Dict of ``{column_name: format string}`` where format string is
strftime compatible in case of parsing string times, or is one of
(D, s, ns, ms, us) in case of parsing integer timestamps.
- Dict of ``{column_name: arg}``, where the arg corresponds
to the keyword arguments of :func:`pandas.to_datetime`.
Especially useful with databases without native Datetime support,
such as SQLite.
columns : list, default: None
List of column names to select from SQL table.
schema : string, default None
Name of SQL schema in database to query (if database flavor
supports this). If specified, this overwrites the default
schema of the SQL database object.
chunksize : int, default None
If specified, return an iterator where `chunksize` is the number
of rows to include in each chunk.
Returns
-------
DataFrame
See Also
--------
pandas.read_sql_table
SQLDatabase.read_query
|
[
"Read",
"SQL",
"database",
"table",
"into",
"a",
"DataFrame",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/io/sql.py#L982-L1029
|
train
|
Read a table into a DataFrame.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b10100 + 0o34) + chr(0b1100111 + 0o10) + chr(591 - 542) + chr(52) + '\067', 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110010) + '\x36', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110011) + '\061' + chr(0b110 + 0o54), ord("\x08")), ehT0Px3KOsy9(chr(0b100000 + 0o20) + chr(111) + chr(0b110011) + chr(0b110001) + chr(55), 60745 - 60737), ehT0Px3KOsy9(chr(219 - 171) + chr(11091 - 10980) + '\x31' + chr(53) + '\x32', 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(0b10111 + 0o32) + chr(0b100 + 0o60) + '\066', 36179 - 36171), ehT0Px3KOsy9(chr(156 - 108) + chr(0b100011 + 0o114) + chr(621 - 570) + chr(50) + chr(0b110111), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x32' + chr(54) + chr(54), 0b1000), ehT0Px3KOsy9(chr(0b111 + 0o51) + chr(0b1101111) + chr(979 - 927) + chr(1841 - 1791), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b100000 + 0o23) + chr(1121 - 1073) + chr(0b1010 + 0o52), 46534 - 46526), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\066' + '\x37', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(398 - 347) + chr(617 - 569) + chr(51), 0b1000), ehT0Px3KOsy9(chr(0b11000 + 0o30) + chr(111) + chr(0b110010) + chr(0b110000) + chr(0b101001 + 0o16), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(49) + chr(0b100001 + 0o24) + chr(50), 8), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110100) + chr(55), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\062' + '\062' + chr(924 - 875), 0o10), ehT0Px3KOsy9(chr(1721 - 1673) + chr(111) + chr(0b110010) + chr(2294 - 2240) + chr(2509 - 2458), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b101001 + 0o106) + chr(283 - 233) + '\061' + '\065', ord("\x08")), ehT0Px3KOsy9(chr(735 - 687) + chr(11466 - 11355) + chr(49) + '\061' + '\x37', 0b1000), ehT0Px3KOsy9(chr(48) + chr(7161 - 7050) + '\x32' + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(50) + chr(0b10101 + 0o40) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(51) + '\x34' + chr(48), 0o10), ehT0Px3KOsy9(chr(800 - 752) + '\x6f' + chr(0b110011) + chr(0b110111) + chr(0b110010), 36816 - 36808), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110000 + 0o3) + chr(0b110000) + chr(0b110011), 8), ehT0Px3KOsy9(chr(2203 - 2155) + '\x6f' + chr(0b1000 + 0o53) + chr(0b1010 + 0o54) + chr(1506 - 1452), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b1001 + 0o53) + chr(0b110000), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1011101 + 0o22) + chr(0b100 + 0o57) + chr(939 - 888) + chr(0b10001 + 0o41), 45217 - 45209), ehT0Px3KOsy9('\x30' + chr(7741 - 7630) + '\x32' + chr(0b110001) + '\065', 8), ehT0Px3KOsy9('\060' + chr(111) + '\061' + '\064', 0o10), ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(0b110001 + 0o76) + chr(51) + chr(48) + chr(52), 8), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(50) + '\061' + '\x33', 47707 - 47699), ehT0Px3KOsy9(chr(0b100000 + 0o20) + chr(0b111 + 0o150) + chr(49) + '\065' + '\x31', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\062' + chr(0b110000) + '\060', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x32' + '\x35' + '\x32', 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b100010 + 0o20) + chr(509 - 457) + chr(1263 - 1213), 0b1000), ehT0Px3KOsy9(chr(0b11110 + 0o22) + chr(5005 - 4894) + '\x32' + chr(0b101110 + 0o11), 0b1000), ehT0Px3KOsy9(chr(0b1000 + 0o50) + chr(0b110011 + 0o74) + chr(51) + '\066' + chr(49), 0b1000), ehT0Px3KOsy9(chr(1125 - 1077) + chr(111) + '\x33' + chr(0b110100) + chr(2492 - 2442), 3920 - 3912), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110010) + chr(273 - 220) + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110010) + chr(48), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + '\157' + '\x35' + chr(48), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'I'), chr(0b1111 + 0o125) + chr(0b1100101 + 0o0) + chr(0b101011 + 0o70) + chr(0b100001 + 0o116) + chr(2461 - 2361) + '\x65')(chr(4984 - 4867) + chr(0b110111 + 0o75) + chr(0b1100110) + '\x2d' + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def QLMuHiY4FMZb(oVre8I6UXc3b, NKKFbr2Z4sr1, o90TMYhFhMm_=None, hyGdBsLYkQVS=ehT0Px3KOsy9(chr(924 - 876) + chr(111) + chr(49), ord("\x08")), T1brfYV34pPD=None, qKlXBtn3PKy4=None, P7DmIFVRivx6=None, op94qe_Rdjul=None):
YbLi4ide0_3E = XnxdIGnwpv_R(NKKFbr2Z4sr1, oVre8I6UXc3b, index=o90TMYhFhMm_, schema=P7DmIFVRivx6)
return xafqLlk3kkUe(YbLi4ide0_3E, xafqLlk3kkUe(SXOLrMavuUCe(b'\x15s\xab\xab'), chr(0b1011000 + 0o14) + '\x65' + chr(0b10101 + 0o116) + '\x6f' + chr(2322 - 2222) + '\x65')('\x75' + chr(116) + '\x66' + chr(0b11 + 0o52) + chr(0b101101 + 0o13)))(coerce_float=hyGdBsLYkQVS, parse_dates=T1brfYV34pPD, columns=qKlXBtn3PKy4, chunksize=op94qe_Rdjul)
|
pandas-dev/pandas
|
pandas/io/sql.py
|
SQLDatabase._query_iterator
|
def _query_iterator(result, chunksize, columns, index_col=None,
coerce_float=True, parse_dates=None):
"""Return generator through chunked result set"""
while True:
data = result.fetchmany(chunksize)
if not data:
break
else:
yield _wrap_result(data, columns, index_col=index_col,
coerce_float=coerce_float,
parse_dates=parse_dates)
|
python
|
def _query_iterator(result, chunksize, columns, index_col=None,
coerce_float=True, parse_dates=None):
"""Return generator through chunked result set"""
while True:
data = result.fetchmany(chunksize)
if not data:
break
else:
yield _wrap_result(data, columns, index_col=index_col,
coerce_float=coerce_float,
parse_dates=parse_dates)
|
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"=",
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",",
"parse_dates",
"=",
"None",
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":",
"while",
"True",
":",
"data",
"=",
"result",
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"fetchmany",
"(",
"chunksize",
")",
"if",
"not",
"data",
":",
"break",
"else",
":",
"yield",
"_wrap_result",
"(",
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",",
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",",
"index_col",
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"index_col",
",",
"coerce_float",
"=",
"coerce_float",
",",
"parse_dates",
"=",
"parse_dates",
")"
] |
Return generator through chunked result set
|
[
"Return",
"generator",
"through",
"chunked",
"result",
"set"
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/io/sql.py#L1032-L1043
|
train
|
Return generator through chunked result set
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110001) + '\x35' + chr(0b110011), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + '\062' + chr(51) + chr(51), 28438 - 28430), ehT0Px3KOsy9('\x30' + '\x6f' + '\061' + '\x31' + chr(54), 41966 - 41958), ehT0Px3KOsy9(chr(48) + chr(0b110101 + 0o72) + '\063' + '\062' + chr(55), 52212 - 52204), ehT0Px3KOsy9('\x30' + chr(0b11000 + 0o127) + chr(0b110001) + '\x35' + chr(0b10 + 0o56), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b10101 + 0o132) + '\061' + '\063' + chr(55), 0o10), ehT0Px3KOsy9(chr(2253 - 2205) + '\157' + chr(2345 - 2294) + chr(0b100 + 0o63) + chr(0b10 + 0o60), 41309 - 41301), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110001) + '\060' + chr(0b100011 + 0o24), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b10010 + 0o41) + chr(1764 - 1715) + '\x36', 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + '\062' + chr(0b0 + 0o60) + chr(49), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + '\062' + '\x31' + chr(0b110001), 0b1000), ehT0Px3KOsy9('\x30' + chr(806 - 695) + chr(1143 - 1092) + '\064' + chr(0b110111), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110001) + chr(50) + chr(48), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b100001 + 0o116) + chr(0b101 + 0o56) + chr(0b11111 + 0o30) + chr(50), 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b10110 + 0o34) + chr(0b101111 + 0o5), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(49) + '\x36' + '\061', 61823 - 61815), ehT0Px3KOsy9('\x30' + '\157' + chr(0b10001 + 0o44), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(5736 - 5625) + chr(50) + chr(0b110010), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b101100 + 0o103) + '\062' + chr(0b110011) + '\x37', 53282 - 53274), ehT0Px3KOsy9(chr(0b10010 + 0o36) + '\x6f' + '\062' + chr(0b110110) + '\064', ord("\x08")), ehT0Px3KOsy9(chr(0b110 + 0o52) + chr(10535 - 10424) + chr(0b110011) + '\064' + chr(1903 - 1850), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + '\x33' + chr(54) + '\x35', 34363 - 34355), ehT0Px3KOsy9(chr(0b100011 + 0o15) + '\x6f' + chr(51) + chr(0b101101 + 0o5) + chr(1650 - 1600), 0b1000), ehT0Px3KOsy9('\060' + chr(1689 - 1578) + '\062' + chr(1070 - 1017) + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110011) + chr(0b110001) + chr(1350 - 1296), 8), ehT0Px3KOsy9('\060' + chr(7000 - 6889) + '\062' + chr(51) + chr(1913 - 1865), ord("\x08")), ehT0Px3KOsy9(chr(0b11111 + 0o21) + '\x6f' + chr(0b11111 + 0o23) + '\060' + chr(0b110100), 0o10), ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(0b1101111) + '\x34' + chr(2024 - 1969), 52886 - 52878), ehT0Px3KOsy9(chr(411 - 363) + chr(111) + '\061' + '\063' + chr(55), 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b101110 + 0o11) + '\x31', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(2245 - 2194) + chr(0b11011 + 0o26) + chr(54), 8), ehT0Px3KOsy9(chr(0b10 + 0o56) + chr(111) + '\063' + '\x33' + chr(0b110011), 50322 - 50314), ehT0Px3KOsy9('\x30' + '\157' + chr(1795 - 1744) + '\062' + '\065', ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + '\x33' + chr(0b10111 + 0o35) + chr(2400 - 2345), 8), ehT0Px3KOsy9(chr(0b11101 + 0o23) + '\157' + chr(49) + '\067' + chr(0b101100 + 0o12), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(1357 - 1307) + chr(2315 - 2264) + chr(49), 0o10), ehT0Px3KOsy9('\x30' + chr(6711 - 6600) + chr(1120 - 1071) + chr(0b11 + 0o64) + '\x34', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(49) + '\x32' + '\063', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b1000 + 0o52) + chr(1093 - 1040), 42705 - 42697), ehT0Px3KOsy9(chr(0b101100 + 0o4) + '\x6f' + chr(52), 35479 - 35471)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(1400 - 1347) + '\060', 35966 - 35958)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'E'), chr(0b101100 + 0o70) + '\145' + chr(0b1100011) + chr(0b110110 + 0o71) + chr(0b1100100) + '\x65')('\165' + chr(0b1110100) + '\146' + chr(1339 - 1294) + chr(2945 - 2889)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def ysyuhdWchnZj(ShZmEKfTkAOZ, op94qe_Rdjul, qKlXBtn3PKy4, o90TMYhFhMm_=None, hyGdBsLYkQVS=ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110001), 23802 - 23794), T1brfYV34pPD=None):
while ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b10110 + 0o33), 8):
ULnjp6D6efFH = ShZmEKfTkAOZ.fetchmany(op94qe_Rdjul)
if not ULnjp6D6efFH:
break
else:
yield jDdYdl3hJF1x(ULnjp6D6efFH, qKlXBtn3PKy4, index_col=o90TMYhFhMm_, coerce_float=hyGdBsLYkQVS, parse_dates=T1brfYV34pPD)
|
pandas-dev/pandas
|
pandas/io/sql.py
|
SQLDatabase.read_query
|
def read_query(self, sql, index_col=None, coerce_float=True,
parse_dates=None, params=None, chunksize=None):
"""Read SQL query into a DataFrame.
Parameters
----------
sql : string
SQL query to be executed.
index_col : string, optional, default: None
Column name to use as index for the returned DataFrame object.
coerce_float : boolean, default True
Attempt to convert values of non-string, non-numeric objects (like
decimal.Decimal) to floating point, useful for SQL result sets.
params : list, tuple or dict, optional, default: None
List of parameters to pass to execute method. The syntax used
to pass parameters is database driver dependent. Check your
database driver documentation for which of the five syntax styles,
described in PEP 249's paramstyle, is supported.
Eg. for psycopg2, uses %(name)s so use params={'name' : 'value'}
parse_dates : list or dict, default: None
- List of column names to parse as dates.
- Dict of ``{column_name: format string}`` where format string is
strftime compatible in case of parsing string times, or is one of
(D, s, ns, ms, us) in case of parsing integer timestamps.
- Dict of ``{column_name: arg dict}``, where the arg dict
corresponds to the keyword arguments of
:func:`pandas.to_datetime` Especially useful with databases
without native Datetime support, such as SQLite.
chunksize : int, default None
If specified, return an iterator where `chunksize` is the number
of rows to include in each chunk.
Returns
-------
DataFrame
See Also
--------
read_sql_table : Read SQL database table into a DataFrame.
read_sql
"""
args = _convert_params(sql, params)
result = self.execute(*args)
columns = result.keys()
if chunksize is not None:
return self._query_iterator(result, chunksize, columns,
index_col=index_col,
coerce_float=coerce_float,
parse_dates=parse_dates)
else:
data = result.fetchall()
frame = _wrap_result(data, columns, index_col=index_col,
coerce_float=coerce_float,
parse_dates=parse_dates)
return frame
|
python
|
def read_query(self, sql, index_col=None, coerce_float=True,
parse_dates=None, params=None, chunksize=None):
"""Read SQL query into a DataFrame.
Parameters
----------
sql : string
SQL query to be executed.
index_col : string, optional, default: None
Column name to use as index for the returned DataFrame object.
coerce_float : boolean, default True
Attempt to convert values of non-string, non-numeric objects (like
decimal.Decimal) to floating point, useful for SQL result sets.
params : list, tuple or dict, optional, default: None
List of parameters to pass to execute method. The syntax used
to pass parameters is database driver dependent. Check your
database driver documentation for which of the five syntax styles,
described in PEP 249's paramstyle, is supported.
Eg. for psycopg2, uses %(name)s so use params={'name' : 'value'}
parse_dates : list or dict, default: None
- List of column names to parse as dates.
- Dict of ``{column_name: format string}`` where format string is
strftime compatible in case of parsing string times, or is one of
(D, s, ns, ms, us) in case of parsing integer timestamps.
- Dict of ``{column_name: arg dict}``, where the arg dict
corresponds to the keyword arguments of
:func:`pandas.to_datetime` Especially useful with databases
without native Datetime support, such as SQLite.
chunksize : int, default None
If specified, return an iterator where `chunksize` is the number
of rows to include in each chunk.
Returns
-------
DataFrame
See Also
--------
read_sql_table : Read SQL database table into a DataFrame.
read_sql
"""
args = _convert_params(sql, params)
result = self.execute(*args)
columns = result.keys()
if chunksize is not None:
return self._query_iterator(result, chunksize, columns,
index_col=index_col,
coerce_float=coerce_float,
parse_dates=parse_dates)
else:
data = result.fetchall()
frame = _wrap_result(data, columns, index_col=index_col,
coerce_float=coerce_float,
parse_dates=parse_dates)
return frame
|
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"=",
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",",
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"=",
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")",
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"frame"
] |
Read SQL query into a DataFrame.
Parameters
----------
sql : string
SQL query to be executed.
index_col : string, optional, default: None
Column name to use as index for the returned DataFrame object.
coerce_float : boolean, default True
Attempt to convert values of non-string, non-numeric objects (like
decimal.Decimal) to floating point, useful for SQL result sets.
params : list, tuple or dict, optional, default: None
List of parameters to pass to execute method. The syntax used
to pass parameters is database driver dependent. Check your
database driver documentation for which of the five syntax styles,
described in PEP 249's paramstyle, is supported.
Eg. for psycopg2, uses %(name)s so use params={'name' : 'value'}
parse_dates : list or dict, default: None
- List of column names to parse as dates.
- Dict of ``{column_name: format string}`` where format string is
strftime compatible in case of parsing string times, or is one of
(D, s, ns, ms, us) in case of parsing integer timestamps.
- Dict of ``{column_name: arg dict}``, where the arg dict
corresponds to the keyword arguments of
:func:`pandas.to_datetime` Especially useful with databases
without native Datetime support, such as SQLite.
chunksize : int, default None
If specified, return an iterator where `chunksize` is the number
of rows to include in each chunk.
Returns
-------
DataFrame
See Also
--------
read_sql_table : Read SQL database table into a DataFrame.
read_sql
|
[
"Read",
"SQL",
"query",
"into",
"a",
"DataFrame",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/io/sql.py#L1045-L1102
|
train
|
Read SQL query into a DataFrame.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b10011 + 0o35) + chr(7920 - 7809) + '\x31' + chr(0b110000) + chr(0b110101), 1979 - 1971), ehT0Px3KOsy9(chr(0b110000) + chr(0b1001010 + 0o45) + chr(0b11000 + 0o35) + chr(0b1101 + 0o47), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(50) + chr(50), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(6385 - 6274) + chr(0b1 + 0o60) + '\063' + chr(0b110111), 16524 - 16516), ehT0Px3KOsy9('\060' + chr(111) + chr(471 - 422) + chr(0b11101 + 0o31) + chr(55), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + '\061' + chr(0b101101 + 0o6) + chr(0b110111), 8), ehT0Px3KOsy9(chr(2094 - 2046) + chr(0b1100110 + 0o11) + chr(0b110010) + chr(640 - 585) + chr(1571 - 1517), 0o10), ehT0Px3KOsy9(chr(48) + chr(9292 - 9181) + chr(50) + chr(54) + chr(0b110100), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b101110 + 0o4) + chr(53), ord("\x08")), ehT0Px3KOsy9(chr(0b11010 + 0o26) + '\157' + chr(1073 - 1023) + '\x34' + chr(0b110010), 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(1019 - 970) + chr(52) + chr(987 - 937), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b111 + 0o150) + '\061' + '\063' + '\x30', 27809 - 27801), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110001) + '\065' + chr(0b101001 + 0o13), 15885 - 15877), ehT0Px3KOsy9(chr(0b10000 + 0o40) + chr(0b1101111) + '\063' + '\x37' + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b11 + 0o56) + '\067' + chr(993 - 943), ord("\x08")), ehT0Px3KOsy9(chr(176 - 128) + chr(0b1101111) + chr(1665 - 1616) + chr(0b110010) + chr(53), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(5266 - 5155) + '\062' + chr(1916 - 1861) + '\062', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\061' + chr(0b110101) + chr(0b1100 + 0o45), 0o10), ehT0Px3KOsy9(chr(48) + chr(271 - 160) + chr(50) + '\x32' + chr(254 - 206), 15309 - 15301), ehT0Px3KOsy9('\x30' + '\x6f' + '\061' + '\067' + chr(52), ord("\x08")), ehT0Px3KOsy9(chr(1825 - 1777) + chr(111) + chr(0b110001) + '\x36' + chr(0b110000), 0b1000), ehT0Px3KOsy9('\060' + chr(6725 - 6614) + chr(51) + chr(51) + '\064', 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(51) + chr(380 - 327), 0o10), ehT0Px3KOsy9(chr(2211 - 2163) + chr(0b1101111) + '\061' + chr(0b1100 + 0o45) + chr(0b111 + 0o55), 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(50) + '\065' + '\x33', 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110010) + chr(0b110110), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x31' + '\x36' + chr(52), 0b1000), ehT0Px3KOsy9(chr(1900 - 1852) + '\157' + chr(0b1000 + 0o53) + chr(0b11001 + 0o36) + chr(53), 22387 - 22379), ehT0Px3KOsy9(chr(987 - 939) + chr(111) + '\062' + chr(1433 - 1385), 24754 - 24746), ehT0Px3KOsy9(chr(48) + chr(0b10110 + 0o131) + '\x31' + '\062' + chr(0b110110), 0b1000), ehT0Px3KOsy9(chr(2209 - 2161) + chr(0b1101111) + chr(1435 - 1385) + chr(1638 - 1583) + '\x30', 20059 - 20051), ehT0Px3KOsy9(chr(1049 - 1001) + chr(8998 - 8887) + chr(0b110010) + chr(0b10011 + 0o35) + chr(686 - 636), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1000111 + 0o50) + chr(52) + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(12210 - 12099) + '\067', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\061' + '\x34', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1000110 + 0o51) + chr(0b110110 + 0o0) + chr(0b110000), 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(52) + '\067', 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(54) + '\x36', 30430 - 30422), ehT0Px3KOsy9(chr(48) + chr(9526 - 9415) + chr(55) + '\063', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + '\066' + chr(1126 - 1075), 5350 - 5342)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110101) + chr(0b100001 + 0o17), 16978 - 16970)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'k'), '\x64' + chr(1896 - 1795) + chr(99) + chr(111) + chr(6622 - 6522) + '\x65')('\165' + chr(0b1110100) + chr(0b1100110) + chr(0b101101) + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def OomMOOBMey7C(oVre8I6UXc3b, GWXd4kBaViZK, o90TMYhFhMm_=None, hyGdBsLYkQVS=ehT0Px3KOsy9(chr(931 - 883) + chr(111) + chr(971 - 922), ord("\x08")), T1brfYV34pPD=None, nEbJZ4wfte2w=None, op94qe_Rdjul=None):
kJDRfRhcZHjS = Q7IKiRWSu9En(GWXd4kBaViZK, nEbJZ4wfte2w)
ShZmEKfTkAOZ = oVre8I6UXc3b.execute(*kJDRfRhcZHjS)
qKlXBtn3PKy4 = ShZmEKfTkAOZ.keys()
if op94qe_Rdjul is not None:
return xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\x1a]g:\x05&\xe1\xdda\xc7\x109\x18\x93\x08'), chr(0b100010 + 0o102) + '\x65' + chr(99) + chr(9408 - 9297) + chr(0b1100100) + chr(101))('\x75' + chr(116) + chr(0b111011 + 0o53) + chr(0b10111 + 0o26) + '\070'))(ShZmEKfTkAOZ, op94qe_Rdjul, qKlXBtn3PKy4, index_col=o90TMYhFhMm_, coerce_float=hyGdBsLYkQVS, parse_dates=T1brfYV34pPD)
else:
ULnjp6D6efFH = ShZmEKfTkAOZ.fetchall()
C4IqNNmLfHXB = jDdYdl3hJF1x(ULnjp6D6efFH, qKlXBtn3PKy4, index_col=o90TMYhFhMm_, coerce_float=hyGdBsLYkQVS, parse_dates=T1brfYV34pPD)
return C4IqNNmLfHXB
|
pandas-dev/pandas
|
pandas/io/sql.py
|
SQLDatabase.to_sql
|
def to_sql(self, frame, name, if_exists='fail', index=True,
index_label=None, schema=None, chunksize=None, dtype=None,
method=None):
"""
Write records stored in a DataFrame to a SQL database.
Parameters
----------
frame : DataFrame
name : string
Name of SQL table.
if_exists : {'fail', 'replace', 'append'}, default 'fail'
- fail: If table exists, do nothing.
- replace: If table exists, drop it, recreate it, and insert data.
- append: If table exists, insert data. Create if does not exist.
index : boolean, default True
Write DataFrame index as a column.
index_label : string or sequence, default None
Column label for index column(s). If None is given (default) and
`index` is True, then the index names are used.
A sequence should be given if the DataFrame uses MultiIndex.
schema : string, default None
Name of SQL schema in database to write to (if database flavor
supports this). If specified, this overwrites the default
schema of the SQLDatabase object.
chunksize : int, default None
If not None, then rows will be written in batches of this size at a
time. If None, all rows will be written at once.
dtype : single type or dict of column name to SQL type, default None
Optional specifying the datatype for columns. The SQL type should
be a SQLAlchemy type. If all columns are of the same type, one
single value can be used.
method : {None', 'multi', callable}, default None
Controls the SQL insertion clause used:
* None : Uses standard SQL ``INSERT`` clause (one per row).
* 'multi': Pass multiple values in a single ``INSERT`` clause.
* callable with signature ``(pd_table, conn, keys, data_iter)``.
Details and a sample callable implementation can be found in the
section :ref:`insert method <io.sql.method>`.
.. versionadded:: 0.24.0
"""
if dtype and not is_dict_like(dtype):
dtype = {col_name: dtype for col_name in frame}
if dtype is not None:
from sqlalchemy.types import to_instance, TypeEngine
for col, my_type in dtype.items():
if not isinstance(to_instance(my_type), TypeEngine):
raise ValueError('The type of {column} is not a '
'SQLAlchemy type '.format(column=col))
table = SQLTable(name, self, frame=frame, index=index,
if_exists=if_exists, index_label=index_label,
schema=schema, dtype=dtype)
table.create()
table.insert(chunksize, method=method)
if (not name.isdigit() and not name.islower()):
# check for potentially case sensitivity issues (GH7815)
# Only check when name is not a number and name is not lower case
engine = self.connectable.engine
with self.connectable.connect() as conn:
table_names = engine.table_names(
schema=schema or self.meta.schema,
connection=conn,
)
if name not in table_names:
msg = (
"The provided table name '{0}' is not found exactly as "
"such in the database after writing the table, possibly "
"due to case sensitivity issues. Consider using lower "
"case table names."
).format(name)
warnings.warn(msg, UserWarning)
|
python
|
def to_sql(self, frame, name, if_exists='fail', index=True,
index_label=None, schema=None, chunksize=None, dtype=None,
method=None):
"""
Write records stored in a DataFrame to a SQL database.
Parameters
----------
frame : DataFrame
name : string
Name of SQL table.
if_exists : {'fail', 'replace', 'append'}, default 'fail'
- fail: If table exists, do nothing.
- replace: If table exists, drop it, recreate it, and insert data.
- append: If table exists, insert data. Create if does not exist.
index : boolean, default True
Write DataFrame index as a column.
index_label : string or sequence, default None
Column label for index column(s). If None is given (default) and
`index` is True, then the index names are used.
A sequence should be given if the DataFrame uses MultiIndex.
schema : string, default None
Name of SQL schema in database to write to (if database flavor
supports this). If specified, this overwrites the default
schema of the SQLDatabase object.
chunksize : int, default None
If not None, then rows will be written in batches of this size at a
time. If None, all rows will be written at once.
dtype : single type or dict of column name to SQL type, default None
Optional specifying the datatype for columns. The SQL type should
be a SQLAlchemy type. If all columns are of the same type, one
single value can be used.
method : {None', 'multi', callable}, default None
Controls the SQL insertion clause used:
* None : Uses standard SQL ``INSERT`` clause (one per row).
* 'multi': Pass multiple values in a single ``INSERT`` clause.
* callable with signature ``(pd_table, conn, keys, data_iter)``.
Details and a sample callable implementation can be found in the
section :ref:`insert method <io.sql.method>`.
.. versionadded:: 0.24.0
"""
if dtype and not is_dict_like(dtype):
dtype = {col_name: dtype for col_name in frame}
if dtype is not None:
from sqlalchemy.types import to_instance, TypeEngine
for col, my_type in dtype.items():
if not isinstance(to_instance(my_type), TypeEngine):
raise ValueError('The type of {column} is not a '
'SQLAlchemy type '.format(column=col))
table = SQLTable(name, self, frame=frame, index=index,
if_exists=if_exists, index_label=index_label,
schema=schema, dtype=dtype)
table.create()
table.insert(chunksize, method=method)
if (not name.isdigit() and not name.islower()):
# check for potentially case sensitivity issues (GH7815)
# Only check when name is not a number and name is not lower case
engine = self.connectable.engine
with self.connectable.connect() as conn:
table_names = engine.table_names(
schema=schema or self.meta.schema,
connection=conn,
)
if name not in table_names:
msg = (
"The provided table name '{0}' is not found exactly as "
"such in the database after writing the table, possibly "
"due to case sensitivity issues. Consider using lower "
"case table names."
).format(name)
warnings.warn(msg, UserWarning)
|
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Write records stored in a DataFrame to a SQL database.
Parameters
----------
frame : DataFrame
name : string
Name of SQL table.
if_exists : {'fail', 'replace', 'append'}, default 'fail'
- fail: If table exists, do nothing.
- replace: If table exists, drop it, recreate it, and insert data.
- append: If table exists, insert data. Create if does not exist.
index : boolean, default True
Write DataFrame index as a column.
index_label : string or sequence, default None
Column label for index column(s). If None is given (default) and
`index` is True, then the index names are used.
A sequence should be given if the DataFrame uses MultiIndex.
schema : string, default None
Name of SQL schema in database to write to (if database flavor
supports this). If specified, this overwrites the default
schema of the SQLDatabase object.
chunksize : int, default None
If not None, then rows will be written in batches of this size at a
time. If None, all rows will be written at once.
dtype : single type or dict of column name to SQL type, default None
Optional specifying the datatype for columns. The SQL type should
be a SQLAlchemy type. If all columns are of the same type, one
single value can be used.
method : {None', 'multi', callable}, default None
Controls the SQL insertion clause used:
* None : Uses standard SQL ``INSERT`` clause (one per row).
* 'multi': Pass multiple values in a single ``INSERT`` clause.
* callable with signature ``(pd_table, conn, keys, data_iter)``.
Details and a sample callable implementation can be found in the
section :ref:`insert method <io.sql.method>`.
.. versionadded:: 0.24.0
|
[
"Write",
"records",
"stored",
"in",
"a",
"DataFrame",
"to",
"a",
"SQL",
"database",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/io/sql.py#L1106-L1181
|
train
|
Writes the DataFrame to a SQL database.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\x30' + chr(111) + chr(51) + chr(0b10110 + 0o36) + chr(0b110101), 0b1000), ehT0Px3KOsy9('\060' + chr(6971 - 6860) + chr(0b1010 + 0o51) + chr(610 - 557) + '\062', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(7269 - 7158) + '\063' + '\x37' + '\065', ord("\x08")), ehT0Px3KOsy9(chr(1804 - 1756) + chr(0b1101111) + chr(0b110001) + chr(51) + chr(0b110000 + 0o5), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(3677 - 3566) + chr(0b100101 + 0o15) + chr(0b110111) + '\064', 7385 - 7377), ehT0Px3KOsy9(chr(0b11100 + 0o24) + chr(4403 - 4292) + chr(50) + chr(1550 - 1502) + '\x36', 17030 - 17022), ehT0Px3KOsy9('\x30' + chr(2371 - 2260) + '\x32' + chr(51), 59861 - 59853), ehT0Px3KOsy9(chr(291 - 243) + chr(9175 - 9064) + chr(2422 - 2372) + chr(0b110101) + '\062', ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(1235 - 1186) + chr(0b101 + 0o53) + chr(49), 0b1000), ehT0Px3KOsy9(chr(677 - 629) + chr(0b100110 + 0o111) + chr(0b11000 + 0o31) + chr(2141 - 2091) + '\x32', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(49) + chr(0b100101 + 0o14) + chr(0b10101 + 0o35), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b10000 + 0o45) + chr(2437 - 2383), 0b1000), ehT0Px3KOsy9('\060' + '\157' + '\x32' + chr(0b101100 + 0o12) + chr(0b101001 + 0o13), 18434 - 18426), ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(4855 - 4744) + chr(55) + '\x32', 0b1000), ehT0Px3KOsy9(chr(1461 - 1413) + chr(0b1101111) + '\067' + chr(0b11101 + 0o26), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + '\x34', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(50) + '\x35' + '\x33', 0o10), ehT0Px3KOsy9(chr(1468 - 1420) + '\157' + '\061' + chr(514 - 465) + chr(768 - 714), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + '\063' + '\063', 0o10), ehT0Px3KOsy9(chr(0b100000 + 0o20) + chr(2717 - 2606) + chr(1017 - 967) + chr(0b10111 + 0o35) + '\x31', 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(0b110001) + chr(787 - 733) + chr(1292 - 1241), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + '\x31' + chr(1192 - 1144) + chr(52), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(627 - 516) + '\x31' + chr(48) + chr(0b101 + 0o62), ord("\x08")), ehT0Px3KOsy9(chr(0b100 + 0o54) + chr(10582 - 10471) + chr(0b110011) + '\x34' + chr(0b110011), ord("\x08")), ehT0Px3KOsy9(chr(2228 - 2180) + chr(0b1101111) + '\x33' + chr(0b110111) + chr(0b100010 + 0o20), 0o10), ehT0Px3KOsy9('\x30' + chr(2185 - 2074) + '\062' + chr(0b110001) + chr(1677 - 1625), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(1456 - 1406) + chr(0b101001 + 0o12) + chr(2234 - 2180), 0b1000), ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(111) + '\x31' + chr(764 - 715), 0o10), ehT0Px3KOsy9(chr(0b11011 + 0o25) + chr(10233 - 10122) + chr(0b11101 + 0o26) + chr(0b101101 + 0o12) + chr(0b110111), 5901 - 5893), ehT0Px3KOsy9(chr(0b110000) + chr(0b101010 + 0o105) + chr(0b11010 + 0o30) + '\x30' + chr(0b100100 + 0o16), 0b1000), ehT0Px3KOsy9(chr(48) + chr(117 - 6) + chr(49) + chr(0b110001) + '\x33', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b10101 + 0o132) + chr(0b101001 + 0o11) + chr(1948 - 1897) + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(4827 - 4716) + chr(1294 - 1243) + chr(0b101001 + 0o12) + chr(0b110011 + 0o0), 0o10), ehT0Px3KOsy9(chr(736 - 688) + chr(0b110100 + 0o73) + chr(0b110010) + chr(1901 - 1847) + chr(50), 0o10), ehT0Px3KOsy9(chr(0b100100 + 0o14) + chr(9285 - 9174) + '\x33' + chr(0b110010) + chr(0b110000), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(50) + '\x33' + '\063', 0o10), ehT0Px3KOsy9(chr(2214 - 2166) + chr(0b1011001 + 0o26) + '\x32' + '\067' + chr(0b110101), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110001) + chr(147 - 96), 28529 - 28521), ehT0Px3KOsy9('\x30' + chr(0b101001 + 0o106) + '\x33' + chr(636 - 583) + chr(0b10111 + 0o37), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(49) + chr(0b100110 + 0o16) + chr(0b1100 + 0o47), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x35' + chr(48), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xcb'), '\144' + chr(0b1100101) + '\x63' + chr(0b100111 + 0o110) + '\x64' + '\145')(chr(0b111110 + 0o67) + '\x74' + chr(468 - 366) + chr(0b11000 + 0o25) + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def b6tBeYOjJJGT(oVre8I6UXc3b, C4IqNNmLfHXB, AIvJRzLdDfgF, zZFPtODM90fp=xafqLlk3kkUe(SXOLrMavuUCe(b'\x83\x8b\x941'), '\x64' + chr(101) + chr(3659 - 3560) + chr(0b1101111) + '\x64' + chr(0b1100101))(chr(2888 - 2771) + chr(0b1110100) + chr(3317 - 3215) + chr(0b101101) + chr(1454 - 1398)), XdowRbJKZWL9=ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110001), 0b1000), Rj5_q03bvJPB=None, P7DmIFVRivx6=None, op94qe_Rdjul=None, jSV9IKnemH7K=None, CVRCXTcnOnH6=None):
if jSV9IKnemH7K and (not KwJXno8t8wVV(jSV9IKnemH7K)):
jSV9IKnemH7K = {W93rymQCbozJ: jSV9IKnemH7K for W93rymQCbozJ in C4IqNNmLfHXB}
if jSV9IKnemH7K is not None:
(AElPlk1Zukk0, TCvHKsFthRg4) = (xafqLlk3kkUe(xafqLlk3kkUe(NPPHb59961Bv(xafqLlk3kkUe(SXOLrMavuUCe(b'\x96\x9b\x91<\xd0\xe5{\xcf,+dZ\xcdJ^w'), '\144' + '\145' + chr(0b1100011) + chr(111) + '\144' + chr(0b11101 + 0o110))('\x75' + '\x74' + chr(102) + chr(1109 - 1064) + chr(56)), xafqLlk3kkUe(SXOLrMavuUCe(b'\x91\x85\xa24\xd2\xf5g\xcb/1/'), '\144' + chr(101) + chr(6073 - 5974) + chr(0b11101 + 0o122) + chr(0b1100 + 0o130) + chr(0b1100101))(chr(0b1010000 + 0o45) + chr(0b1011011 + 0o31) + '\x66' + chr(0b101101) + '\070')), xafqLlk3kkUe(SXOLrMavuUCe(b'\x91\x93\x8d8\xcf'), chr(8221 - 8121) + chr(0b1001 + 0o134) + chr(0b1100011) + chr(0b1101 + 0o142) + '\x64' + chr(0b1100101))(chr(117) + chr(0b1110100) + '\x66' + chr(0b101101) + chr(0b111000))), xafqLlk3kkUe(SXOLrMavuUCe(b'\x91\x85\xa24\xd2\xf5g\xcb/1/'), '\144' + chr(101) + chr(0b1100011) + chr(0b101101 + 0o102) + chr(0b111010 + 0o52) + chr(101))(chr(0b101011 + 0o112) + '\164' + chr(0b1100110) + '\055' + chr(2287 - 2231))), xafqLlk3kkUe(xafqLlk3kkUe(NPPHb59961Bv(xafqLlk3kkUe(SXOLrMavuUCe(b'\x96\x9b\x91<\xd0\xe5{\xcf,+dZ\xcdJ^w'), chr(0b1100100) + chr(7102 - 7001) + chr(0b1100011) + chr(0b1101111) + '\144' + chr(0b11001 + 0o114))(chr(0b1101001 + 0o14) + chr(116) + chr(0b1100110) + '\x2d' + chr(0b111000)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xb1\x93\x8d8\xf9\xe8t\xc3/7'), chr(0b1100100) + chr(0b1100101) + chr(0b111011 + 0o50) + chr(0b1011001 + 0o26) + chr(0b1100100) + '\x65')(chr(0b1001000 + 0o55) + chr(116) + chr(9735 - 9633) + '\055' + chr(1315 - 1259))), xafqLlk3kkUe(SXOLrMavuUCe(b'\x91\x93\x8d8\xcf'), '\x64' + '\x65' + '\x63' + chr(111) + '\x64' + chr(7228 - 7127))('\165' + chr(0b1110100) + chr(10285 - 10183) + chr(0b1011 + 0o42) + chr(0b111000))), xafqLlk3kkUe(SXOLrMavuUCe(b'\xb1\x93\x8d8\xf9\xe8t\xc3/7'), chr(0b1100100) + chr(0b101101 + 0o70) + '\143' + chr(2211 - 2100) + chr(9242 - 9142) + chr(0b1011110 + 0o7))('\165' + '\164' + '\146' + chr(0b10110 + 0o27) + chr(1969 - 1913))))
for (Qa2uSJqQPT3w, PgUW1UssNxfH) in xafqLlk3kkUe(jSV9IKnemH7K, xafqLlk3kkUe(SXOLrMavuUCe(b'\x8c\x9e\x980\xcf'), chr(0b1100100) + '\x65' + chr(99) + '\x6f' + chr(0b101101 + 0o67) + chr(0b111010 + 0o53))(chr(0b1110101) + chr(0b1110100) + '\x66' + chr(0b101101) + chr(129 - 73)))():
if not PlSM16l2KDPD(AElPlk1Zukk0(PgUW1UssNxfH), TCvHKsFthRg4):
raise q1QCh3W88sgk(xafqLlk3kkUe(xafqLlk3kkUe(SXOLrMavuUCe(b'\xb1\x82\x98}\xc8\xffc\xcfa=,\x0e\xcfYTh\xde#u\xdcS-4\xc3\x94\xe3\xea)\x9e\xa2\x18\xcb\x97\xf3\xbc\xf8\xd5n\x83\x1a\xc5\x9e\x84-\xd9\xa6'), chr(100) + chr(101) + chr(6320 - 6221) + '\x6f' + chr(0b11 + 0o141) + chr(227 - 126))(chr(0b111100 + 0o71) + chr(0b1000 + 0o154) + chr(0b1100110) + chr(573 - 528) + chr(0b111000)), xafqLlk3kkUe(SXOLrMavuUCe(b'\x83\x85\x8f0\xdd\xf2'), '\144' + '\x65' + chr(0b1100011) + chr(111) + '\x64' + chr(0b1100101))('\165' + chr(0b1110100) + chr(0b110100 + 0o62) + chr(0b101101) + '\070'))(column=Qa2uSJqQPT3w))
YbLi4ide0_3E = XnxdIGnwpv_R(AIvJRzLdDfgF, oVre8I6UXc3b, frame=C4IqNNmLfHXB, index=XdowRbJKZWL9, if_exists=zZFPtODM90fp, index_label=Rj5_q03bvJPB, schema=P7DmIFVRivx6, dtype=jSV9IKnemH7K)
xafqLlk3kkUe(YbLi4ide0_3E, xafqLlk3kkUe(SXOLrMavuUCe(b'\x86\x98\x98<\xc8\xe3'), '\x64' + '\145' + '\x63' + '\157' + chr(880 - 780) + chr(101))(chr(0b1110101) + chr(116) + chr(0b1010001 + 0o25) + chr(45) + chr(56)))()
xafqLlk3kkUe(YbLi4ide0_3E, xafqLlk3kkUe(SXOLrMavuUCe(b'\x8c\x84\x8e8\xce\xf2'), '\144' + chr(101) + '\x63' + chr(111) + '\144' + chr(0b11111 + 0o106))(chr(117) + '\x74' + chr(0b1011111 + 0o7) + '\055' + '\070'))(op94qe_Rdjul, method=CVRCXTcnOnH6)
if not xafqLlk3kkUe(AIvJRzLdDfgF, xafqLlk3kkUe(SXOLrMavuUCe(b'\x8c\x99\x994\xdb\xefg'), chr(9228 - 9128) + chr(3613 - 3512) + chr(99) + '\x6f' + chr(0b11101 + 0o107) + chr(3881 - 3780))('\165' + chr(116) + '\146' + chr(0b101101) + chr(0b111000)))() and (not xafqLlk3kkUe(AIvJRzLdDfgF, xafqLlk3kkUe(SXOLrMavuUCe(b'\x8c\x99\x912\xcb\xe3a'), '\x64' + chr(0b110111 + 0o56) + chr(99) + '\157' + chr(0b1000111 + 0o35) + chr(101))(chr(0b1110101) + '\x74' + '\x66' + '\x2d' + chr(0b111000)))()):
ZYbnEw0oVPbF = oVre8I6UXc3b.connectable.engine
with xafqLlk3kkUe(oVre8I6UXc3b.connectable, xafqLlk3kkUe(SXOLrMavuUCe(b'\x86\x85\x933\xd9\xe5g'), '\x64' + chr(0b10 + 0o143) + '\143' + chr(0b10000 + 0o137) + chr(0b11100 + 0o110) + chr(0b1100101))('\x75' + chr(116) + chr(0b101100 + 0o72) + chr(45) + chr(0b111000)))() as npwjCV10gdob:
tmU9MHfzAbu1 = ZYbnEw0oVPbF.table_names(schema=P7DmIFVRivx6 or oVre8I6UXc3b.meta.schema, connection=npwjCV10gdob)
if AIvJRzLdDfgF not in tmU9MHfzAbu1:
jtbovtaIYjRB = xafqLlk3kkUe(SXOLrMavuUCe(b'\xb1\x82\x98}\xcc\xf4|\xdc(6/J\x94NZf\xc7+;\xcf\x12)"\xc3\xdd\xf7\xaet\xd8\xa2"\xe9\xfb\xdc\xbf\xef\x9dm\x81\x16\x8b\x8e\xdd8\xc4\xe7p\xde-+jO\xc7\x1aHq\xc8&;\xc8\x1dd3\x8b\x9f\xac\xfah\x8b\xe3)\xfb\xa8\xd7\xf0\xfa\xdb\x7f\x8b\x11\xc5\x9d\x8f4\xc8\xef}\xcda&"K\x94NZf\xc7+7\x81\x03+4\x90\x93\xee\xf2p\xdf\xe6>\xff\xfb\xc6\xbf\xbb\xdej\x9d\x06\xc5\x99\x983\xcf\xefg\xc37;>W\x94SHw\xde+h\x8fS\x07(\x8d\x89\xe5\xfal\x8d\xa2>\xe9\xb2\xdc\xb7\xbb\xd1d\x99\x06\x97\xca\x9e<\xcf\xe33\xde 0&K\x94TZi\xce=5'), chr(100) + chr(0b11 + 0o142) + chr(99) + chr(111) + '\144' + '\145')(chr(117) + chr(116) + '\x66' + '\055' + chr(280 - 224)).format(AIvJRzLdDfgF)
xafqLlk3kkUe(fJoTPf8D_opC, xafqLlk3kkUe(SXOLrMavuUCe(b'\x92\x8b\x8f3'), '\144' + chr(0b11101 + 0o110) + '\143' + '\157' + '\144' + '\x65')(chr(117) + chr(0b1110100) + '\146' + chr(0b1100 + 0o41) + chr(56)))(jtbovtaIYjRB, hOkXjmluKZfJ)
|
pandas-dev/pandas
|
pandas/io/sql.py
|
SQLiteTable._create_table_setup
|
def _create_table_setup(self):
"""
Return a list of SQL statements that creates a table reflecting the
structure of a DataFrame. The first entry will be a CREATE TABLE
statement while the rest will be CREATE INDEX statements.
"""
column_names_and_types = self._get_column_names_and_types(
self._sql_type_name
)
pat = re.compile(r'\s+')
column_names = [col_name for col_name, _, _ in column_names_and_types]
if any(map(pat.search, column_names)):
warnings.warn(_SAFE_NAMES_WARNING, stacklevel=6)
escape = _get_valid_sqlite_name
create_tbl_stmts = [escape(cname) + ' ' + ctype
for cname, ctype, _ in column_names_and_types]
if self.keys is not None and len(self.keys):
if not is_list_like(self.keys):
keys = [self.keys]
else:
keys = self.keys
cnames_br = ", ".join(escape(c) for c in keys)
create_tbl_stmts.append(
"CONSTRAINT {tbl}_pk PRIMARY KEY ({cnames_br})".format(
tbl=self.name, cnames_br=cnames_br))
create_stmts = ["CREATE TABLE " + escape(self.name) + " (\n" +
',\n '.join(create_tbl_stmts) + "\n)"]
ix_cols = [cname for cname, _, is_index in column_names_and_types
if is_index]
if len(ix_cols):
cnames = "_".join(ix_cols)
cnames_br = ",".join(escape(c) for c in ix_cols)
create_stmts.append(
"CREATE INDEX " + escape("ix_" + self.name + "_" + cnames) +
"ON " + escape(self.name) + " (" + cnames_br + ")")
return create_stmts
|
python
|
def _create_table_setup(self):
"""
Return a list of SQL statements that creates a table reflecting the
structure of a DataFrame. The first entry will be a CREATE TABLE
statement while the rest will be CREATE INDEX statements.
"""
column_names_and_types = self._get_column_names_and_types(
self._sql_type_name
)
pat = re.compile(r'\s+')
column_names = [col_name for col_name, _, _ in column_names_and_types]
if any(map(pat.search, column_names)):
warnings.warn(_SAFE_NAMES_WARNING, stacklevel=6)
escape = _get_valid_sqlite_name
create_tbl_stmts = [escape(cname) + ' ' + ctype
for cname, ctype, _ in column_names_and_types]
if self.keys is not None and len(self.keys):
if not is_list_like(self.keys):
keys = [self.keys]
else:
keys = self.keys
cnames_br = ", ".join(escape(c) for c in keys)
create_tbl_stmts.append(
"CONSTRAINT {tbl}_pk PRIMARY KEY ({cnames_br})".format(
tbl=self.name, cnames_br=cnames_br))
create_stmts = ["CREATE TABLE " + escape(self.name) + " (\n" +
',\n '.join(create_tbl_stmts) + "\n)"]
ix_cols = [cname for cname, _, is_index in column_names_and_types
if is_index]
if len(ix_cols):
cnames = "_".join(ix_cols)
cnames_br = ",".join(escape(c) for c in ix_cols)
create_stmts.append(
"CREATE INDEX " + escape("ix_" + self.name + "_" + cnames) +
"ON " + escape(self.name) + " (" + cnames_br + ")")
return create_stmts
|
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] |
Return a list of SQL statements that creates a table reflecting the
structure of a DataFrame. The first entry will be a CREATE TABLE
statement while the rest will be CREATE INDEX statements.
|
[
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] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/io/sql.py#L1311-L1353
|
train
|
Returns a list of SQL statements that creates a table reflecting the theCOOKIE structure of the current DataFrame.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(1707 - 1659) + chr(111) + '\x31' + '\x30' + chr(0b110110), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(0b110001) + chr(2438 - 2388) + chr(2781 - 2728), ord("\x08")), ehT0Px3KOsy9(chr(0b100110 + 0o12) + chr(9773 - 9662) + chr(1500 - 1451) + '\x36', 47666 - 47658), ehT0Px3KOsy9(chr(778 - 730) + '\x6f' + chr(0b110101) + '\060', 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b101110 + 0o3) + chr(53) + chr(194 - 146), 50759 - 50751), ehT0Px3KOsy9(chr(0b100100 + 0o14) + '\157' + chr(0b110001) + chr(0b110101) + chr(0b1011 + 0o54), 0o10), ehT0Px3KOsy9(chr(0b10100 + 0o34) + '\x6f' + chr(735 - 685) + chr(0b110101) + chr(0b10000 + 0o40), 0o10), ehT0Px3KOsy9('\060' + chr(9040 - 8929) + chr(51) + chr(2097 - 2042) + '\x36', 0b1000), ehT0Px3KOsy9(chr(1724 - 1676) + '\157' + '\x37', 2702 - 2694), ehT0Px3KOsy9(chr(2140 - 2092) + chr(111) + chr(50) + '\064' + '\x37', 59142 - 59134), ehT0Px3KOsy9(chr(2123 - 2075) + '\x6f' + chr(0b101111 + 0o3) + chr(0b110000 + 0o3) + chr(0b11011 + 0o30), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1001001 + 0o46) + '\061' + chr(0b110100) + chr(1367 - 1315), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(6146 - 6035) + chr(0b10000 + 0o42) + chr(0b110100) + '\x36', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x33' + '\x37' + chr(0b110011), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(51) + '\x33' + chr(0b110101), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b1000 + 0o53) + '\x37' + '\x33', 8), ehT0Px3KOsy9(chr(48) + chr(0b111100 + 0o63) + chr(0b1100 + 0o46) + '\064' + chr(0b110011), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + '\063' + chr(0b110001) + chr(0b10 + 0o62), 49953 - 49945), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x31' + '\x32' + chr(0b100110 + 0o21), 24655 - 24647), ehT0Px3KOsy9('\x30' + chr(5378 - 5267) + chr(0b10111 + 0o34) + chr(52) + '\x31', 0o10), ehT0Px3KOsy9(chr(0b101101 + 0o3) + chr(0b1101111) + '\x32' + '\065' + chr(0b110100), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b1000 + 0o53) + chr(0b110111) + chr(0b110110), 8), ehT0Px3KOsy9(chr(1402 - 1354) + '\157' + chr(1722 - 1672), 19299 - 19291), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(1504 - 1454) + chr(0b11 + 0o60) + chr(0b101 + 0o56), 8), ehT0Px3KOsy9(chr(0b100110 + 0o12) + '\x6f' + '\x33' + chr(51) + '\x31', 47382 - 47374), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110011) + chr(0b110110) + chr(0b1000 + 0o54), 0b1000), ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(0b1010110 + 0o31) + chr(0b110010) + chr(1736 - 1683) + '\063', 23845 - 23837), ehT0Px3KOsy9(chr(0b100010 + 0o16) + chr(0b1010000 + 0o37) + chr(49) + '\x34' + chr(0b11111 + 0o25), 8), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b10110 + 0o34) + chr(55) + '\x31', 0b1000), ehT0Px3KOsy9('\x30' + chr(8322 - 8211) + '\063' + '\062', ord("\x08")), ehT0Px3KOsy9(chr(0b1111 + 0o41) + chr(0b1001101 + 0o42) + '\062' + chr(0b100001 + 0o21) + chr(0b110110), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(8545 - 8434) + chr(50) + '\x30', 0o10), ehT0Px3KOsy9(chr(1507 - 1459) + '\157' + chr(2312 - 2261) + chr(196 - 148) + chr(2347 - 2297), 10415 - 10407), ehT0Px3KOsy9(chr(0b101000 + 0o10) + chr(6493 - 6382) + chr(2066 - 2013) + '\x30', 8), ehT0Px3KOsy9('\x30' + '\x6f' + '\x32' + '\x36' + chr(0b1101 + 0o44), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110011) + chr(0b11011 + 0o27) + '\062', 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + '\067' + '\x33', 63761 - 63753), ehT0Px3KOsy9(chr(0b101100 + 0o4) + chr(0b101100 + 0o103) + chr(656 - 605) + chr(0b11111 + 0o22) + chr(55), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110011) + '\064' + chr(0b110101), 0b1000), ehT0Px3KOsy9('\060' + '\157' + '\x32' + '\x36' + chr(48), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + chr(6306 - 6195) + '\x35' + chr(48), 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'h'), chr(0b1100100) + chr(0b100101 + 0o100) + chr(99) + chr(7262 - 7151) + chr(100) + '\145')('\x75' + chr(0b1010 + 0o152) + chr(0b10100 + 0o122) + '\055' + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def LvWWj3uvwwqI(oVre8I6UXc3b):
bFLckXDrlGbQ = oVre8I6UXc3b._get_column_names_and_types(oVre8I6UXc3b._sql_type_name)
BumvCMvK3ogt = _7u55U49WwX2.compile(xafqLlk3kkUe(SXOLrMavuUCe(b'\x1a&%'), '\144' + chr(884 - 783) + '\x63' + chr(0b1101111) + chr(0b1100100) + '\145')(chr(0b1110101) + chr(9025 - 8909) + '\146' + '\x2d' + chr(56)))
Xw0ldSZpFZe4 = [W93rymQCbozJ for (W93rymQCbozJ, VNGQdHSFPrso, VNGQdHSFPrso) in bFLckXDrlGbQ]
if UVSi4XW7eBIM(abA97kOQKaLo(xafqLlk3kkUe(BumvCMvK3ogt, xafqLlk3kkUe(SXOLrMavuUCe(b'50oZ\x0b\x07'), '\x64' + chr(101) + chr(5967 - 5868) + '\157' + '\x64' + chr(101))(chr(0b1110101) + chr(116) + '\x66' + chr(0b101101) + chr(0b111000))), Xw0ldSZpFZe4)):
xafqLlk3kkUe(fJoTPf8D_opC, xafqLlk3kkUe(SXOLrMavuUCe(b'14|F'), chr(0b1 + 0o143) + chr(101) + '\143' + chr(0b1101111) + chr(0b10100 + 0o120) + chr(6891 - 6790))('\x75' + '\164' + chr(102) + chr(0b101101) + chr(0b101100 + 0o14)))(Ux_596rPtQO_, stacklevel=ehT0Px3KOsy9(chr(1029 - 981) + chr(111) + '\066', 0o10))
r5aqo2PTYhZy = lW_21TFceGCl
MjBY59CjAjYO = [r5aqo2PTYhZy(vtI4x3YoBm5h) + xafqLlk3kkUe(SXOLrMavuUCe(b'f'), chr(0b1011 + 0o131) + '\145' + chr(4832 - 4733) + '\x6f' + chr(100) + '\x65')(chr(117) + chr(0b111001 + 0o73) + chr(102) + '\x2d' + chr(56)) + VBDnCO4L2x91 for (vtI4x3YoBm5h, VBDnCO4L2x91, VNGQdHSFPrso) in bFLckXDrlGbQ]
if xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'-0w['), chr(0b1010101 + 0o17) + chr(0b1100101) + '\143' + chr(0b1101111) + chr(100) + chr(0b1100101))('\165' + chr(12020 - 11904) + chr(102) + chr(0b1011 + 0o42) + '\x38')) is not None and c2A0yzQpDQB3(xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'-0w['), chr(3056 - 2956) + '\145' + '\143' + '\x6f' + chr(0b1010 + 0o132) + '\x65')(chr(0b1110101) + '\x74' + chr(102) + chr(0b100101 + 0o10) + chr(56)))):
if not bAgBF7jXI53B(xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'-0w['), '\144' + '\145' + chr(0b1001110 + 0o25) + '\157' + chr(0b111111 + 0o45) + '\x65')(chr(0b1000010 + 0o63) + '\x74' + '\146' + chr(0b101011 + 0o2) + chr(0b111000)))):
w8H8C9ec5BO1 = [oVre8I6UXc3b.keys]
else:
w8H8C9ec5BO1 = oVre8I6UXc3b.keys
V88UtwfUkAcz = xafqLlk3kkUe(SXOLrMavuUCe(b'ju'), chr(0b1100100) + chr(0b1001000 + 0o35) + chr(0b111110 + 0o45) + chr(0b111101 + 0o62) + chr(0b10010 + 0o122) + chr(4849 - 4748))(chr(11690 - 11573) + chr(0b1110100) + '\146' + '\055' + chr(0b111000)).join((r5aqo2PTYhZy(qzn1Ctg9WgNh) for qzn1Ctg9WgNh in w8H8C9ec5BO1))
xafqLlk3kkUe(MjBY59CjAjYO, xafqLlk3kkUe(SXOLrMavuUCe(b"'%~M\x06\x0b"), '\x64' + '\x65' + chr(0b1100011) + chr(3256 - 3145) + chr(0b100101 + 0o77) + chr(0b1100101))(chr(117) + chr(0b1110100) + chr(102) + chr(0b1010 + 0o43) + '\x38'))(xafqLlk3kkUe(xafqLlk3kkUe(SXOLrMavuUCe(b'\x05\x1a@{<=\xe9\xb7I\xf3\xbb\x1f\xd2\x99\xb1\x86\xfc\xbc<\xc1\xfc\xacK\xd6\x98\xa6\xf2D\xf2_\xcf0\xeaS\xd2\xbcZ\xa2\x80\xc3\x197|UA'), chr(9645 - 9545) + chr(0b10010 + 0o123) + chr(0b1100011) + chr(0b1000110 + 0o51) + '\144' + chr(0b10101 + 0o120))(chr(0b1110101) + chr(116) + chr(102) + chr(0b101101) + chr(0b101111 + 0o11)), xafqLlk3kkUe(SXOLrMavuUCe(b' :|E\t\x1b'), chr(1720 - 1620) + chr(5630 - 5529) + chr(0b1100011) + chr(2226 - 2115) + '\x64' + chr(0b10100 + 0o121))('\x75' + chr(0b1010110 + 0o36) + '\x66' + '\x2d' + '\070'))(tbl=xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\x07\x1cxb:\x15\xe4\x9aC\xc1\xfc"'), chr(222 - 122) + chr(0b11000 + 0o115) + chr(0b111 + 0o134) + chr(0b1000 + 0o147) + chr(0b110100 + 0o60) + chr(0b1100101))('\165' + '\164' + '\x66' + chr(272 - 227) + '\x38')), cnames_br=V88UtwfUkAcz))
lucOdo_SYa1b = [xafqLlk3kkUe(SXOLrMavuUCe(b'\x05\x07Ki<*\x88\xaaF\xe5\xd7!\x86'), '\144' + chr(728 - 627) + '\x63' + chr(111) + '\144' + chr(101))('\x75' + chr(0b101001 + 0o113) + '\x66' + chr(1975 - 1930) + chr(56)) + r5aqo2PTYhZy(oVre8I6UXc3b.AIvJRzLdDfgF) + xafqLlk3kkUe(SXOLrMavuUCe(b'f}\x04'), '\x64' + chr(101) + '\143' + '\157' + '\144' + chr(0b111111 + 0o46))(chr(0b1110101) + chr(9252 - 9136) + chr(3281 - 3179) + chr(0b11000 + 0o25) + chr(56)) + xafqLlk3kkUe(SXOLrMavuUCe(b'j_.\x08'), chr(100) + chr(101) + chr(99) + chr(111) + chr(4404 - 4304) + '\145')(chr(117) + chr(11937 - 11821) + chr(0b1100110) + '\055' + chr(0b111000)).join(MjBY59CjAjYO) + xafqLlk3kkUe(SXOLrMavuUCe(b'L|'), chr(8966 - 8866) + '\145' + '\143' + chr(0b1100100 + 0o13) + '\144' + '\145')(chr(5390 - 5273) + chr(0b10 + 0o162) + chr(102) + chr(1508 - 1463) + '\070')]
WjXvBhCrMkBU = [vtI4x3YoBm5h for (vtI4x3YoBm5h, VNGQdHSFPrso, NqzcuhFmI3SG) in bFLckXDrlGbQ if NqzcuhFmI3SG]
if c2A0yzQpDQB3(WjXvBhCrMkBU):
lH75eIlUjGZV = xafqLlk3kkUe(SXOLrMavuUCe(b'\x19'), '\144' + chr(0b1100101) + chr(3992 - 3893) + chr(8616 - 8505) + chr(0b10110 + 0o116) + chr(0b1100101))(chr(117) + chr(0b1110100) + chr(102) + chr(0b101101) + chr(0b110000 + 0o10)).join(WjXvBhCrMkBU)
V88UtwfUkAcz = xafqLlk3kkUe(SXOLrMavuUCe(b'j'), '\x64' + chr(0b1000001 + 0o44) + chr(99) + chr(0b1101111) + chr(100) + '\145')('\x75' + chr(116) + chr(9868 - 9766) + chr(0b101101) + '\x38').join((r5aqo2PTYhZy(qzn1Ctg9WgNh) for qzn1Ctg9WgNh in WjXvBhCrMkBU))
xafqLlk3kkUe(lucOdo_SYa1b, xafqLlk3kkUe(SXOLrMavuUCe(b"'%~M\x06\x0b"), chr(2119 - 2019) + chr(0b1100101) + '\x63' + '\x6f' + chr(9134 - 9034) + chr(0b1100101))(chr(0b1110101) + chr(116) + chr(4041 - 3939) + '\055' + chr(1023 - 967)))(xafqLlk3kkUe(SXOLrMavuUCe(b'\x05\x07Ki<*\x88\xb7I\xe3\xde<\x86'), chr(1800 - 1700) + '\145' + chr(0b1100011) + '\x6f' + '\144' + '\x65')(chr(117) + chr(0b1101111 + 0o5) + chr(0b1100110) + chr(45) + chr(0b11011 + 0o35)) + r5aqo2PTYhZy(xafqLlk3kkUe(SXOLrMavuUCe(b'/-Q'), chr(0b1100100) + chr(0b1100101) + chr(99) + '\157' + chr(4276 - 4176) + '\145')('\165' + chr(12521 - 12405) + '\x66' + chr(672 - 627) + '\070') + xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\x07\x1cxb:\x15\xe4\x9aC\xc1\xfc"'), chr(1655 - 1555) + chr(0b1100101) + chr(99) + '\157' + chr(3215 - 3115) + '\145')(chr(2575 - 2458) + chr(0b1101111 + 0o5) + chr(102) + chr(45) + chr(1234 - 1178))) + xafqLlk3kkUe(SXOLrMavuUCe(b'\x19'), chr(0b1100100) + chr(101) + chr(819 - 720) + chr(0b1101111) + '\144' + chr(101))(chr(117) + chr(7032 - 6916) + chr(0b10110 + 0o120) + '\055' + '\070') + lH75eIlUjGZV) + xafqLlk3kkUe(SXOLrMavuUCe(b'\t\x1b.'), chr(0b1011100 + 0o10) + chr(1083 - 982) + '\143' + chr(0b1101111) + chr(0b1100000 + 0o4) + chr(9456 - 9355))(chr(0b1101111 + 0o6) + chr(0b1110100) + chr(9557 - 9455) + chr(1210 - 1165) + chr(2509 - 2453)) + r5aqo2PTYhZy(xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\x07\x1cxb:\x15\xe4\x9aC\xc1\xfc"'), chr(371 - 271) + '\145' + chr(1204 - 1105) + chr(0b1101111) + '\x64' + '\145')('\165' + chr(0b100111 + 0o115) + chr(0b101011 + 0o73) + chr(1293 - 1248) + chr(270 - 214)))) + xafqLlk3kkUe(SXOLrMavuUCe(b'f}'), chr(0b1000111 + 0o35) + chr(0b10001 + 0o124) + chr(0b1100011) + chr(5112 - 5001) + chr(0b100110 + 0o76) + chr(0b111110 + 0o47))(chr(0b11101 + 0o130) + chr(7362 - 7246) + chr(827 - 725) + chr(0b100011 + 0o12) + chr(56)) + V88UtwfUkAcz + xafqLlk3kkUe(SXOLrMavuUCe(b'o'), chr(6429 - 6329) + chr(5285 - 5184) + chr(4382 - 4283) + '\157' + chr(100) + chr(0b1010100 + 0o21))('\165' + chr(0b101010 + 0o112) + chr(0b101011 + 0o73) + chr(90 - 45) + chr(0b100001 + 0o27)))
return lucOdo_SYa1b
|
pandas-dev/pandas
|
pandas/io/sql.py
|
SQLiteDatabase._query_iterator
|
def _query_iterator(cursor, chunksize, columns, index_col=None,
coerce_float=True, parse_dates=None):
"""Return generator through chunked result set"""
while True:
data = cursor.fetchmany(chunksize)
if type(data) == tuple:
data = list(data)
if not data:
cursor.close()
break
else:
yield _wrap_result(data, columns, index_col=index_col,
coerce_float=coerce_float,
parse_dates=parse_dates)
|
python
|
def _query_iterator(cursor, chunksize, columns, index_col=None,
coerce_float=True, parse_dates=None):
"""Return generator through chunked result set"""
while True:
data = cursor.fetchmany(chunksize)
if type(data) == tuple:
data = list(data)
if not data:
cursor.close()
break
else:
yield _wrap_result(data, columns, index_col=index_col,
coerce_float=coerce_float,
parse_dates=parse_dates)
|
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] |
Return generator through chunked result set
|
[
"Return",
"generator",
"through",
"chunked",
"result",
"set"
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/io/sql.py#L1438-L1452
|
train
|
Return generator through chunked result set
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(1816 - 1768) + chr(111) + chr(0b11000 + 0o32) + '\x33' + '\x37', ord("\x08")), ehT0Px3KOsy9(chr(1484 - 1436) + '\x6f' + chr(0b110011 + 0o0) + chr(1745 - 1695) + chr(0b10100 + 0o40), 60477 - 60469), ehT0Px3KOsy9('\x30' + chr(530 - 419) + chr(0b110010) + chr(250 - 201), 47276 - 47268), ehT0Px3KOsy9(chr(0b101010 + 0o6) + chr(0b1101111) + chr(1911 - 1860) + chr(0b11011 + 0o27) + '\x32', 0b1000), ehT0Px3KOsy9(chr(854 - 806) + chr(0b1101001 + 0o6) + chr(283 - 234) + chr(84 - 30) + chr(48), 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(2658 - 2605) + chr(1185 - 1137), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b10 + 0o60) + '\x34' + chr(51), 57580 - 57572), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\060', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(1922 - 1811) + chr(49) + '\063' + '\061', 41947 - 41939), ehT0Px3KOsy9('\060' + '\157' + '\x31' + chr(0b10110 + 0o37) + chr(2247 - 2195), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1011110 + 0o21) + chr(0b10000 + 0o42) + chr(2371 - 2318) + '\061', 43214 - 43206), ehT0Px3KOsy9(chr(0b110000) + chr(1844 - 1733) + '\063' + chr(51), 0b1000), ehT0Px3KOsy9(chr(234 - 186) + chr(0b1101111) + '\x31' + '\062' + '\060', 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + '\066' + '\066', 30622 - 30614), ehT0Px3KOsy9('\x30' + chr(111) + chr(1909 - 1859) + chr(53) + chr(49), 8), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(49) + chr(55) + chr(0b110011), ord("\x08")), ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(0b101111 + 0o100) + chr(0b10010 + 0o37) + chr(50) + chr(52), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b111101 + 0o62) + '\x31' + chr(0b11101 + 0o25), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b111001 + 0o66) + '\062' + chr(1320 - 1268) + chr(275 - 225), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(1495 - 1446) + chr(0b101010 + 0o10) + chr(235 - 181), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(1086 - 1035) + '\062' + chr(49), 40830 - 40822), ehT0Px3KOsy9('\x30' + '\x6f' + '\062' + chr(0b110010) + '\x36', 0o10), ehT0Px3KOsy9(chr(0b101111 + 0o1) + '\x6f' + chr(0b110110) + '\064', 0o10), ehT0Px3KOsy9(chr(1057 - 1009) + chr(0b1101111) + chr(1724 - 1675) + chr(2153 - 2101) + '\x32', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(2367 - 2317) + '\065' + '\062', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(533 - 483) + '\060' + '\x34', 0b1000), ehT0Px3KOsy9(chr(1947 - 1899) + chr(111) + chr(53) + '\x33', 0o10), ehT0Px3KOsy9('\060' + chr(11190 - 11079) + chr(2423 - 2372) + chr(1640 - 1592) + chr(48), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(50) + '\067' + chr(54), 8345 - 8337), ehT0Px3KOsy9('\x30' + chr(0b110110 + 0o71) + chr(50) + '\067', 31525 - 31517), ehT0Px3KOsy9('\060' + chr(2268 - 2157) + chr(1437 - 1388) + chr(0b110100) + chr(1022 - 970), 54591 - 54583), ehT0Px3KOsy9(chr(0b11 + 0o55) + chr(0b1100111 + 0o10) + chr(0b110010) + chr(1008 - 959), 8), ehT0Px3KOsy9('\x30' + '\157' + '\061' + chr(241 - 190) + '\063', 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110001) + chr(0b110111) + chr(0b110001), 0b1000), ehT0Px3KOsy9(chr(389 - 341) + chr(111) + chr(0b11111 + 0o24) + chr(54) + chr(762 - 709), 38464 - 38456), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b11101 + 0o24) + '\062' + chr(0b110101 + 0o2), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(49) + chr(0b110010) + '\063', ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(0b110011) + chr(2291 - 2239) + '\x34', 0o10), ehT0Px3KOsy9('\x30' + '\157' + '\063' + '\062' + chr(0b1100 + 0o45), 8), ehT0Px3KOsy9(chr(0b100111 + 0o11) + chr(0b1101111) + chr(0b11010 + 0o27) + chr(0b110110) + chr(0b110001), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b10100 + 0o34) + '\157' + chr(1765 - 1712) + '\060', 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xb1'), chr(0b1100100) + '\x65' + chr(0b1100011) + '\157' + '\144' + chr(0b1100101))('\x75' + chr(116) + chr(102) + chr(0b101101) + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def ysyuhdWchnZj(jtcPmNZZo_gL, op94qe_Rdjul, qKlXBtn3PKy4, o90TMYhFhMm_=None, hyGdBsLYkQVS=ehT0Px3KOsy9('\x30' + '\157' + chr(0b1101 + 0o44), 30647 - 30639), T1brfYV34pPD=None):
while ehT0Px3KOsy9(chr(48) + chr(111) + chr(49), 8):
ULnjp6D6efFH = jtcPmNZZo_gL.fetchmany(op94qe_Rdjul)
if PlSM16l2KDPD(ULnjp6D6efFH, KNyTy8rYcwji):
ULnjp6D6efFH = YyaZ4tpXu4lf(ULnjp6D6efFH)
if not ULnjp6D6efFH:
xafqLlk3kkUe(jtcPmNZZo_gL, xafqLlk3kkUe(SXOLrMavuUCe(b'\xfc\xb8~\xa1\x15'), chr(0b1100001 + 0o3) + '\145' + chr(0b1100011) + chr(0b1101111) + chr(2712 - 2612) + chr(5090 - 4989))('\165' + chr(0b11110 + 0o126) + chr(0b1100110) + chr(0b101101) + '\070'))()
break
else:
yield jDdYdl3hJF1x(ULnjp6D6efFH, qKlXBtn3PKy4, index_col=o90TMYhFhMm_, coerce_float=hyGdBsLYkQVS, parse_dates=T1brfYV34pPD)
|
pandas-dev/pandas
|
pandas/io/sql.py
|
SQLiteDatabase.to_sql
|
def to_sql(self, frame, name, if_exists='fail', index=True,
index_label=None, schema=None, chunksize=None, dtype=None,
method=None):
"""
Write records stored in a DataFrame to a SQL database.
Parameters
----------
frame: DataFrame
name: string
Name of SQL table.
if_exists: {'fail', 'replace', 'append'}, default 'fail'
fail: If table exists, do nothing.
replace: If table exists, drop it, recreate it, and insert data.
append: If table exists, insert data. Create if it does not exist.
index : boolean, default True
Write DataFrame index as a column
index_label : string or sequence, default None
Column label for index column(s). If None is given (default) and
`index` is True, then the index names are used.
A sequence should be given if the DataFrame uses MultiIndex.
schema : string, default None
Ignored parameter included for compatibility with SQLAlchemy
version of ``to_sql``.
chunksize : int, default None
If not None, then rows will be written in batches of this
size at a time. If None, all rows will be written at once.
dtype : single type or dict of column name to SQL type, default None
Optional specifying the datatype for columns. The SQL type should
be a string. If all columns are of the same type, one single value
can be used.
method : {None, 'multi', callable}, default None
Controls the SQL insertion clause used:
* None : Uses standard SQL ``INSERT`` clause (one per row).
* 'multi': Pass multiple values in a single ``INSERT`` clause.
* callable with signature ``(pd_table, conn, keys, data_iter)``.
Details and a sample callable implementation can be found in the
section :ref:`insert method <io.sql.method>`.
.. versionadded:: 0.24.0
"""
if dtype and not is_dict_like(dtype):
dtype = {col_name: dtype for col_name in frame}
if dtype is not None:
for col, my_type in dtype.items():
if not isinstance(my_type, str):
raise ValueError('{column} ({type!s}) not a string'.format(
column=col, type=my_type))
table = SQLiteTable(name, self, frame=frame, index=index,
if_exists=if_exists, index_label=index_label,
dtype=dtype)
table.create()
table.insert(chunksize, method)
|
python
|
def to_sql(self, frame, name, if_exists='fail', index=True,
index_label=None, schema=None, chunksize=None, dtype=None,
method=None):
"""
Write records stored in a DataFrame to a SQL database.
Parameters
----------
frame: DataFrame
name: string
Name of SQL table.
if_exists: {'fail', 'replace', 'append'}, default 'fail'
fail: If table exists, do nothing.
replace: If table exists, drop it, recreate it, and insert data.
append: If table exists, insert data. Create if it does not exist.
index : boolean, default True
Write DataFrame index as a column
index_label : string or sequence, default None
Column label for index column(s). If None is given (default) and
`index` is True, then the index names are used.
A sequence should be given if the DataFrame uses MultiIndex.
schema : string, default None
Ignored parameter included for compatibility with SQLAlchemy
version of ``to_sql``.
chunksize : int, default None
If not None, then rows will be written in batches of this
size at a time. If None, all rows will be written at once.
dtype : single type or dict of column name to SQL type, default None
Optional specifying the datatype for columns. The SQL type should
be a string. If all columns are of the same type, one single value
can be used.
method : {None, 'multi', callable}, default None
Controls the SQL insertion clause used:
* None : Uses standard SQL ``INSERT`` clause (one per row).
* 'multi': Pass multiple values in a single ``INSERT`` clause.
* callable with signature ``(pd_table, conn, keys, data_iter)``.
Details and a sample callable implementation can be found in the
section :ref:`insert method <io.sql.method>`.
.. versionadded:: 0.24.0
"""
if dtype and not is_dict_like(dtype):
dtype = {col_name: dtype for col_name in frame}
if dtype is not None:
for col, my_type in dtype.items():
if not isinstance(my_type, str):
raise ValueError('{column} ({type!s}) not a string'.format(
column=col, type=my_type))
table = SQLiteTable(name, self, frame=frame, index=index,
if_exists=if_exists, index_label=index_label,
dtype=dtype)
table.create()
table.insert(chunksize, method)
|
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] |
Write records stored in a DataFrame to a SQL database.
Parameters
----------
frame: DataFrame
name: string
Name of SQL table.
if_exists: {'fail', 'replace', 'append'}, default 'fail'
fail: If table exists, do nothing.
replace: If table exists, drop it, recreate it, and insert data.
append: If table exists, insert data. Create if it does not exist.
index : boolean, default True
Write DataFrame index as a column
index_label : string or sequence, default None
Column label for index column(s). If None is given (default) and
`index` is True, then the index names are used.
A sequence should be given if the DataFrame uses MultiIndex.
schema : string, default None
Ignored parameter included for compatibility with SQLAlchemy
version of ``to_sql``.
chunksize : int, default None
If not None, then rows will be written in batches of this
size at a time. If None, all rows will be written at once.
dtype : single type or dict of column name to SQL type, default None
Optional specifying the datatype for columns. The SQL type should
be a string. If all columns are of the same type, one single value
can be used.
method : {None, 'multi', callable}, default None
Controls the SQL insertion clause used:
* None : Uses standard SQL ``INSERT`` clause (one per row).
* 'multi': Pass multiple values in a single ``INSERT`` clause.
* callable with signature ``(pd_table, conn, keys, data_iter)``.
Details and a sample callable implementation can be found in the
section :ref:`insert method <io.sql.method>`.
.. versionadded:: 0.24.0
|
[
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"records",
"stored",
"in",
"a",
"DataFrame",
"to",
"a",
"SQL",
"database",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/io/sql.py#L1481-L1537
|
train
|
Write records stored in a DataFrame to a SQL database.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(1686 - 1638) + '\157' + chr(49) + '\x35' + chr(0b1100 + 0o53), 0o10), ehT0Px3KOsy9(chr(2197 - 2149) + '\x6f' + chr(0b101101 + 0o10) + chr(0b100 + 0o55), 0b1000), ehT0Px3KOsy9(chr(48) + chr(10979 - 10868) + chr(50) + '\062' + chr(1262 - 1207), 0b1000), ehT0Px3KOsy9(chr(1125 - 1077) + chr(111) + chr(0b100111 + 0o16) + chr(48), 0o10), ehT0Px3KOsy9(chr(232 - 184) + chr(0b1101111) + chr(0b11010 + 0o27) + '\065', 62091 - 62083), ehT0Px3KOsy9('\x30' + '\157' + chr(49) + chr(0b110011) + '\064', ord("\x08")), ehT0Px3KOsy9(chr(1880 - 1832) + chr(0b110101 + 0o72) + chr(1763 - 1714) + chr(0b110111) + chr(52), ord("\x08")), ehT0Px3KOsy9(chr(0b10001 + 0o37) + chr(111) + '\066' + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + '\x33' + chr(48) + '\061', ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + '\x37' + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110010) + chr(0b110111 + 0o0) + chr(0b110010), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110011 + 0o2) + chr(0b101110 + 0o4), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(51) + chr(54) + chr(0b110101), 0o10), ehT0Px3KOsy9('\x30' + chr(0b10101 + 0o132) + chr(2190 - 2139) + chr(76 - 23) + chr(0b110011), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(8878 - 8767) + chr(0b110001) + '\x35' + '\x37', 8), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x35' + '\x37', 50574 - 50566), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x33' + '\x35' + '\x36', 61923 - 61915), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b100110 + 0o17) + chr(2616 - 2563), 0b1000), ehT0Px3KOsy9(chr(0b1011 + 0o45) + '\x6f' + '\x34' + '\x32', ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(50) + chr(52), 40226 - 40218), ehT0Px3KOsy9(chr(0b1110 + 0o42) + '\x6f' + '\061' + chr(49) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\063' + chr(0b11100 + 0o26) + chr(54), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110011 + 0o0) + chr(0b1110 + 0o46) + chr(54), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x33' + chr(1536 - 1484) + chr(0b110011 + 0o3), 8), ehT0Px3KOsy9(chr(0b10001 + 0o37) + chr(0b110101 + 0o72) + chr(406 - 356) + chr(0b110001) + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(0b100001 + 0o17) + chr(1410 - 1299) + chr(51) + '\062' + '\064', 0o10), ehT0Px3KOsy9('\x30' + chr(8364 - 8253) + '\061' + chr(2931 - 2876) + chr(0b110001), 31909 - 31901), ehT0Px3KOsy9('\060' + chr(0b10111 + 0o130) + chr(2414 - 2364) + '\062', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1000001 + 0o56) + chr(51) + '\x37', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(11933 - 11822) + '\x32' + chr(51) + '\065', 0b1000), ehT0Px3KOsy9(chr(0b10001 + 0o37) + chr(6110 - 5999) + chr(0b110010) + chr(1141 - 1091), 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b111 + 0o150) + '\x34', 0o10), ehT0Px3KOsy9('\x30' + chr(111) + '\061' + chr(1032 - 984) + chr(52), 31032 - 31024), ehT0Px3KOsy9(chr(0b100100 + 0o14) + chr(0b1011010 + 0o25) + chr(1656 - 1606) + chr(0b1100 + 0o51) + '\x30', 52712 - 52704), ehT0Px3KOsy9('\x30' + chr(9793 - 9682) + chr(969 - 920) + chr(0b101000 + 0o14) + chr(0b110110), 0o10), ehT0Px3KOsy9(chr(292 - 244) + chr(8521 - 8410) + '\061' + '\062' + chr(0b110000), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1000000 + 0o57) + chr(0b10001 + 0o44) + '\061', 8), ehT0Px3KOsy9(chr(0b100001 + 0o17) + '\157' + chr(1648 - 1598) + chr(0b110111) + chr(0b1100 + 0o44), 18585 - 18577), ehT0Px3KOsy9('\x30' + '\x6f' + chr(1548 - 1497) + chr(0b110011) + chr(0b110011), 0o10), ehT0Px3KOsy9('\060' + '\157' + '\x32' + chr(49) + chr(50), 8)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + chr(0b1101110 + 0o1) + chr(0b1001 + 0o54) + chr(330 - 282), 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'A'), '\x64' + chr(0b11100 + 0o111) + chr(99) + chr(0b1101111) + chr(0b1100011 + 0o1) + chr(101))('\x75' + '\x74' + chr(0b110110 + 0o60) + chr(0b100101 + 0o10) + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def b6tBeYOjJJGT(oVre8I6UXc3b, C4IqNNmLfHXB, AIvJRzLdDfgF, zZFPtODM90fp=xafqLlk3kkUe(SXOLrMavuUCe(b'\tH\xfeD'), chr(6194 - 6094) + chr(0b1010111 + 0o16) + chr(0b1100011) + '\x6f' + chr(0b1100001 + 0o3) + '\145')('\165' + chr(0b1000111 + 0o55) + chr(0b1010111 + 0o17) + chr(309 - 264) + chr(56)), XdowRbJKZWL9=ehT0Px3KOsy9(chr(0b11 + 0o55) + chr(111) + '\x31', 0b1000), Rj5_q03bvJPB=None, P7DmIFVRivx6=None, op94qe_Rdjul=None, jSV9IKnemH7K=None, CVRCXTcnOnH6=None):
if jSV9IKnemH7K and (not KwJXno8t8wVV(jSV9IKnemH7K)):
jSV9IKnemH7K = {W93rymQCbozJ: jSV9IKnemH7K for W93rymQCbozJ in C4IqNNmLfHXB}
if jSV9IKnemH7K is not None:
for (Qa2uSJqQPT3w, PgUW1UssNxfH) in xafqLlk3kkUe(jSV9IKnemH7K, xafqLlk3kkUe(SXOLrMavuUCe(b'\x06]\xf2E~'), '\144' + '\145' + chr(99) + chr(0b1101111) + chr(100) + chr(0b1100011 + 0o2))(chr(117) + '\x74' + '\146' + chr(0b101101) + chr(0b1111 + 0o51)))():
if not PlSM16l2KDPD(PgUW1UssNxfH, M8_cKLkHVB2V):
raise q1QCh3W88sgk(xafqLlk3kkUe(xafqLlk3kkUe(SXOLrMavuUCe(b'\x14J\xf8Dx1\x12L\xe1\x12\xc1^\x8c\x9b\n\x0e\x9dP\x0b4#\xb9\x92\xc6\xeb\xf4\nfm\xf4|c'), chr(0b111010 + 0o52) + '\x65' + chr(0b1100011) + '\x6f' + chr(100) + chr(3092 - 2991))(chr(0b110010 + 0o103) + chr(8588 - 8472) + '\146' + chr(45) + chr(0b101000 + 0o20)), xafqLlk3kkUe(SXOLrMavuUCe(b'\tF\xe5El('), chr(100) + chr(101) + '\x63' + '\x6f' + '\144' + '\145')(chr(0b11101 + 0o130) + '\x74' + '\146' + chr(0b101101) + '\x38'))(column=Qa2uSJqQPT3w, type=PgUW1UssNxfH))
YbLi4ide0_3E = DibIiDH57Xhu(AIvJRzLdDfgF, oVre8I6UXc3b, frame=C4IqNNmLfHXB, index=XdowRbJKZWL9, if_exists=zZFPtODM90fp, index_label=Rj5_q03bvJPB, dtype=jSV9IKnemH7K)
xafqLlk3kkUe(YbLi4ide0_3E, xafqLlk3kkUe(SXOLrMavuUCe(b'\x0c[\xf2Iy9'), chr(5857 - 5757) + chr(101) + '\x63' + chr(0b1101111) + chr(100) + '\x65')('\x75' + '\164' + '\146' + '\x2d' + '\070'))()
xafqLlk3kkUe(YbLi4ide0_3E, xafqLlk3kkUe(SXOLrMavuUCe(b'\x06G\xe4M\x7f('), chr(4197 - 4097) + '\x65' + chr(0b1010001 + 0o22) + chr(0b1101111) + '\x64' + chr(2374 - 2273))(chr(0b0 + 0o165) + chr(116) + '\x66' + chr(0b101101) + chr(978 - 922)))(op94qe_Rdjul, CVRCXTcnOnH6)
|
pandas-dev/pandas
|
pandas/core/arrays/categorical.py
|
_maybe_to_categorical
|
def _maybe_to_categorical(array):
"""
Coerce to a categorical if a series is given.
Internal use ONLY.
"""
if isinstance(array, (ABCSeries, ABCCategoricalIndex)):
return array._values
elif isinstance(array, np.ndarray):
return Categorical(array)
return array
|
python
|
def _maybe_to_categorical(array):
"""
Coerce to a categorical if a series is given.
Internal use ONLY.
"""
if isinstance(array, (ABCSeries, ABCCategoricalIndex)):
return array._values
elif isinstance(array, np.ndarray):
return Categorical(array)
return array
|
[
"def",
"_maybe_to_categorical",
"(",
"array",
")",
":",
"if",
"isinstance",
"(",
"array",
",",
"(",
"ABCSeries",
",",
"ABCCategoricalIndex",
")",
")",
":",
"return",
"array",
".",
"_values",
"elif",
"isinstance",
"(",
"array",
",",
"np",
".",
"ndarray",
")",
":",
"return",
"Categorical",
"(",
"array",
")",
"return",
"array"
] |
Coerce to a categorical if a series is given.
Internal use ONLY.
|
[
"Coerce",
"to",
"a",
"categorical",
"if",
"a",
"series",
"is",
"given",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/arrays/categorical.py#L131-L141
|
train
|
Coerce to a categorical if a series is given.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(48) + '\157' + '\x32' + chr(2130 - 2075) + chr(2060 - 2009), 1349 - 1341), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(51) + '\062' + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(337 - 286) + chr(0b11001 + 0o27) + chr(0b1001 + 0o52), 0o10), ehT0Px3KOsy9(chr(0b11101 + 0o23) + chr(111) + chr(0b100001 + 0o20) + chr(0b1 + 0o57) + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1001111 + 0o40) + chr(2232 - 2181) + '\064' + chr(0b110001), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b100101 + 0o112) + chr(0b110010) + '\062' + chr(793 - 745), 0b1000), ehT0Px3KOsy9(chr(1191 - 1143) + chr(111) + '\x31' + '\x36' + chr(1236 - 1187), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(1502 - 1453) + '\061' + '\x30', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1011111 + 0o20) + chr(2420 - 2369) + chr(0b110100), 0o10), ehT0Px3KOsy9('\x30' + chr(7670 - 7559) + chr(1095 - 1045) + chr(48) + chr(2091 - 2036), 5154 - 5146), ehT0Px3KOsy9(chr(48) + chr(0b1 + 0o156) + chr(0b101011 + 0o14) + chr(0b110010 + 0o0), 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + '\062' + chr(1924 - 1875) + chr(0b110001), 4324 - 4316), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\062' + chr(0b110011) + chr(0b110001), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b10001 + 0o42) + chr(0b1100 + 0o51) + chr(1718 - 1669), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b101110 + 0o10), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110101) + '\x36', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(5040 - 4929) + '\x35' + chr(2681 - 2629), 50404 - 50396), ehT0Px3KOsy9(chr(2158 - 2110) + chr(111) + chr(0b110001) + '\x31', 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b101110 + 0o3) + chr(737 - 687) + chr(50), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b111 + 0o54) + chr(124 - 74) + chr(2490 - 2439), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(49) + chr(0b110011) + chr(53), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1011111 + 0o20) + chr(0b110010) + '\067' + chr(50), 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(0b10101 + 0o34) + '\065' + '\062', 0b1000), ehT0Px3KOsy9(chr(0b0 + 0o60) + chr(0b1101111) + '\x32' + '\061', 27952 - 27944), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110011) + '\x30' + chr(48), 0b1000), ehT0Px3KOsy9('\x30' + chr(6316 - 6205) + chr(2575 - 2524) + chr(0b110001) + chr(2707 - 2654), 12284 - 12276), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(1182 - 1132) + '\066', ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(0b1110 + 0o43) + chr(0b11011 + 0o26) + '\065', 0o10), ehT0Px3KOsy9(chr(1174 - 1126) + chr(0b1101111) + '\x33' + chr(0b110000) + chr(0b101100 + 0o13), 18572 - 18564), ehT0Px3KOsy9(chr(348 - 300) + chr(0b10010 + 0o135) + chr(53) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110010) + chr(0b110001), 8), ehT0Px3KOsy9(chr(0b110000) + chr(8486 - 8375) + chr(0b10111 + 0o33) + chr(55) + chr(0b1001 + 0o53), 0b1000), ehT0Px3KOsy9(chr(48) + chr(7749 - 7638) + chr(49) + '\066' + chr(53), ord("\x08")), ehT0Px3KOsy9(chr(1145 - 1097) + chr(111) + chr(0b11010 + 0o31) + '\x34' + '\x37', 30866 - 30858), ehT0Px3KOsy9(chr(0b100001 + 0o17) + '\x6f' + '\x34' + chr(54), 0o10), ehT0Px3KOsy9(chr(2263 - 2215) + '\x6f' + chr(49) + '\066' + '\065', 8), ehT0Px3KOsy9('\060' + chr(10101 - 9990) + chr(51) + chr(2197 - 2148) + '\066', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(231 - 177) + chr(2213 - 2165), 61753 - 61745), ehT0Px3KOsy9(chr(48) + chr(0b101000 + 0o107) + chr(0b110001) + chr(874 - 823) + chr(0b110011 + 0o0), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(4743 - 4632) + '\062' + '\x33' + chr(0b110010), 53646 - 53638)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b100101 + 0o13) + '\x6f' + chr(0b11 + 0o62) + chr(0b110000), 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x95'), chr(0b11001 + 0o113) + '\145' + chr(0b1100011) + chr(0b101001 + 0o106) + chr(0b1100100) + chr(0b1100101))(chr(4395 - 4278) + '\164' + chr(0b1000101 + 0o41) + chr(0b1100 + 0o41) + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def _MTomSOwj9B3(B0ePDhpqxN5n):
if PlSM16l2KDPD(B0ePDhpqxN5n, (essMXh4s9f1w, Ou_oEUbhlMXT)):
return xafqLlk3kkUe(B0ePDhpqxN5n, xafqLlk3kkUe(SXOLrMavuUCe(b'\xe4\xa7\xa2*\x94\xf5\x02'), chr(100) + chr(0b111110 + 0o47) + '\143' + chr(111) + chr(100) + '\x65')(chr(9937 - 9820) + '\164' + chr(2249 - 2147) + chr(868 - 823) + '\x38'))
elif PlSM16l2KDPD(B0ePDhpqxN5n, xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\xd5\xb5\xa24\x93\xf1\x08'), '\144' + chr(0b1100101) + '\x63' + chr(111) + '\144' + '\145')('\x75' + chr(3568 - 3452) + chr(102) + chr(570 - 525) + chr(910 - 854)))):
return XxOW0_jwnido(B0ePDhpqxN5n)
return B0ePDhpqxN5n
|
pandas-dev/pandas
|
pandas/core/arrays/categorical.py
|
contains
|
def contains(cat, key, container):
"""
Helper for membership check for ``key`` in ``cat``.
This is a helper method for :method:`__contains__`
and :class:`CategoricalIndex.__contains__`.
Returns True if ``key`` is in ``cat.categories`` and the
location of ``key`` in ``categories`` is in ``container``.
Parameters
----------
cat : :class:`Categorical`or :class:`categoricalIndex`
key : a hashable object
The key to check membership for.
container : Container (e.g. list-like or mapping)
The container to check for membership in.
Returns
-------
is_in : bool
True if ``key`` is in ``self.categories`` and location of
``key`` in ``categories`` is in ``container``, else False.
Notes
-----
This method does not check for NaN values. Do that separately
before calling this method.
"""
hash(key)
# get location of key in categories.
# If a KeyError, the key isn't in categories, so logically
# can't be in container either.
try:
loc = cat.categories.get_loc(key)
except KeyError:
return False
# loc is the location of key in categories, but also the *value*
# for key in container. So, `key` may be in categories,
# but still not in `container`. Example ('b' in categories,
# but not in values):
# 'b' in Categorical(['a'], categories=['a', 'b']) # False
if is_scalar(loc):
return loc in container
else:
# if categories is an IntervalIndex, loc is an array.
return any(loc_ in container for loc_ in loc)
|
python
|
def contains(cat, key, container):
"""
Helper for membership check for ``key`` in ``cat``.
This is a helper method for :method:`__contains__`
and :class:`CategoricalIndex.__contains__`.
Returns True if ``key`` is in ``cat.categories`` and the
location of ``key`` in ``categories`` is in ``container``.
Parameters
----------
cat : :class:`Categorical`or :class:`categoricalIndex`
key : a hashable object
The key to check membership for.
container : Container (e.g. list-like or mapping)
The container to check for membership in.
Returns
-------
is_in : bool
True if ``key`` is in ``self.categories`` and location of
``key`` in ``categories`` is in ``container``, else False.
Notes
-----
This method does not check for NaN values. Do that separately
before calling this method.
"""
hash(key)
# get location of key in categories.
# If a KeyError, the key isn't in categories, so logically
# can't be in container either.
try:
loc = cat.categories.get_loc(key)
except KeyError:
return False
# loc is the location of key in categories, but also the *value*
# for key in container. So, `key` may be in categories,
# but still not in `container`. Example ('b' in categories,
# but not in values):
# 'b' in Categorical(['a'], categories=['a', 'b']) # False
if is_scalar(loc):
return loc in container
else:
# if categories is an IntervalIndex, loc is an array.
return any(loc_ in container for loc_ in loc)
|
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] |
Helper for membership check for ``key`` in ``cat``.
This is a helper method for :method:`__contains__`
and :class:`CategoricalIndex.__contains__`.
Returns True if ``key`` is in ``cat.categories`` and the
location of ``key`` in ``categories`` is in ``container``.
Parameters
----------
cat : :class:`Categorical`or :class:`categoricalIndex`
key : a hashable object
The key to check membership for.
container : Container (e.g. list-like or mapping)
The container to check for membership in.
Returns
-------
is_in : bool
True if ``key`` is in ``self.categories`` and location of
``key`` in ``categories`` is in ``container``, else False.
Notes
-----
This method does not check for NaN values. Do that separately
before calling this method.
|
[
"Helper",
"for",
"membership",
"check",
"for",
"key",
"in",
"cat",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/arrays/categorical.py#L144-L192
|
train
|
Returns True if key is in container False otherwise.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b110000) + chr(0b111110 + 0o61) + chr(0b110001) + '\x32', ord("\x08")), ehT0Px3KOsy9(chr(1902 - 1854) + chr(0b1011101 + 0o22) + chr(0b110001) + '\067' + chr(1712 - 1663), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110010) + chr(1431 - 1380) + '\062', 0b1000), ehT0Px3KOsy9('\060' + chr(111) + '\066' + chr(53), 0b1000), ehT0Px3KOsy9('\060' + chr(9070 - 8959) + chr(0b10100 + 0o37) + '\064' + chr(0b10001 + 0o40), 0b1000), ehT0Px3KOsy9(chr(0b10101 + 0o33) + chr(0b1101111) + '\063' + chr(0b101010 + 0o7) + chr(50), 0b1000), ehT0Px3KOsy9(chr(287 - 239) + chr(111) + '\061' + chr(0b110000), 62480 - 62472), ehT0Px3KOsy9('\x30' + chr(7524 - 7413) + '\x34' + chr(295 - 240), 59451 - 59443), ehT0Px3KOsy9(chr(48) + '\x6f' + '\061' + chr(55) + '\x33', 0o10), ehT0Px3KOsy9(chr(0b1001 + 0o47) + chr(111) + chr(0b1 + 0o60) + '\065' + chr(717 - 667), ord("\x08")), ehT0Px3KOsy9(chr(1725 - 1677) + '\157' + chr(0b100111 + 0o13) + '\x33' + chr(827 - 777), 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b1010011 + 0o34) + chr(0b110001) + chr(576 - 524) + chr(2444 - 2394), 0o10), ehT0Px3KOsy9(chr(1767 - 1719) + chr(0b1000000 + 0o57) + chr(49) + chr(0b110011 + 0o1) + chr(0b100101 + 0o20), 0o10), ehT0Px3KOsy9(chr(48) + chr(842 - 731) + chr(53) + chr(0b110010 + 0o3), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110001) + chr(0b110111) + '\061', 8), ehT0Px3KOsy9('\060' + chr(111) + chr(579 - 530) + '\061' + '\x36', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(1662 - 1613) + chr(0b101100 + 0o6) + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x32' + chr(50) + '\062', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1000101 + 0o52) + '\x35', 10197 - 10189), ehT0Px3KOsy9(chr(48) + chr(0b1100000 + 0o17) + chr(0b110011) + chr(0b11111 + 0o23), 0b1000), ehT0Px3KOsy9(chr(0b1101 + 0o43) + '\157' + '\x33' + '\066', 30117 - 30109), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b11011 + 0o30) + chr(55) + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + '\061' + chr(55) + chr(880 - 827), 0b1000), ehT0Px3KOsy9(chr(0b10101 + 0o33) + chr(111) + chr(0b110010) + '\x36' + chr(0b110001), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1000001 + 0o56) + chr(0b110011) + chr(1573 - 1522) + chr(1619 - 1570), ord("\x08")), ehT0Px3KOsy9(chr(0b11100 + 0o24) + chr(8112 - 8001) + '\x33' + '\x32' + chr(2226 - 2172), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(50) + '\x36' + chr(48), 0b1000), ehT0Px3KOsy9(chr(865 - 817) + chr(0b1101111) + chr(2108 - 2055), 8), ehT0Px3KOsy9(chr(0b0 + 0o60) + chr(111) + chr(2198 - 2149) + chr(0b110011), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\062' + chr(51) + chr(2039 - 1991), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\061' + chr(0b101111 + 0o6) + chr(2681 - 2626), 0b1000), ehT0Px3KOsy9('\x30' + '\157' + '\061' + chr(50) + '\063', 8), ehT0Px3KOsy9(chr(2119 - 2071) + '\x6f' + '\063' + chr(0b110100) + chr(343 - 289), 54742 - 54734), ehT0Px3KOsy9(chr(1894 - 1846) + chr(111) + chr(216 - 166) + chr(0b110001) + chr(52), 40186 - 40178), ehT0Px3KOsy9(chr(0b111 + 0o51) + chr(111) + '\x35' + '\x30', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(10263 - 10152) + chr(921 - 871) + chr(49) + '\064', 8), ehT0Px3KOsy9(chr(0b100100 + 0o14) + '\x6f' + chr(1838 - 1788) + chr(48), 0b1000), ehT0Px3KOsy9(chr(1761 - 1713) + chr(11591 - 11480) + '\x32' + chr(55) + '\063', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(50) + '\064' + '\x30', 16735 - 16727), ehT0Px3KOsy9('\060' + chr(111) + '\061' + chr(0b110011) + chr(0b110001), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110101) + chr(48), 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'$'), chr(4861 - 4761) + '\x65' + chr(99) + chr(0b1001 + 0o146) + '\x64' + chr(0b1100101))(chr(0b1000111 + 0o56) + chr(6232 - 6116) + chr(0b1011111 + 0o7) + '\055' + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def hJgVZSp3iMlY(re0VVGAVKu27, K3J4ZwSlE0sT, DCCEfdtuXq1i):
xfhwxiBOH72k(K3J4ZwSlE0sT)
try:
MmVY7Id_ODNA = re0VVGAVKu27.categories.get_loc(K3J4ZwSlE0sT)
except RQ6CSRrFArYB:
return ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110000), 0o10)
if aORqH388wQku(MmVY7Id_ODNA):
return MmVY7Id_ODNA in DCCEfdtuXq1i
else:
return UVSi4XW7eBIM((DiEp2P04Q4oi in DCCEfdtuXq1i for DiEp2P04Q4oi in MmVY7Id_ODNA))
|
pandas-dev/pandas
|
pandas/core/arrays/categorical.py
|
_get_codes_for_values
|
def _get_codes_for_values(values, categories):
"""
utility routine to turn values into codes given the specified categories
"""
from pandas.core.algorithms import _get_data_algo, _hashtables
dtype_equal = is_dtype_equal(values.dtype, categories.dtype)
if dtype_equal:
# To prevent erroneous dtype coercion in _get_data_algo, retrieve
# the underlying numpy array. gh-22702
values = getattr(values, '_ndarray_values', values)
categories = getattr(categories, '_ndarray_values', categories)
elif (is_extension_array_dtype(categories.dtype) and
is_object_dtype(values)):
# Support inferring the correct extension dtype from an array of
# scalar objects. e.g.
# Categorical(array[Period, Period], categories=PeriodIndex(...))
try:
values = (
categories.dtype.construct_array_type()._from_sequence(values)
)
except Exception:
# but that may fail for any reason, so fall back to object
values = ensure_object(values)
categories = ensure_object(categories)
else:
values = ensure_object(values)
categories = ensure_object(categories)
(hash_klass, vec_klass), vals = _get_data_algo(values, _hashtables)
(_, _), cats = _get_data_algo(categories, _hashtables)
t = hash_klass(len(cats))
t.map_locations(cats)
return coerce_indexer_dtype(t.lookup(vals), cats)
|
python
|
def _get_codes_for_values(values, categories):
"""
utility routine to turn values into codes given the specified categories
"""
from pandas.core.algorithms import _get_data_algo, _hashtables
dtype_equal = is_dtype_equal(values.dtype, categories.dtype)
if dtype_equal:
# To prevent erroneous dtype coercion in _get_data_algo, retrieve
# the underlying numpy array. gh-22702
values = getattr(values, '_ndarray_values', values)
categories = getattr(categories, '_ndarray_values', categories)
elif (is_extension_array_dtype(categories.dtype) and
is_object_dtype(values)):
# Support inferring the correct extension dtype from an array of
# scalar objects. e.g.
# Categorical(array[Period, Period], categories=PeriodIndex(...))
try:
values = (
categories.dtype.construct_array_type()._from_sequence(values)
)
except Exception:
# but that may fail for any reason, so fall back to object
values = ensure_object(values)
categories = ensure_object(categories)
else:
values = ensure_object(values)
categories = ensure_object(categories)
(hash_klass, vec_klass), vals = _get_data_algo(values, _hashtables)
(_, _), cats = _get_data_algo(categories, _hashtables)
t = hash_klass(len(cats))
t.map_locations(cats)
return coerce_indexer_dtype(t.lookup(vals), cats)
|
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] |
utility routine to turn values into codes given the specified categories
|
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] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/arrays/categorical.py#L2549-L2582
|
train
|
This utility routine returns the codes given the values and categories.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110010 + 0o1) + chr(0b1001 + 0o55) + chr(2396 - 2344), 0b1000), ehT0Px3KOsy9(chr(0b1110 + 0o42) + chr(0b1101111) + chr(2686 - 2631) + '\064', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(3958 - 3847) + chr(0b110011) + '\x37' + chr(0b0 + 0o61), 31338 - 31330), ehT0Px3KOsy9(chr(48) + chr(0b11101 + 0o122) + chr(1859 - 1809) + chr(51) + chr(48), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x31' + chr(0b110101) + chr(0b1101 + 0o51), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\061' + chr(50) + chr(50), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110010) + chr(75 - 26) + '\062', 51946 - 51938), ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(0b1101001 + 0o6) + '\x32' + chr(0b1 + 0o60) + chr(0b10110 + 0o33), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1000000 + 0o57) + '\063' + '\067' + chr(1384 - 1333), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\061' + chr(1114 - 1062), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1010 + 0o145) + chr(50) + chr(0b110101 + 0o2) + '\061', ord("\x08")), ehT0Px3KOsy9(chr(0b1010 + 0o46) + chr(0b1101111) + '\065' + chr(50), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + '\x31' + '\067' + chr(0b110111), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110001) + chr(0b1110 + 0o44) + chr(0b1010 + 0o50), 8), ehT0Px3KOsy9(chr(48) + chr(0b11101 + 0o122) + '\061' + chr(322 - 268) + chr(0b11010 + 0o33), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(51) + chr(0b1101 + 0o52) + chr(49), 8), ehT0Px3KOsy9('\060' + chr(111) + chr(0b101110 + 0o5) + chr(0b101101 + 0o3) + chr(49), 22614 - 22606), ehT0Px3KOsy9(chr(570 - 522) + '\x6f' + '\063' + '\x32' + chr(0b100101 + 0o14), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x31' + chr(1466 - 1415) + '\066', 27871 - 27863), ehT0Px3KOsy9(chr(0b100010 + 0o16) + '\157' + chr(0b110010) + chr(0b110110), 0o10), ehT0Px3KOsy9('\x30' + chr(6182 - 6071) + chr(0b1000 + 0o53) + chr(48) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110011) + chr(0b110100) + chr(49), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(999 - 948) + '\066' + chr(0b110100), 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b11000 + 0o33) + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(0b111 + 0o51) + chr(750 - 639) + chr(50) + chr(0b1111 + 0o42) + chr(0b101110 + 0o6), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b10111 + 0o130) + chr(786 - 737) + chr(320 - 272) + chr(49), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b111101 + 0o62) + chr(49) + chr(0b110111) + chr(1643 - 1593), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(803 - 753) + chr(0b101101 + 0o10) + chr(53), 0o10), ehT0Px3KOsy9(chr(2128 - 2080) + chr(111) + chr(1070 - 1021) + chr(54) + '\065', 8), ehT0Px3KOsy9(chr(48) + chr(111) + chr(1382 - 1333) + '\x36' + chr(0b101101 + 0o6), 0o10), ehT0Px3KOsy9(chr(0b101101 + 0o3) + '\157' + chr(720 - 669) + chr(567 - 514) + chr(0b11100 + 0o25), ord("\x08")), ehT0Px3KOsy9(chr(0b100001 + 0o17) + '\x6f' + chr(0b110001) + '\061' + chr(50), 23697 - 23689), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110001) + '\062' + chr(48), ord("\x08")), ehT0Px3KOsy9(chr(0b10011 + 0o35) + '\x6f' + chr(1175 - 1126) + chr(50) + chr(0b11011 + 0o33), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b100110 + 0o21) + chr(440 - 385), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x32' + '\062' + '\x30', 731 - 723), ehT0Px3KOsy9(chr(2270 - 2222) + chr(111) + '\061' + chr(1652 - 1600), 8), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(1976 - 1927) + chr(626 - 572) + '\x33', 8), ehT0Px3KOsy9(chr(1772 - 1724) + chr(111) + chr(0b110 + 0o55) + '\x30', 0o10), ehT0Px3KOsy9(chr(0b100010 + 0o16) + chr(111) + '\061' + chr(51), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110101) + chr(2059 - 2011), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xda'), chr(0b1100100) + chr(101) + '\143' + '\x6f' + chr(100) + chr(101))(chr(117) + chr(6838 - 6722) + chr(0b1100110) + chr(1292 - 1247) + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def SrdNuo8P440p(SPnCNu54H1db, mZZDAT49UzAb):
(XXUTrUA1yaHq, LEul_3kw5r1U) = (xafqLlk3kkUe(xafqLlk3kkUe(xafqLlk3kkUe(NPPHb59961Bv(xafqLlk3kkUe(SXOLrMavuUCe(b'\x84]\x97\xfc\x0f!\xa4\xea\x94~\xdc\x04\x1e>\x12\x96\xb3\xb8*~\xad\x92'), chr(0b1000010 + 0o42) + chr(0b1100101) + chr(99) + '\x6f' + chr(0b1001111 + 0o25) + chr(0b110101 + 0o60))('\x75' + '\164' + chr(102) + '\x2d' + '\x38'), xafqLlk3kkUe(SXOLrMavuUCe(b'\xab[\x9c\xec16\xeb\xfd\x9aS\xd8F\x18='), chr(729 - 629) + '\x65' + chr(803 - 704) + '\x6f' + '\144' + '\145')('\165' + chr(116) + chr(102) + chr(0b101101) + chr(0b101001 + 0o17))), xafqLlk3kkUe(SXOLrMavuUCe(b'\x97S\x8b\xfd'), chr(0b1100100) + chr(101) + chr(0b100111 + 0o74) + '\x6f' + chr(0b1100100) + chr(7913 - 7812))('\x75' + chr(0b1100111 + 0o15) + chr(0b1100110) + '\055' + chr(56))), xafqLlk3kkUe(SXOLrMavuUCe(b'\x95P\x9e\xf7\x1c;\xfe\xe1\x96\x7f'), chr(2470 - 2370) + '\145' + chr(6314 - 6215) + chr(7509 - 7398) + '\x64' + chr(0b1100101))(chr(9267 - 9150) + chr(0b1110100) + chr(9964 - 9862) + chr(1774 - 1729) + chr(0b110111 + 0o1))), xafqLlk3kkUe(SXOLrMavuUCe(b'\xab[\x9c\xec16\xeb\xfd\x9aS\xd8F\x18='), '\144' + '\x65' + chr(3018 - 2919) + chr(111) + '\x64' + chr(101))(chr(0b1011010 + 0o33) + chr(116) + chr(102) + '\055' + chr(0b111000))), xafqLlk3kkUe(xafqLlk3kkUe(xafqLlk3kkUe(NPPHb59961Bv(xafqLlk3kkUe(SXOLrMavuUCe(b'\x84]\x97\xfc\x0f!\xa4\xea\x94~\xdc\x04\x1e>\x12\x96\xb3\xb8*~\xad\x92'), '\x64' + chr(101) + chr(0b1100011) + chr(0b1000001 + 0o56) + chr(4474 - 4374) + '\145')(chr(0b1110101) + chr(0b1110100) + '\x66' + chr(0b101101) + chr(0b111000)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xabT\x98\xeb\x06&\xeb\xeb\x97i\xca'), chr(6032 - 5932) + '\145' + chr(99) + '\x6f' + chr(100) + chr(101))(chr(0b1100010 + 0o23) + chr(2292 - 2176) + chr(102) + chr(1745 - 1700) + chr(56))), xafqLlk3kkUe(SXOLrMavuUCe(b'\x97S\x8b\xfd'), chr(5107 - 5007) + chr(101) + '\143' + '\x6f' + chr(100) + chr(9306 - 9205))(chr(117) + chr(116) + chr(0b1100110) + chr(1181 - 1136) + '\070')), xafqLlk3kkUe(SXOLrMavuUCe(b'\x95P\x9e\xf7\x1c;\xfe\xe1\x96\x7f'), chr(4716 - 4616) + chr(0b1100101) + chr(5091 - 4992) + chr(0b1101111) + '\144' + '\145')(chr(0b1110101) + chr(0b1110100) + chr(0b1011111 + 0o7) + chr(45) + chr(537 - 481))), xafqLlk3kkUe(SXOLrMavuUCe(b'\xabT\x98\xeb\x06&\xeb\xeb\x97i\xca'), '\x64' + chr(0b1100101) + chr(587 - 488) + '\x6f' + chr(1797 - 1697) + chr(2411 - 2310))(chr(0b1110101) + '\164' + '\146' + chr(45) + chr(2173 - 2117))))
nzq7a3W9hvjF = V1zUTkhQur0z(SPnCNu54H1db.dtype, mZZDAT49UzAb.dtype)
if nzq7a3W9hvjF:
SPnCNu54H1db = xafqLlk3kkUe(SPnCNu54H1db, xafqLlk3kkUe(SXOLrMavuUCe(b'\xabR\x9d\xf9\x1c \xeb\xf0\xa4z\xd8F\n7\x06'), chr(100) + chr(101) + chr(600 - 501) + chr(0b1101111) + chr(0b1100100) + '\145')('\x75' + chr(0b1110100) + chr(0b1100110) + '\055' + '\070'), SPnCNu54H1db)
mZZDAT49UzAb = xafqLlk3kkUe(mZZDAT49UzAb, xafqLlk3kkUe(SXOLrMavuUCe(b'\xabR\x9d\xf9\x1c \xeb\xf0\xa4z\xd8F\n7\x06'), chr(0b1001100 + 0o30) + '\x65' + chr(515 - 416) + '\157' + chr(3239 - 3139) + '\x65')('\165' + chr(116) + chr(102) + chr(45) + chr(683 - 627)), mZZDAT49UzAb)
elif BeeaaSlTfmO2(xafqLlk3kkUe(mZZDAT49UzAb, xafqLlk3kkUe(SXOLrMavuUCe(b'\x90H\x80\xe8\x0b'), chr(0b1100100) + chr(0b1000101 + 0o40) + chr(0b1011110 + 0o5) + chr(111) + '\144' + '\145')(chr(0b1011100 + 0o31) + chr(0b1110100) + '\146' + chr(972 - 927) + chr(56)))) and NGkWsclKfnpq(SPnCNu54H1db):
try:
SPnCNu54H1db = mZZDAT49UzAb.dtype.construct_array_type()._from_sequence(SPnCNu54H1db)
except jLmadlzMdunT:
SPnCNu54H1db = vd4vF5cOhwLp(SPnCNu54H1db)
mZZDAT49UzAb = vd4vF5cOhwLp(mZZDAT49UzAb)
else:
SPnCNu54H1db = vd4vF5cOhwLp(SPnCNu54H1db)
mZZDAT49UzAb = vd4vF5cOhwLp(mZZDAT49UzAb)
((QXaNhVnhbARy, nC3Tem87KLEd), ipy0WJZo1Oft) = XXUTrUA1yaHq(SPnCNu54H1db, LEul_3kw5r1U)
((VNGQdHSFPrso, VNGQdHSFPrso), _IZEDmb5AMbL) = XXUTrUA1yaHq(mZZDAT49UzAb, LEul_3kw5r1U)
YeT3l7JgTbWR = QXaNhVnhbARy(c2A0yzQpDQB3(_IZEDmb5AMbL))
xafqLlk3kkUe(YeT3l7JgTbWR, xafqLlk3kkUe(SXOLrMavuUCe(b'\x99]\x89\xc7\x02=\xe9\xe8\x8fe\xd6D\x0c'), chr(0b1100100) + chr(0b1100101) + chr(99) + chr(1591 - 1480) + chr(0b1100100) + '\145')(chr(0b1110101) + '\x74' + chr(0b1110 + 0o130) + '\055' + chr(0b100000 + 0o30)))(_IZEDmb5AMbL)
return IhoUBFeIAvnv(xafqLlk3kkUe(YeT3l7JgTbWR, xafqLlk3kkUe(SXOLrMavuUCe(b'\x98S\x96\xf3\x1b"'), chr(0b1000110 + 0o36) + chr(5073 - 4972) + chr(0b1100011) + chr(0b1001000 + 0o47) + chr(0b10101 + 0o117) + chr(0b1100101))(chr(117) + '\x74' + chr(0b1100110) + chr(0b101101) + chr(0b111000)))(ipy0WJZo1Oft), _IZEDmb5AMbL)
|
pandas-dev/pandas
|
pandas/core/arrays/categorical.py
|
_recode_for_categories
|
def _recode_for_categories(codes, old_categories, new_categories):
"""
Convert a set of codes for to a new set of categories
Parameters
----------
codes : array
old_categories, new_categories : Index
Returns
-------
new_codes : array
Examples
--------
>>> old_cat = pd.Index(['b', 'a', 'c'])
>>> new_cat = pd.Index(['a', 'b'])
>>> codes = np.array([0, 1, 1, 2])
>>> _recode_for_categories(codes, old_cat, new_cat)
array([ 1, 0, 0, -1])
"""
from pandas.core.algorithms import take_1d
if len(old_categories) == 0:
# All null anyway, so just retain the nulls
return codes.copy()
elif new_categories.equals(old_categories):
# Same categories, so no need to actually recode
return codes.copy()
indexer = coerce_indexer_dtype(new_categories.get_indexer(old_categories),
new_categories)
new_codes = take_1d(indexer, codes.copy(), fill_value=-1)
return new_codes
|
python
|
def _recode_for_categories(codes, old_categories, new_categories):
"""
Convert a set of codes for to a new set of categories
Parameters
----------
codes : array
old_categories, new_categories : Index
Returns
-------
new_codes : array
Examples
--------
>>> old_cat = pd.Index(['b', 'a', 'c'])
>>> new_cat = pd.Index(['a', 'b'])
>>> codes = np.array([0, 1, 1, 2])
>>> _recode_for_categories(codes, old_cat, new_cat)
array([ 1, 0, 0, -1])
"""
from pandas.core.algorithms import take_1d
if len(old_categories) == 0:
# All null anyway, so just retain the nulls
return codes.copy()
elif new_categories.equals(old_categories):
# Same categories, so no need to actually recode
return codes.copy()
indexer = coerce_indexer_dtype(new_categories.get_indexer(old_categories),
new_categories)
new_codes = take_1d(indexer, codes.copy(), fill_value=-1)
return new_codes
|
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"take_1d",
"(",
"indexer",
",",
"codes",
".",
"copy",
"(",
")",
",",
"fill_value",
"=",
"-",
"1",
")",
"return",
"new_codes"
] |
Convert a set of codes for to a new set of categories
Parameters
----------
codes : array
old_categories, new_categories : Index
Returns
-------
new_codes : array
Examples
--------
>>> old_cat = pd.Index(['b', 'a', 'c'])
>>> new_cat = pd.Index(['a', 'b'])
>>> codes = np.array([0, 1, 1, 2])
>>> _recode_for_categories(codes, old_cat, new_cat)
array([ 1, 0, 0, -1])
|
[
"Convert",
"a",
"set",
"of",
"codes",
"for",
"to",
"a",
"new",
"set",
"of",
"categories"
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/arrays/categorical.py#L2585-L2617
|
train
|
Convert a set of codes for to a new set of categories
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + '\x6f' + '\065' + '\062', 0o10), ehT0Px3KOsy9(chr(1287 - 1239) + chr(0b1101111) + chr(0b110001) + '\066' + chr(0b100000 + 0o20), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(49) + chr(0b110010) + '\061', 0o10), ehT0Px3KOsy9(chr(459 - 411) + chr(0b1011000 + 0o27) + chr(49) + '\x35' + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(48) + chr(9674 - 9563) + chr(367 - 313) + '\061', 40895 - 40887), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(2317 - 2266) + '\x36' + chr(0b110011), 42036 - 42028), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b101111 + 0o3) + chr(905 - 857) + '\x30', 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + '\061' + chr(0b110101) + '\060', 0b1000), ehT0Px3KOsy9(chr(172 - 124) + '\157' + '\061' + '\064' + '\x34', ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + '\063' + chr(49), 35651 - 35643), ehT0Px3KOsy9('\x30' + chr(0b1000110 + 0o51) + chr(0b11110 + 0o24) + chr(0b110100) + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(668 - 620) + chr(0b11000 + 0o127) + '\x33' + chr(55) + chr(0b110001), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x33' + chr(50) + chr(1898 - 1846), 0b1000), ehT0Px3KOsy9(chr(254 - 206) + '\157' + chr(2049 - 1999) + chr(1705 - 1655) + chr(0b110001), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1001000 + 0o47) + chr(0b110011) + chr(0b101011 + 0o13) + chr(0b10101 + 0o40), 33939 - 33931), ehT0Px3KOsy9(chr(0b110 + 0o52) + chr(0b1101111) + '\061' + '\x31' + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(0b10101 + 0o33) + chr(0b1101111) + chr(0b110001) + chr(0b110011) + chr(53), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(1911 - 1858) + chr(0b110001), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b100010 + 0o17) + chr(0b110100 + 0o2) + chr(1513 - 1465), 8), ehT0Px3KOsy9('\x30' + '\x6f' + chr(50) + chr(0b110111), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b10110 + 0o131) + '\061' + '\060' + '\066', 0o10), ehT0Px3KOsy9(chr(2057 - 2009) + '\x6f' + chr(0b110010) + '\064' + chr(1798 - 1743), 25938 - 25930), ehT0Px3KOsy9(chr(0b110000) + chr(8084 - 7973) + chr(0b1011 + 0o46) + '\064' + '\x30', 5439 - 5431), ehT0Px3KOsy9(chr(2236 - 2188) + chr(5766 - 5655) + '\x33' + '\x31' + chr(50), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1000010 + 0o55) + '\x33' + '\066' + chr(0b110101), 8), ehT0Px3KOsy9('\x30' + '\157' + chr(50) + chr(1876 - 1827) + chr(783 - 733), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x33' + chr(416 - 365) + '\066', 51788 - 51780), ehT0Px3KOsy9(chr(0b101111 + 0o1) + '\x6f' + chr(1623 - 1573) + chr(170 - 121) + '\x33', 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + '\x33' + chr(1897 - 1849) + '\x34', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(1109 - 998) + '\062', ord("\x08")), ehT0Px3KOsy9(chr(1265 - 1217) + chr(4868 - 4757) + chr(0b10111 + 0o32) + chr(323 - 270) + '\x35', 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + '\x33' + '\x36' + chr(54), 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(0b10100 + 0o35) + '\062' + chr(0b110010), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + '\x31' + chr(0b11000 + 0o33) + '\060', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1011 + 0o144) + chr(0b110011) + chr(51) + chr(50), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110001), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b110100 + 0o73) + '\x31', 8), ehT0Px3KOsy9(chr(0b101101 + 0o3) + chr(111) + chr(0b110011) + chr(439 - 385), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(51) + '\060' + chr(517 - 464), ord("\x08")), ehT0Px3KOsy9(chr(906 - 858) + chr(111) + chr(0b110011) + chr(0b110100) + chr(53), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + chr(111) + '\065' + chr(0b110000), 16052 - 16044)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x04'), chr(0b1100100) + '\145' + '\143' + '\157' + chr(0b110011 + 0o61) + chr(101))(chr(117) + chr(8013 - 7897) + chr(1552 - 1450) + chr(0b1110 + 0o37) + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def V3m1SlhRYSW0(AoWJEgIAbHh_, uMS41nVaCB3S, QVK8u7RnAnpO):
(u8JncEabnCrx,) = (xafqLlk3kkUe(xafqLlk3kkUe(xafqLlk3kkUe(NPPHb59961Bv(xafqLlk3kkUe(SXOLrMavuUCe(b'Z\x11?\x0eP\x80\xae\x0b\x0bk\xc7\xd7\xb5\xfd\x92"/@\x04\x7f+\xd4'), '\144' + chr(8534 - 8433) + chr(0b10000 + 0o123) + '\x6f' + chr(0b1100000 + 0o4) + chr(0b1001111 + 0o26))(chr(117) + chr(2418 - 2302) + '\x66' + '\055' + chr(1876 - 1820)), xafqLlk3kkUe(SXOLrMavuUCe(b'^\x11:\x0fn\xc2\xe4'), chr(0b1011110 + 0o6) + chr(0b100111 + 0o76) + chr(0b1100011) + chr(5378 - 5267) + chr(0b1100100) + chr(101))(chr(117) + chr(116) + '\x66' + chr(0b101100 + 0o1) + '\x38')), xafqLlk3kkUe(SXOLrMavuUCe(b'I\x1f#\x0f'), chr(100) + chr(0b1100101) + chr(99) + chr(10518 - 10407) + '\144' + chr(0b1100101))('\x75' + chr(0b1110100) + chr(0b1010000 + 0o26) + '\x2d' + '\070')), xafqLlk3kkUe(SXOLrMavuUCe(b'K\x1c6\x05C\x9a\xf4\x00\tj'), '\144' + '\x65' + chr(3735 - 3636) + '\157' + '\x64' + chr(10038 - 9937))('\x75' + chr(8322 - 8206) + chr(102) + '\055' + chr(0b10001 + 0o47))), xafqLlk3kkUe(SXOLrMavuUCe(b'^\x11:\x0fn\xc2\xe4'), chr(0b1011111 + 0o5) + '\145' + chr(822 - 723) + chr(0b1101111) + chr(100) + chr(101))(chr(0b1110101) + chr(116) + chr(0b1100110) + chr(0b101101) + '\070')),)
if c2A0yzQpDQB3(uMS41nVaCB3S) == ehT0Px3KOsy9('\x30' + '\x6f' + chr(1316 - 1268), 10771 - 10763):
return xafqLlk3kkUe(AoWJEgIAbHh_, xafqLlk3kkUe(SXOLrMavuUCe(b'C\x17\x05\x02y\xa0\xb4\x02\x13O\xd1\x98'), chr(0b1110 + 0o126) + chr(0b1100101) + chr(8854 - 8755) + chr(111) + chr(100) + chr(0b1100101))(chr(0b1110101) + chr(0b1001110 + 0o46) + chr(102) + chr(0b101101) + chr(0b100100 + 0o24)))()
elif xafqLlk3kkUe(QVK8u7RnAnpO, xafqLlk3kkUe(SXOLrMavuUCe(b'O\x01$\x0b]\x80'), chr(100) + '\x65' + chr(6460 - 6361) + chr(111) + chr(100) + '\145')(chr(117) + chr(116) + chr(102) + chr(45) + chr(0b11 + 0o65)))(uMS41nVaCB3S):
return xafqLlk3kkUe(AoWJEgIAbHh_, xafqLlk3kkUe(SXOLrMavuUCe(b'C\x17\x05\x02y\xa0\xb4\x02\x13O\xd1\x98'), chr(0b1100000 + 0o4) + chr(2351 - 2250) + chr(3647 - 3548) + chr(111) + chr(0b1100100) + '\145')(chr(117) + chr(5613 - 5497) + chr(0b1100110) + chr(0b101101) + '\x38'))()
BvJfssszZMhp = IhoUBFeIAvnv(QVK8u7RnAnpO.XZES6opsvx5w(uMS41nVaCB3S), QVK8u7RnAnpO)
ZOp_qeUX5QuP = u8JncEabnCrx(BvJfssszZMhp, AoWJEgIAbHh_.igThHS4jwVsa(), fill_value=-ehT0Px3KOsy9('\060' + chr(0b11000 + 0o127) + chr(1234 - 1185), 8))
return ZOp_qeUX5QuP
|
pandas-dev/pandas
|
pandas/core/arrays/categorical.py
|
_factorize_from_iterable
|
def _factorize_from_iterable(values):
"""
Factorize an input `values` into `categories` and `codes`. Preserves
categorical dtype in `categories`.
*This is an internal function*
Parameters
----------
values : list-like
Returns
-------
codes : ndarray
categories : Index
If `values` has a categorical dtype, then `categories` is
a CategoricalIndex keeping the categories and order of `values`.
"""
from pandas.core.indexes.category import CategoricalIndex
if not is_list_like(values):
raise TypeError("Input must be list-like")
if is_categorical(values):
if isinstance(values, (ABCCategoricalIndex, ABCSeries)):
values = values._values
categories = CategoricalIndex(values.categories, dtype=values.dtype)
codes = values.codes
else:
# The value of ordered is irrelevant since we don't use cat as such,
# but only the resulting categories, the order of which is independent
# from ordered. Set ordered to False as default. See GH #15457
cat = Categorical(values, ordered=False)
categories = cat.categories
codes = cat.codes
return codes, categories
|
python
|
def _factorize_from_iterable(values):
"""
Factorize an input `values` into `categories` and `codes`. Preserves
categorical dtype in `categories`.
*This is an internal function*
Parameters
----------
values : list-like
Returns
-------
codes : ndarray
categories : Index
If `values` has a categorical dtype, then `categories` is
a CategoricalIndex keeping the categories and order of `values`.
"""
from pandas.core.indexes.category import CategoricalIndex
if not is_list_like(values):
raise TypeError("Input must be list-like")
if is_categorical(values):
if isinstance(values, (ABCCategoricalIndex, ABCSeries)):
values = values._values
categories = CategoricalIndex(values.categories, dtype=values.dtype)
codes = values.codes
else:
# The value of ordered is irrelevant since we don't use cat as such,
# but only the resulting categories, the order of which is independent
# from ordered. Set ordered to False as default. See GH #15457
cat = Categorical(values, ordered=False)
categories = cat.categories
codes = cat.codes
return codes, categories
|
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Factorize an input `values` into `categories` and `codes`. Preserves
categorical dtype in `categories`.
*This is an internal function*
Parameters
----------
values : list-like
Returns
-------
codes : ndarray
categories : Index
If `values` has a categorical dtype, then `categories` is
a CategoricalIndex keeping the categories and order of `values`.
|
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] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/arrays/categorical.py#L2635-L2670
|
train
|
Factorize an input values into categories and codes. Preserves categorical dtype in categories.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + chr(0b100110 + 0o111) + chr(0b110010) + chr(2316 - 2261) + chr(0b110000), 4690 - 4682), ehT0Px3KOsy9(chr(1914 - 1866) + chr(0b1101111) + chr(1760 - 1711) + '\065' + chr(0b110110), 49252 - 49244), ehT0Px3KOsy9('\x30' + chr(0b1101100 + 0o3) + chr(0b10 + 0o61) + '\x37' + chr(0b110111), 554 - 546), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110011) + '\x32' + '\x37', 7403 - 7395), ehT0Px3KOsy9('\060' + chr(0b1111 + 0o140) + chr(2201 - 2150) + chr(0b110001 + 0o2) + chr(0b110011), 44550 - 44542), ehT0Px3KOsy9(chr(48) + '\157' + '\061' + '\x35' + chr(2002 - 1953), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b100000 + 0o23) + chr(0b100000 + 0o20) + '\062', ord("\x08")), ehT0Px3KOsy9(chr(0b11000 + 0o30) + chr(0b1101111) + chr(0b0 + 0o66) + chr(50), 0b1000), ehT0Px3KOsy9(chr(0b1 + 0o57) + '\157' + '\x31' + chr(485 - 432) + chr(55), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(1417 - 1367) + '\067' + '\062', 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110101) + chr(0b110100), 65407 - 65399), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110011) + chr(50) + chr(0b101100 + 0o7), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b110100 + 0o73) + '\062' + '\x36', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\063' + chr(0b110011) + chr(0b1111 + 0o41), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + '\x37' + chr(0b10100 + 0o37), 32076 - 32068), ehT0Px3KOsy9(chr(1394 - 1346) + '\x6f' + chr(0b100 + 0o57) + '\061', 17447 - 17439), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\063' + chr(51) + chr(51), 8), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110010) + '\064' + chr(52), 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(2085 - 2035) + chr(2158 - 2109), 0o10), ehT0Px3KOsy9('\x30' + chr(8052 - 7941) + '\x32' + chr(52) + chr(50), 0o10), ehT0Px3KOsy9('\060' + chr(111) + '\x33' + '\060', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\062' + chr(52), 0b1000), ehT0Px3KOsy9('\060' + chr(1530 - 1419) + '\063' + '\x31' + '\062', 19822 - 19814), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x32' + chr(0b110101) + '\061', 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110010) + chr(0b110000) + '\x37', 0o10), ehT0Px3KOsy9('\060' + chr(0b1000 + 0o147) + chr(2113 - 2064) + chr(54) + chr(0b110101), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110010) + chr(0b10000 + 0o47), ord("\x08")), ehT0Px3KOsy9(chr(1225 - 1177) + '\x6f' + chr(1158 - 1109) + chr(51), 0o10), ehT0Px3KOsy9(chr(0b11 + 0o55) + chr(0b1011 + 0o144) + chr(1017 - 968) + chr(0b100111 + 0o20) + chr(52), 0o10), ehT0Px3KOsy9(chr(0b10010 + 0o36) + '\x6f' + chr(0b110011) + '\064' + chr(0b110011), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + '\x33' + '\060' + '\061', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b100101 + 0o14) + chr(0b10111 + 0o32) + chr(50), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + '\061' + chr(2140 - 2087), 0o10), ehT0Px3KOsy9(chr(0b1101 + 0o43) + '\157' + chr(0b110001) + chr(0b1111 + 0o45) + chr(0b110110), ord("\x08")), ehT0Px3KOsy9(chr(1686 - 1638) + '\157' + chr(0b110001) + chr(2621 - 2567) + chr(2243 - 2190), 8), ehT0Px3KOsy9('\060' + chr(448 - 337) + chr(1705 - 1654) + '\061' + '\x31', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110000), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b10000 + 0o43) + '\067' + chr(0b110111), 8), ehT0Px3KOsy9(chr(0b110000) + chr(3799 - 3688) + '\061' + chr(50), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + '\x33' + '\063' + chr(0b110001), 26708 - 26700)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b10111 + 0o36) + chr(0b110000), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x96'), '\144' + '\x65' + chr(0b111100 + 0o47) + chr(0b1101111) + chr(0b1010001 + 0o23) + chr(0b1001100 + 0o31))('\165' + chr(116) + chr(0b10010 + 0o124) + chr(0b101101) + chr(221 - 165)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def DLdThINXppxL(SPnCNu54H1db):
(YH_C7u76pUaX,) = (xafqLlk3kkUe(xafqLlk3kkUe(xafqLlk3kkUe(xafqLlk3kkUe(NPPHb59961Bv(xafqLlk3kkUe(SXOLrMavuUCe(b'\xc8\x0f\x91\xb3\xba\x1a\xecQ\x00\xc8I\xfd\x7f\xb6_|\xa3\xc1b\x8c{u\xbe\xcc\xe0\x1aer'), '\x64' + '\x65' + chr(0b1100011) + '\x6f' + '\x64' + chr(9079 - 8978))(chr(117) + '\164' + chr(6428 - 6326) + '\x2d' + chr(0b10011 + 0o45)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xfb\x0f\x8b\xb2\xbc\x06\xb0[\x0c\xdb@\x9ax\xbc^a'), chr(100) + '\145' + chr(99) + '\157' + '\x64' + chr(0b1010100 + 0o21))('\x75' + chr(0b1110100) + chr(0b1100110) + chr(45) + chr(1753 - 1697))), xafqLlk3kkUe(SXOLrMavuUCe(b'\xdb\x01\x8d\xb2'), chr(100) + '\x65' + chr(0b1100011) + chr(111) + chr(0b1100100) + '\x65')('\165' + '\x74' + chr(0b1100110) + chr(0b11100 + 0o21) + '\070')), xafqLlk3kkUe(SXOLrMavuUCe(b'\xd1\x00\x9b\xb2\xa3\x0c\xb1'), '\x64' + chr(0b1100101) + chr(2154 - 2055) + chr(10936 - 10825) + chr(100) + chr(0b110010 + 0o63))(chr(12603 - 12486) + chr(3137 - 3021) + chr(102) + chr(0b101101) + chr(0b111000))), xafqLlk3kkUe(SXOLrMavuUCe(b'\xdb\x0f\x8b\xb2\xbc\x06\xb0K'), chr(0b1100100) + chr(0b1100101) + chr(0b1100011) + '\157' + chr(0b11 + 0o141) + '\x65')('\x75' + '\164' + chr(0b1100010 + 0o4) + chr(1293 - 1248) + chr(914 - 858))), xafqLlk3kkUe(SXOLrMavuUCe(b'\xfb\x0f\x8b\xb2\xbc\x06\xb0[\x0c\xdb@\x9ax\xbc^a'), '\144' + chr(101) + chr(99) + chr(0b1101111) + chr(263 - 163) + chr(8918 - 8817))(chr(0b101 + 0o160) + '\x74' + chr(830 - 728) + chr(0b101101) + '\x38')),)
if not bAgBF7jXI53B(SPnCNu54H1db):
raise sznFqDbNBHlx(xafqLlk3kkUe(SXOLrMavuUCe(b'\xf1\x00\x8f\xa2\xafI\xafG\x1c\xce\x0c\xb1s\xf8Wp\xa8\xd0<\xceq\x7f\xaf'), '\144' + chr(4465 - 4364) + '\143' + chr(0b111000 + 0o67) + '\144' + '\x65')(chr(117) + chr(11841 - 11725) + '\146' + '\x2d' + chr(0b101001 + 0o17)))
if OywpAkUqi4xT(SPnCNu54H1db):
if PlSM16l2KDPD(SPnCNu54H1db, (Ou_oEUbhlMXT, essMXh4s9f1w)):
SPnCNu54H1db = SPnCNu54H1db._values
mZZDAT49UzAb = YH_C7u76pUaX(SPnCNu54H1db.categories, dtype=SPnCNu54H1db.dtype)
AoWJEgIAbHh_ = SPnCNu54H1db.codes
else:
re0VVGAVKu27 = XxOW0_jwnido(SPnCNu54H1db, ordered=ehT0Px3KOsy9(chr(0b110000) + chr(9902 - 9791) + '\x30', 8))
mZZDAT49UzAb = re0VVGAVKu27.categories
AoWJEgIAbHh_ = re0VVGAVKu27.codes
return (AoWJEgIAbHh_, mZZDAT49UzAb)
|
pandas-dev/pandas
|
pandas/core/arrays/categorical.py
|
_factorize_from_iterables
|
def _factorize_from_iterables(iterables):
"""
A higher-level wrapper over `_factorize_from_iterable`.
*This is an internal function*
Parameters
----------
iterables : list-like of list-likes
Returns
-------
codes_list : list of ndarrays
categories_list : list of Indexes
Notes
-----
See `_factorize_from_iterable` for more info.
"""
if len(iterables) == 0:
# For consistency, it should return a list of 2 lists.
return [[], []]
return map(list, lzip(*[_factorize_from_iterable(it) for it in iterables]))
|
python
|
def _factorize_from_iterables(iterables):
"""
A higher-level wrapper over `_factorize_from_iterable`.
*This is an internal function*
Parameters
----------
iterables : list-like of list-likes
Returns
-------
codes_list : list of ndarrays
categories_list : list of Indexes
Notes
-----
See `_factorize_from_iterable` for more info.
"""
if len(iterables) == 0:
# For consistency, it should return a list of 2 lists.
return [[], []]
return map(list, lzip(*[_factorize_from_iterable(it) for it in iterables]))
|
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"# For consistency, it should return a list of 2 lists.",
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] |
A higher-level wrapper over `_factorize_from_iterable`.
*This is an internal function*
Parameters
----------
iterables : list-like of list-likes
Returns
-------
codes_list : list of ndarrays
categories_list : list of Indexes
Notes
-----
See `_factorize_from_iterable` for more info.
|
[
"A",
"higher",
"-",
"level",
"wrapper",
"over",
"_factorize_from_iterable",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/arrays/categorical.py#L2673-L2695
|
train
|
A higher - level wrapper over _factorize_from_iterable.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(9232 - 9121) + chr(0b0 + 0o65) + '\x37', 0b1000), ehT0Px3KOsy9(chr(1465 - 1417) + chr(0b1001001 + 0o46) + '\061' + '\067' + '\x36', 27178 - 27170), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\062' + chr(0b110111) + '\x36', 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110010) + '\x36' + chr(1509 - 1461), ord("\x08")), ehT0Px3KOsy9(chr(504 - 456) + chr(111) + chr(693 - 644) + chr(54) + chr(0b10100 + 0o40), ord("\x08")), ehT0Px3KOsy9(chr(0b101000 + 0o10) + '\x6f' + '\062' + chr(0b110101), 0b1000), ehT0Px3KOsy9(chr(0b110000 + 0o0) + '\x6f' + chr(0b110000), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x33' + chr(0b110011) + chr(50), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(1963 - 1912) + '\067' + '\064', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(251 - 202) + chr(53) + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(0b100111 + 0o11) + chr(11786 - 11675) + chr(0b110010) + '\x35' + chr(0b110001), 65141 - 65133), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110010) + chr(1392 - 1339) + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(1115 - 1067) + chr(3639 - 3528) + '\061' + chr(0b110001) + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(5120 - 5009) + chr(0b110011) + '\x30' + chr(0b110110), 0b1000), ehT0Px3KOsy9(chr(0b11010 + 0o26) + '\x6f' + '\x32' + chr(2703 - 2650) + chr(0b0 + 0o62), 49365 - 49357), ehT0Px3KOsy9(chr(0b110000) + chr(0b101001 + 0o106) + '\062' + chr(1209 - 1155) + chr(0b110001), 33622 - 33614), ehT0Px3KOsy9(chr(0b10101 + 0o33) + chr(111) + '\x33' + chr(2106 - 2054) + '\064', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(1347 - 1296) + '\x33' + '\x33', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\062' + chr(48), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(55) + chr(0b100001 + 0o20), 0o10), ehT0Px3KOsy9(chr(1206 - 1158) + '\157' + chr(0b110001) + chr(0b11001 + 0o27), 46163 - 46155), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\061' + '\067' + chr(0b110110), 8), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(50) + '\x32' + '\x33', ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(49) + chr(48) + '\x30', 52551 - 52543), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\063' + chr(0b110111) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(2213 - 2165) + chr(0b1101111) + chr(0b110011) + chr(2329 - 2279), 20391 - 20383), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x33' + chr(49) + '\x32', 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(968 - 918) + chr(0b10 + 0o63) + '\x33', 8), ehT0Px3KOsy9('\060' + chr(875 - 764) + '\x33' + chr(52) + chr(0b1011 + 0o51), 8), ehT0Px3KOsy9('\x30' + chr(0b1010111 + 0o30) + chr(0b1111 + 0o44) + chr(0b11011 + 0o30) + chr(54), 24155 - 24147), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\062' + '\x34' + '\065', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(53) + chr(53), 0b1000), ehT0Px3KOsy9(chr(1786 - 1738) + chr(0b1101111) + chr(0b11 + 0o56) + chr(0b110010) + '\066', 46210 - 46202), ehT0Px3KOsy9('\060' + chr(111) + chr(50) + chr(0b110010) + chr(0b100010 + 0o25), 6856 - 6848), ehT0Px3KOsy9('\x30' + chr(0b1001000 + 0o47) + '\063' + chr(0b101 + 0o53) + chr(1963 - 1915), 0b1000), ehT0Px3KOsy9(chr(0b100010 + 0o16) + '\x6f' + chr(0b110010) + '\061' + '\061', 0o10), ehT0Px3KOsy9(chr(48) + chr(381 - 270) + chr(0b110001) + '\x35' + chr(0b110100 + 0o1), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(4904 - 4793) + chr(54) + chr(1361 - 1311), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(12005 - 11894) + chr(52) + '\060', 36131 - 36123), ehT0Px3KOsy9('\060' + chr(0b110010 + 0o75) + chr(2042 - 1993) + chr(0b110010) + '\x30', 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110101) + '\x30', 309 - 301)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x01'), chr(0b1000100 + 0o40) + '\145' + chr(0b110000 + 0o63) + chr(111) + chr(100) + chr(101))(chr(0b1110101) + chr(5463 - 5347) + chr(0b1100110) + chr(45) + chr(1198 - 1142)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def E2pgwRlvMYwD(Ymkm2d6mcyoO):
if c2A0yzQpDQB3(Ymkm2d6mcyoO) == ehT0Px3KOsy9('\060' + '\x6f' + '\060', 8):
return [[], []]
return abA97kOQKaLo(YyaZ4tpXu4lf, d_hwvqxFHyy9(*[DLdThINXppxL(SdOiQfoVLiMl) for SdOiQfoVLiMl in Ymkm2d6mcyoO]))
|
pandas-dev/pandas
|
pandas/core/arrays/categorical.py
|
Categorical.copy
|
def copy(self):
"""
Copy constructor.
"""
return self._constructor(values=self._codes.copy(),
dtype=self.dtype,
fastpath=True)
|
python
|
def copy(self):
"""
Copy constructor.
"""
return self._constructor(values=self._codes.copy(),
dtype=self.dtype,
fastpath=True)
|
[
"def",
"copy",
"(",
"self",
")",
":",
"return",
"self",
".",
"_constructor",
"(",
"values",
"=",
"self",
".",
"_codes",
".",
"copy",
"(",
")",
",",
"dtype",
"=",
"self",
".",
"dtype",
",",
"fastpath",
"=",
"True",
")"
] |
Copy constructor.
|
[
"Copy",
"constructor",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/arrays/categorical.py#L455-L461
|
train
|
Copy the object.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + chr(848 - 737) + chr(0b11010 + 0o30) + chr(1957 - 1908) + '\065', 0o10), ehT0Px3KOsy9('\060' + chr(0b11110 + 0o121) + '\x31' + chr(0b110010) + '\062', 0b1000), ehT0Px3KOsy9(chr(0b10100 + 0o34) + chr(0b1101111) + '\063' + chr(53) + chr(50), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x31' + chr(2495 - 2444) + chr(0b110001), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(377 - 328) + chr(549 - 496) + '\x36', 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110011) + '\x36', 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b11 + 0o57) + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(0b111 + 0o51) + '\157' + '\x31' + '\062', 47838 - 47830), ehT0Px3KOsy9('\x30' + chr(0b110001 + 0o76) + chr(55) + chr(1965 - 1915), ord("\x08")), ehT0Px3KOsy9(chr(0b100001 + 0o17) + chr(111) + chr(0b101 + 0o56) + chr(357 - 302) + chr(1088 - 1034), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b11010 + 0o31) + chr(54) + chr(879 - 830), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(1333 - 1282) + chr(0b10 + 0o56) + '\060', 0b1000), ehT0Px3KOsy9(chr(1898 - 1850) + chr(8772 - 8661) + '\x37' + chr(48), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1010001 + 0o36) + chr(0b110010) + chr(0b110100) + chr(217 - 165), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(2711 - 2600) + '\x31' + chr(50) + chr(0b110001 + 0o6), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110001) + '\066' + '\x34', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x33' + '\x33' + '\060', 0o10), ehT0Px3KOsy9(chr(0b100100 + 0o14) + chr(0b1100100 + 0o13) + chr(0b110001) + '\x33' + chr(48), ord("\x08")), ehT0Px3KOsy9(chr(677 - 629) + '\157' + '\063' + chr(1274 - 1224), 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110011) + chr(0b110001) + '\067', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\063' + chr(50 - 0), 8), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110001) + chr(53) + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\061' + '\x31' + '\062', 0o10), ehT0Px3KOsy9(chr(48) + '\157' + '\061' + '\064' + chr(1951 - 1901), 0b1000), ehT0Px3KOsy9(chr(0b101110 + 0o2) + '\157' + chr(0b101001 + 0o10) + chr(0b111 + 0o54) + '\060', 8), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b1000 + 0o53) + chr(757 - 709) + '\060', 8), ehT0Px3KOsy9('\x30' + '\157' + chr(0b100011 + 0o20) + chr(0b101110 + 0o10), 8), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x33' + chr(0b11110 + 0o30) + chr(683 - 629), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\062' + '\x33' + chr(0b110000), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\062' + chr(1688 - 1637) + chr(217 - 162), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(11388 - 11277) + chr(1799 - 1748) + chr(267 - 212) + chr(425 - 374), 0o10), ehT0Px3KOsy9(chr(1526 - 1478) + '\157' + '\061' + chr(0b110011) + '\066', 0b1000), ehT0Px3KOsy9(chr(48) + chr(4993 - 4882) + chr(0b110001) + chr(2201 - 2148) + '\060', 8), ehT0Px3KOsy9(chr(954 - 906) + '\x6f' + chr(0b11010 + 0o30) + '\065' + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(2151 - 2103) + chr(8874 - 8763) + '\063' + '\067' + chr(54), 8), ehT0Px3KOsy9(chr(1040 - 992) + chr(0b1101111) + chr(0b110010) + chr(1617 - 1569), 8), ehT0Px3KOsy9(chr(48) + chr(1966 - 1855) + chr(0b110001) + chr(0b110000) + chr(50), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b11011 + 0o124) + chr(0b110001) + '\065' + chr(2382 - 2330), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + '\063' + chr(817 - 763) + chr(50), 62995 - 62987), ehT0Px3KOsy9(chr(0b110000) + chr(11023 - 10912) + '\x32' + chr(51), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + chr(1934 - 1823) + chr(0b11111 + 0o26) + chr(48), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xa3'), chr(6785 - 6685) + chr(0b101101 + 0o70) + chr(0b1100011) + chr(0b1001110 + 0o41) + chr(0b100010 + 0o102) + chr(8437 - 8336))(chr(0b1110101) + chr(116) + chr(0b10010 + 0o124) + '\055' + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def igThHS4jwVsa(oVre8I6UXc3b):
return xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\xd21\x857\x1djb\x7fY\x8a\x9e\xb2'), chr(0b1111 + 0o125) + '\145' + chr(99) + '\x6f' + chr(3327 - 3227) + chr(101))(chr(117) + '\x74' + chr(3645 - 3543) + chr(0b101101) + chr(0b111000)))(values=xafqLlk3kkUe(oVre8I6UXc3b._codes, xafqLlk3kkUe(SXOLrMavuUCe(b'\xe45\xbe1&M$`M\xa8\x82\xa1'), chr(921 - 821) + '\145' + chr(8217 - 8118) + chr(0b1101111) + '\x64' + chr(0b110010 + 0o63))('\x75' + chr(116) + chr(0b10100 + 0o122) + '\x2d' + '\x38'))(), dtype=xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\xe9&\x93)\x0b'), chr(6500 - 6400) + '\145' + '\x63' + chr(0b1101111) + '\144' + chr(0b1100101))(chr(6886 - 6769) + '\x74' + '\x66' + chr(0b100110 + 0o7) + '\x38')), fastpath=ehT0Px3KOsy9(chr(0b1100 + 0o44) + '\x6f' + chr(0b11000 + 0o31), ord("\x08")))
|
pandas-dev/pandas
|
pandas/core/arrays/categorical.py
|
Categorical.astype
|
def astype(self, dtype, copy=True):
"""
Coerce this type to another dtype
Parameters
----------
dtype : numpy dtype or pandas type
copy : bool, default True
By default, astype always returns a newly allocated object.
If copy is set to False and dtype is categorical, the original
object is returned.
.. versionadded:: 0.19.0
"""
if is_categorical_dtype(dtype):
# GH 10696/18593
dtype = self.dtype.update_dtype(dtype)
self = self.copy() if copy else self
if dtype == self.dtype:
return self
return self._set_dtype(dtype)
return np.array(self, dtype=dtype, copy=copy)
|
python
|
def astype(self, dtype, copy=True):
"""
Coerce this type to another dtype
Parameters
----------
dtype : numpy dtype or pandas type
copy : bool, default True
By default, astype always returns a newly allocated object.
If copy is set to False and dtype is categorical, the original
object is returned.
.. versionadded:: 0.19.0
"""
if is_categorical_dtype(dtype):
# GH 10696/18593
dtype = self.dtype.update_dtype(dtype)
self = self.copy() if copy else self
if dtype == self.dtype:
return self
return self._set_dtype(dtype)
return np.array(self, dtype=dtype, copy=copy)
|
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",",
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"=",
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"update_dtype",
"(",
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"self",
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"(",
")",
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"(",
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",",
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",",
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")"
] |
Coerce this type to another dtype
Parameters
----------
dtype : numpy dtype or pandas type
copy : bool, default True
By default, astype always returns a newly allocated object.
If copy is set to False and dtype is categorical, the original
object is returned.
.. versionadded:: 0.19.0
|
[
"Coerce",
"this",
"type",
"to",
"another",
"dtype"
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/arrays/categorical.py#L463-L485
|
train
|
Coerce this type to another dtype.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\x30' + '\157' + chr(633 - 585), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(51) + chr(312 - 264) + '\060', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(50) + chr(1489 - 1434) + '\062', 35892 - 35884), ehT0Px3KOsy9(chr(248 - 200) + chr(0b1010111 + 0o30) + '\066' + '\063', 4968 - 4960), ehT0Px3KOsy9(chr(48) + chr(111) + chr(50) + chr(0b100011 + 0o20) + chr(54), 0b1000), ehT0Px3KOsy9(chr(1521 - 1473) + chr(0b1101111) + '\063' + chr(1486 - 1438) + chr(49), 0o10), ehT0Px3KOsy9('\060' + chr(3640 - 3529) + chr(0b10111 + 0o33) + '\x37' + '\062', 8), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\063' + '\060' + '\063', ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(1327 - 1277) + chr(49) + chr(0b10000 + 0o43), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b110001 + 0o76) + chr(49) + '\063' + chr(49), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(1916 - 1866) + chr(2281 - 2230) + chr(55), 0o10), ehT0Px3KOsy9(chr(0b11 + 0o55) + chr(0b1101111) + '\064' + '\060', 0o10), ehT0Px3KOsy9('\060' + chr(7105 - 6994) + chr(2194 - 2144) + chr(1375 - 1324), 44801 - 44793), ehT0Px3KOsy9('\x30' + '\157' + '\061' + chr(0b1101 + 0o45) + '\065', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(49) + chr(0b110000 + 0o4) + chr(53), 58835 - 58827), ehT0Px3KOsy9(chr(0b11000 + 0o30) + chr(3070 - 2959) + chr(0b110101) + chr(647 - 596), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(2869 - 2758) + '\x33' + chr(0b110010) + chr(0b100 + 0o54), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110111), 46882 - 46874), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(50) + chr(48) + chr(48), 0o10), ehT0Px3KOsy9('\x30' + '\157' + '\061' + '\x35' + '\x36', 41536 - 41528), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(50) + chr(0b11010 + 0o26) + '\x30', 8), ehT0Px3KOsy9(chr(48) + '\157' + '\x32' + chr(50) + chr(53), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110001) + chr(50) + '\x31', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110001) + '\063' + chr(2382 - 2330), 0b1000), ehT0Px3KOsy9('\060' + chr(3930 - 3819) + chr(51) + chr(1509 - 1460) + chr(0b100010 + 0o16), 0b1000), ehT0Px3KOsy9(chr(137 - 89) + chr(9983 - 9872) + chr(917 - 868) + '\063' + '\x30', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x33' + '\066' + chr(0b110000 + 0o7), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b11100 + 0o27) + chr(53) + '\x30', 4889 - 4881), ehT0Px3KOsy9('\x30' + chr(0b100001 + 0o116) + chr(1863 - 1812) + chr(48) + chr(2139 - 2089), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + '\061' + chr(48) + '\062', 0o10), ehT0Px3KOsy9(chr(734 - 686) + chr(0b0 + 0o157) + '\061' + chr(0b110000) + chr(53), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\061' + chr(0b100100 + 0o20) + chr(48), 0b1000), ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(7786 - 7675) + chr(0b110001) + chr(262 - 212) + chr(0b110111), 12060 - 12052), ehT0Px3KOsy9('\x30' + chr(136 - 25) + '\061' + '\065' + '\066', 8), ehT0Px3KOsy9(chr(0b10010 + 0o36) + '\x6f' + chr(0b110100) + chr(0b11110 + 0o26), 29592 - 29584), ehT0Px3KOsy9('\x30' + chr(11542 - 11431) + chr(51) + '\x33' + chr(53), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b100000 + 0o117) + '\062' + chr(0b110100) + '\x32', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1000000 + 0o57) + chr(0b101101 + 0o6), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110010) + '\x34' + chr(50), 8), ehT0Px3KOsy9(chr(0b10100 + 0o34) + chr(111) + chr(1033 - 983) + '\067' + chr(0b10111 + 0o31), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b11 + 0o62) + chr(48), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'.'), chr(0b1100100) + chr(0b1010001 + 0o24) + '\x63' + chr(111) + '\144' + chr(0b1010 + 0o133))('\165' + '\x74' + chr(0b1011111 + 0o7) + chr(45) + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def XF6WakKHWOo5(oVre8I6UXc3b, jSV9IKnemH7K, igThHS4jwVsa=ehT0Px3KOsy9(chr(0b110000) + chr(7331 - 7220) + chr(0b110000 + 0o1), 11839 - 11831)):
if P9dMe_tcBUdc(jSV9IKnemH7K):
jSV9IKnemH7K = oVre8I6UXc3b.dtype.update_dtype(jSV9IKnemH7K)
oVre8I6UXc3b = oVre8I6UXc3b.igThHS4jwVsa() if igThHS4jwVsa else oVre8I6UXc3b
if jSV9IKnemH7K == xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'd\xb4\xc3C\xfb'), '\144' + chr(101) + chr(0b1100011) + '\x6f' + chr(0b101011 + 0o71) + chr(0b1100101))(chr(117) + chr(5315 - 5199) + '\x66' + chr(0b10100 + 0o31) + '\070')):
return oVre8I6UXc3b
return xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'_\xb3\xdfG\xc1\xa5\xce\xba\xfb<'), chr(100) + chr(101) + chr(99) + chr(6266 - 6155) + chr(0b1100100) + chr(3848 - 3747))('\165' + chr(0b111010 + 0o72) + '\146' + '\055' + chr(0b111000)))(jSV9IKnemH7K)
return xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'a\xb2\xc8R\xe7'), '\x64' + '\x65' + '\143' + '\157' + chr(100) + chr(101))(chr(4309 - 4192) + chr(0b1000110 + 0o56) + chr(102) + chr(1842 - 1797) + '\070'))(oVre8I6UXc3b, dtype=jSV9IKnemH7K, copy=igThHS4jwVsa)
|
pandas-dev/pandas
|
pandas/core/arrays/categorical.py
|
Categorical._from_inferred_categories
|
def _from_inferred_categories(cls, inferred_categories, inferred_codes,
dtype, true_values=None):
"""
Construct a Categorical from inferred values.
For inferred categories (`dtype` is None) the categories are sorted.
For explicit `dtype`, the `inferred_categories` are cast to the
appropriate type.
Parameters
----------
inferred_categories : Index
inferred_codes : Index
dtype : CategoricalDtype or 'category'
true_values : list, optional
If none are provided, the default ones are
"True", "TRUE", and "true."
Returns
-------
Categorical
"""
from pandas import Index, to_numeric, to_datetime, to_timedelta
cats = Index(inferred_categories)
known_categories = (isinstance(dtype, CategoricalDtype) and
dtype.categories is not None)
if known_categories:
# Convert to a specialized type with `dtype` if specified.
if dtype.categories.is_numeric():
cats = to_numeric(inferred_categories, errors="coerce")
elif is_datetime64_dtype(dtype.categories):
cats = to_datetime(inferred_categories, errors="coerce")
elif is_timedelta64_dtype(dtype.categories):
cats = to_timedelta(inferred_categories, errors="coerce")
elif dtype.categories.is_boolean():
if true_values is None:
true_values = ["True", "TRUE", "true"]
cats = cats.isin(true_values)
if known_categories:
# Recode from observation order to dtype.categories order.
categories = dtype.categories
codes = _recode_for_categories(inferred_codes, cats, categories)
elif not cats.is_monotonic_increasing:
# Sort categories and recode for unknown categories.
unsorted = cats.copy()
categories = cats.sort_values()
codes = _recode_for_categories(inferred_codes, unsorted,
categories)
dtype = CategoricalDtype(categories, ordered=False)
else:
dtype = CategoricalDtype(cats, ordered=False)
codes = inferred_codes
return cls(codes, dtype=dtype, fastpath=True)
|
python
|
def _from_inferred_categories(cls, inferred_categories, inferred_codes,
dtype, true_values=None):
"""
Construct a Categorical from inferred values.
For inferred categories (`dtype` is None) the categories are sorted.
For explicit `dtype`, the `inferred_categories` are cast to the
appropriate type.
Parameters
----------
inferred_categories : Index
inferred_codes : Index
dtype : CategoricalDtype or 'category'
true_values : list, optional
If none are provided, the default ones are
"True", "TRUE", and "true."
Returns
-------
Categorical
"""
from pandas import Index, to_numeric, to_datetime, to_timedelta
cats = Index(inferred_categories)
known_categories = (isinstance(dtype, CategoricalDtype) and
dtype.categories is not None)
if known_categories:
# Convert to a specialized type with `dtype` if specified.
if dtype.categories.is_numeric():
cats = to_numeric(inferred_categories, errors="coerce")
elif is_datetime64_dtype(dtype.categories):
cats = to_datetime(inferred_categories, errors="coerce")
elif is_timedelta64_dtype(dtype.categories):
cats = to_timedelta(inferred_categories, errors="coerce")
elif dtype.categories.is_boolean():
if true_values is None:
true_values = ["True", "TRUE", "true"]
cats = cats.isin(true_values)
if known_categories:
# Recode from observation order to dtype.categories order.
categories = dtype.categories
codes = _recode_for_categories(inferred_codes, cats, categories)
elif not cats.is_monotonic_increasing:
# Sort categories and recode for unknown categories.
unsorted = cats.copy()
categories = cats.sort_values()
codes = _recode_for_categories(inferred_codes, unsorted,
categories)
dtype = CategoricalDtype(categories, ordered=False)
else:
dtype = CategoricalDtype(cats, ordered=False)
codes = inferred_codes
return cls(codes, dtype=dtype, fastpath=True)
|
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Construct a Categorical from inferred values.
For inferred categories (`dtype` is None) the categories are sorted.
For explicit `dtype`, the `inferred_categories` are cast to the
appropriate type.
Parameters
----------
inferred_categories : Index
inferred_codes : Index
dtype : CategoricalDtype or 'category'
true_values : list, optional
If none are provided, the default ones are
"True", "TRUE", and "true."
Returns
-------
Categorical
|
[
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] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/arrays/categorical.py#L528-L586
|
train
|
Construct a Categorical from inferred values.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(1900 - 1852) + chr(111) + chr(0b101010 + 0o10) + '\x35' + '\x32', 55123 - 55115), ehT0Px3KOsy9('\060' + chr(5599 - 5488) + chr(0b1110 + 0o44) + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1010011 + 0o34) + '\x33' + '\x31' + '\064', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b100111 + 0o110) + chr(0b110011) + chr(0b100011 + 0o23) + '\x36', 0o10), ehT0Px3KOsy9(chr(1994 - 1946) + '\157' + '\061' + chr(0b1011 + 0o46) + '\067', 0o10), ehT0Px3KOsy9(chr(2275 - 2227) + chr(111) + '\x32' + '\066' + chr(714 - 666), 56336 - 56328), ehT0Px3KOsy9('\x30' + chr(0b1010011 + 0o34) + '\x32' + chr(1939 - 1884) + chr(338 - 284), 11380 - 11372), ehT0Px3KOsy9(chr(48) + chr(0b101000 + 0o107) + '\061' + chr(542 - 489) + '\x36', 0o10), ehT0Px3KOsy9('\x30' + chr(7080 - 6969) + chr(2591 - 2537) + '\064', 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\062' + chr(54) + chr(0b100100 + 0o22), 0o10), ehT0Px3KOsy9(chr(818 - 770) + '\x6f' + chr(0b100110 + 0o20) + chr(0b100000 + 0o24), 8), ehT0Px3KOsy9(chr(1388 - 1340) + '\157' + chr(0b110010) + chr(0b110001) + chr(51), ord("\x08")), ehT0Px3KOsy9(chr(981 - 933) + chr(0b101110 + 0o101) + '\062' + '\060' + chr(0b110110), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(3445 - 3334) + chr(0b110010) + chr(48) + chr(50), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\061' + chr(2456 - 2402) + chr(0b110011), ord("\x08")), ehT0Px3KOsy9(chr(863 - 815) + '\x6f' + chr(2350 - 2299) + chr(710 - 658) + '\x37', 0o10), ehT0Px3KOsy9(chr(930 - 882) + chr(111) + '\062' + chr(1221 - 1171) + '\x37', 39999 - 39991), ehT0Px3KOsy9(chr(0b110 + 0o52) + chr(0b1101111) + chr(0b110011) + chr(50) + '\067', ord("\x08")), ehT0Px3KOsy9(chr(538 - 490) + chr(0b1100101 + 0o12) + chr(0b1000 + 0o51) + '\062' + '\x30', 38751 - 38743), ehT0Px3KOsy9(chr(0b100011 + 0o15) + chr(12034 - 11923) + '\062' + chr(52) + chr(2209 - 2158), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + '\x33' + '\x32', 34171 - 34163), ehT0Px3KOsy9(chr(857 - 809) + chr(148 - 37) + chr(50) + '\x32' + chr(0b11010 + 0o34), 20059 - 20051), ehT0Px3KOsy9(chr(0b10010 + 0o36) + chr(0b1101111) + chr(49) + '\065' + chr(0b110100), 24338 - 24330), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110011) + chr(0b100101 + 0o17) + '\x35', 42135 - 42127), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b0 + 0o63) + chr(665 - 614) + chr(0b11001 + 0o36), ord("\x08")), ehT0Px3KOsy9('\060' + chr(10385 - 10274) + '\x31' + '\x33' + chr(824 - 774), 0b1000), ehT0Px3KOsy9('\060' + chr(11283 - 11172) + '\062' + chr(55) + chr(0b110011), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\062' + chr(51) + chr(2915 - 2860), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b111 + 0o57) + chr(0b110110), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x33' + '\063' + chr(0b101110 + 0o2), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b100011 + 0o114) + '\x34' + '\x30', 4301 - 4293), ehT0Px3KOsy9('\060' + '\x6f' + '\x31', 45986 - 45978), ehT0Px3KOsy9(chr(1111 - 1063) + '\157' + chr(0b110001) + '\x33', 0b1000), ehT0Px3KOsy9(chr(0b100011 + 0o15) + '\157' + '\x32' + chr(175 - 125) + chr(0b110110), 8), ehT0Px3KOsy9(chr(0b1 + 0o57) + '\x6f' + chr(0b1001 + 0o50) + chr(53) + '\x36', 8), ehT0Px3KOsy9(chr(48) + chr(6237 - 6126) + chr(49) + '\x34' + chr(52), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1001101 + 0o42) + chr(0b110010) + chr(0b110101) + chr(52), 0b1000), ehT0Px3KOsy9(chr(0b101111 + 0o1) + chr(0b1101111) + '\x32' + '\x37' + chr(0b1101 + 0o45), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(9129 - 9018) + chr(53) + '\061', 0o10), ehT0Px3KOsy9(chr(491 - 443) + chr(111) + chr(0b10100 + 0o37) + chr(0b11100 + 0o24) + '\x33', 28202 - 28194)][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + chr(0b1000001 + 0o56) + chr(0b100110 + 0o17) + chr(1571 - 1523), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x84'), chr(0b1011001 + 0o13) + '\145' + '\x63' + '\157' + chr(100) + chr(4134 - 4033))(chr(0b1110101) + '\164' + chr(0b1100110) + chr(0b101101) + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def ydSewXnOdd9k(NSstowUUZlxS, kSTOB7MpzlDk, aKSlaOrC7I1g, jSV9IKnemH7K, t6baE7EFJavV=None):
(EJkE1Nx1bysb, D3UiWg6YVSO0, IF08dLE993_s, o52vswvoQUMc) = (xafqLlk3kkUe(NPPHb59961Bv(xafqLlk3kkUe(SXOLrMavuUCe(b'\xdaw\xa2\x92.\xc3'), chr(0b1000 + 0o134) + '\x65' + chr(99) + chr(0b1101111) + '\144' + chr(10040 - 9939))(chr(0b1110101) + chr(2303 - 2187) + '\146' + chr(1045 - 1000) + chr(0b111000)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xe3x\xa8\x937'), chr(0b110101 + 0o57) + chr(101) + chr(0b111110 + 0o45) + chr(0b1011100 + 0o23) + '\x64' + chr(5865 - 5764))(chr(0b1110101) + '\164' + '\x66' + '\x2d' + chr(0b111000))), xafqLlk3kkUe(SXOLrMavuUCe(b'\xe3x\xa8\x937'), chr(0b1010111 + 0o15) + chr(101) + chr(0b110011 + 0o60) + chr(111) + chr(0b1011001 + 0o13) + '\x65')('\x75' + '\x74' + chr(0b1100110) + '\055' + chr(0b111000))), xafqLlk3kkUe(NPPHb59961Bv(xafqLlk3kkUe(SXOLrMavuUCe(b'\xdaw\xa2\x92.\xc3'), chr(100) + chr(0b1110 + 0o127) + chr(0b1100011) + chr(111) + '\x64' + '\x65')(chr(117) + '\164' + chr(0b1100110) + chr(45) + chr(56)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xdey\x93\x98:\xdd\xdb\x1c]\xd5'), '\x64' + '\145' + chr(0b1 + 0o142) + '\x6f' + '\x64' + chr(0b100011 + 0o102))(chr(0b1110101) + '\x74' + chr(1192 - 1090) + '\x2d' + chr(0b110 + 0o62))), xafqLlk3kkUe(SXOLrMavuUCe(b'\xdey\x93\x98:\xdd\xdb\x1c]\xd5'), chr(2522 - 2422) + '\145' + chr(0b1100011) + chr(5311 - 5200) + '\x64' + chr(9304 - 9203))(chr(0b1110101) + chr(0b1110100) + '\x66' + chr(0b101101) + chr(0b111000))), xafqLlk3kkUe(NPPHb59961Bv(xafqLlk3kkUe(SXOLrMavuUCe(b'\xdaw\xa2\x92.\xc3'), '\144' + chr(0b1100101) + chr(0b100 + 0o137) + chr(0b10111 + 0o130) + chr(100) + chr(0b1100101))(chr(117) + chr(0b1001000 + 0o54) + '\146' + chr(0b10101 + 0o30) + chr(282 - 226)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xdey\x93\x92.\xc4\xdb\x1a]\xdbQ'), chr(100) + chr(0b1100101) + chr(1102 - 1003) + '\157' + '\144' + chr(0b1100101))('\x75' + '\x74' + chr(0b1000001 + 0o45) + chr(0b101101) + chr(0b111000))), xafqLlk3kkUe(SXOLrMavuUCe(b'\xdey\x93\x92.\xc4\xdb\x1a]\xdbQ'), '\x64' + '\145' + chr(99) + '\157' + '\144' + chr(0b1100101))('\x75' + chr(0b1110100) + '\146' + chr(0b101101) + '\070')), xafqLlk3kkUe(NPPHb59961Bv(xafqLlk3kkUe(SXOLrMavuUCe(b'\xdaw\xa2\x92.\xc3'), chr(0b1100100) + chr(0b1 + 0o144) + chr(0b1100011) + chr(0b1101111) + chr(0b1000011 + 0o41) + chr(1096 - 995))(chr(5007 - 4890) + chr(0b1011000 + 0o34) + chr(0b1100110) + '\x2d' + chr(56)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xdey\x93\x82&\xdd\xdb\nQ\xda@\xea'), '\144' + chr(101) + chr(0b1100011) + chr(0b1101111) + '\x64' + '\145')('\x75' + chr(1281 - 1165) + chr(0b1100110) + chr(45) + '\x38')), xafqLlk3kkUe(SXOLrMavuUCe(b'\xdey\x93\x82&\xdd\xdb\nQ\xda@\xea'), '\x64' + chr(0b1001001 + 0o34) + chr(0b1100011) + chr(111) + '\x64' + chr(296 - 195))('\x75' + chr(116) + '\x66' + '\x2d' + chr(0b1001 + 0o57))))
_IZEDmb5AMbL = EJkE1Nx1bysb(kSTOB7MpzlDk)
fsMVcjitw7pK = PlSM16l2KDPD(jSV9IKnemH7K, CBSVoRj_kvTn) and jSV9IKnemH7K.categories is not None
if fsMVcjitw7pK:
if xafqLlk3kkUe(jSV9IKnemH7K.categories, xafqLlk3kkUe(SXOLrMavuUCe(b'\xc3e\x93\x98:\xdd\xdb\x1c]\xd5'), chr(100) + chr(5517 - 5416) + chr(0b1100011) + chr(0b1101111) + chr(0b1100100) + chr(0b1100101))(chr(6525 - 6408) + '\164' + chr(0b1100110) + chr(0b10000 + 0o35) + '\x38'))():
_IZEDmb5AMbL = D3UiWg6YVSO0(kSTOB7MpzlDk, errors=xafqLlk3kkUe(SXOLrMavuUCe(b'\xc9y\xa9\x84,\xd5'), chr(0b1100100) + '\145' + chr(9593 - 9494) + '\x6f' + chr(6878 - 6778) + chr(0b1100101))(chr(11164 - 11047) + '\164' + chr(0b1001001 + 0o35) + chr(185 - 140) + chr(56)))
elif o97MkxKQGNoK(xafqLlk3kkUe(jSV9IKnemH7K, xafqLlk3kkUe(SXOLrMavuUCe(b'\xc9w\xb8\x93(\xdf\xcc\x07Q\xc5'), chr(0b1100100) + chr(1175 - 1074) + chr(0b1011000 + 0o13) + chr(111) + chr(0b1100100) + '\145')(chr(0b1011101 + 0o30) + '\x74' + chr(102) + chr(0b100100 + 0o11) + '\x38'))):
_IZEDmb5AMbL = IF08dLE993_s(kSTOB7MpzlDk, errors=xafqLlk3kkUe(SXOLrMavuUCe(b'\xc9y\xa9\x84,\xd5'), chr(0b11110 + 0o106) + '\145' + chr(99) + chr(0b1101111) + chr(2651 - 2551) + chr(101))(chr(0b1101110 + 0o7) + chr(0b1110100) + chr(0b11001 + 0o115) + chr(0b100110 + 0o7) + chr(0b0 + 0o70)))
elif n1ufouZS6xrY(xafqLlk3kkUe(jSV9IKnemH7K, xafqLlk3kkUe(SXOLrMavuUCe(b'\xc9w\xb8\x93(\xdf\xcc\x07Q\xc5'), chr(0b1100100) + chr(101) + chr(0b1010 + 0o131) + '\x6f' + '\x64' + '\x65')('\x75' + '\164' + chr(102) + chr(1296 - 1251) + '\x38'))):
_IZEDmb5AMbL = o52vswvoQUMc(kSTOB7MpzlDk, errors=xafqLlk3kkUe(SXOLrMavuUCe(b'\xc9y\xa9\x84,\xd5'), '\144' + '\x65' + chr(0b1010111 + 0o14) + '\x6f' + chr(0b1001100 + 0o30) + chr(0b111110 + 0o47))('\165' + chr(0b1110100) + chr(0b111010 + 0o54) + '\055' + chr(56)))
elif xafqLlk3kkUe(jSV9IKnemH7K.categories, xafqLlk3kkUe(SXOLrMavuUCe(b'\xc3e\x93\x94 \xdf\xd2\x0bU\xd8'), chr(0b100111 + 0o75) + chr(0b10101 + 0o120) + chr(9005 - 8906) + chr(111) + '\x64' + chr(101))(chr(0b1110101) + chr(13134 - 13018) + '\146' + '\055' + '\x38'))():
if t6baE7EFJavV is None:
t6baE7EFJavV = [xafqLlk3kkUe(SXOLrMavuUCe(b'\xfed\xb9\x93'), chr(0b111010 + 0o52) + chr(0b1100101) + '\x63' + chr(1779 - 1668) + chr(0b1010101 + 0o17) + '\145')('\165' + chr(0b1100010 + 0o22) + chr(102) + chr(0b101101) + chr(0b100001 + 0o27)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xfeD\x99\xb3'), chr(1531 - 1431) + chr(0b1100101) + chr(0b1100011) + '\x6f' + chr(0b1100100) + chr(2039 - 1938))(chr(0b1110101) + '\x74' + chr(0b1100110) + chr(0b101101) + chr(0b111000)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xded\xb9\x93'), chr(0b1100100) + '\x65' + chr(99) + '\x6f' + chr(0b1100100) + chr(1208 - 1107))('\165' + '\164' + chr(102) + '\x2d' + '\070')]
_IZEDmb5AMbL = _IZEDmb5AMbL.isin(t6baE7EFJavV)
if fsMVcjitw7pK:
mZZDAT49UzAb = jSV9IKnemH7K.categories
AoWJEgIAbHh_ = V3m1SlhRYSW0(aKSlaOrC7I1g, _IZEDmb5AMbL, mZZDAT49UzAb)
elif not xafqLlk3kkUe(_IZEDmb5AMbL, xafqLlk3kkUe(SXOLrMavuUCe(b'\xc3e\x93\x9b \xde\xd1\x1a[\xd8]\xe8\xd9\xeb\x1d\x84\xe5\xb21\xd0s\xf8\x0b'), '\x64' + '\145' + chr(0b1100011) + chr(0b100011 + 0o114) + chr(100) + chr(0b110100 + 0o61))('\165' + '\164' + chr(0b111101 + 0o51) + '\x2d' + chr(56))):
pdUUd5kyzN3b = _IZEDmb5AMbL.igThHS4jwVsa()
mZZDAT49UzAb = _IZEDmb5AMbL.sort_values()
AoWJEgIAbHh_ = V3m1SlhRYSW0(aKSlaOrC7I1g, pdUUd5kyzN3b, mZZDAT49UzAb)
jSV9IKnemH7K = CBSVoRj_kvTn(mZZDAT49UzAb, ordered=ehT0Px3KOsy9('\060' + chr(1305 - 1194) + chr(48), ord("\x08")))
else:
jSV9IKnemH7K = CBSVoRj_kvTn(_IZEDmb5AMbL, ordered=ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b1001 + 0o47), 8))
AoWJEgIAbHh_ = aKSlaOrC7I1g
return NSstowUUZlxS(AoWJEgIAbHh_, dtype=jSV9IKnemH7K, fastpath=ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110001), 8))
|
pandas-dev/pandas
|
pandas/core/arrays/categorical.py
|
Categorical.from_codes
|
def from_codes(cls, codes, categories=None, ordered=None, dtype=None):
"""
Make a Categorical type from codes and categories or dtype.
This constructor is useful if you already have codes and
categories/dtype and so do not need the (computation intensive)
factorization step, which is usually done on the constructor.
If your data does not follow this convention, please use the normal
constructor.
Parameters
----------
codes : array-like, integers
An integer array, where each integer points to a category in
categories or dtype.categories, or else is -1 for NaN.
categories : index-like, optional
The categories for the categorical. Items need to be unique.
If the categories are not given here, then they must be provided
in `dtype`.
ordered : bool, optional
Whether or not this categorical is treated as an ordered
categorical. If not given here or in `dtype`, the resulting
categorical will be unordered.
dtype : CategoricalDtype or the string "category", optional
If :class:`CategoricalDtype`, cannot be used together with
`categories` or `ordered`.
.. versionadded:: 0.24.0
When `dtype` is provided, neither `categories` nor `ordered`
should be provided.
Examples
--------
>>> dtype = pd.CategoricalDtype(['a', 'b'], ordered=True)
>>> pd.Categorical.from_codes(codes=[0, 1, 0, 1], dtype=dtype)
[a, b, a, b]
Categories (2, object): [a < b]
"""
dtype = CategoricalDtype._from_values_or_dtype(categories=categories,
ordered=ordered,
dtype=dtype)
if dtype.categories is None:
msg = ("The categories must be provided in 'categories' or "
"'dtype'. Both were None.")
raise ValueError(msg)
codes = np.asarray(codes) # #21767
if not is_integer_dtype(codes):
msg = "codes need to be array-like integers"
if is_float_dtype(codes):
icodes = codes.astype('i8')
if (icodes == codes).all():
msg = None
codes = icodes
warn(("float codes will be disallowed in the future and "
"raise a ValueError"), FutureWarning, stacklevel=2)
if msg:
raise ValueError(msg)
if len(codes) and (
codes.max() >= len(dtype.categories) or codes.min() < -1):
raise ValueError("codes need to be between -1 and "
"len(categories)-1")
return cls(codes, dtype=dtype, fastpath=True)
|
python
|
def from_codes(cls, codes, categories=None, ordered=None, dtype=None):
"""
Make a Categorical type from codes and categories or dtype.
This constructor is useful if you already have codes and
categories/dtype and so do not need the (computation intensive)
factorization step, which is usually done on the constructor.
If your data does not follow this convention, please use the normal
constructor.
Parameters
----------
codes : array-like, integers
An integer array, where each integer points to a category in
categories or dtype.categories, or else is -1 for NaN.
categories : index-like, optional
The categories for the categorical. Items need to be unique.
If the categories are not given here, then they must be provided
in `dtype`.
ordered : bool, optional
Whether or not this categorical is treated as an ordered
categorical. If not given here or in `dtype`, the resulting
categorical will be unordered.
dtype : CategoricalDtype or the string "category", optional
If :class:`CategoricalDtype`, cannot be used together with
`categories` or `ordered`.
.. versionadded:: 0.24.0
When `dtype` is provided, neither `categories` nor `ordered`
should be provided.
Examples
--------
>>> dtype = pd.CategoricalDtype(['a', 'b'], ordered=True)
>>> pd.Categorical.from_codes(codes=[0, 1, 0, 1], dtype=dtype)
[a, b, a, b]
Categories (2, object): [a < b]
"""
dtype = CategoricalDtype._from_values_or_dtype(categories=categories,
ordered=ordered,
dtype=dtype)
if dtype.categories is None:
msg = ("The categories must be provided in 'categories' or "
"'dtype'. Both were None.")
raise ValueError(msg)
codes = np.asarray(codes) # #21767
if not is_integer_dtype(codes):
msg = "codes need to be array-like integers"
if is_float_dtype(codes):
icodes = codes.astype('i8')
if (icodes == codes).all():
msg = None
codes = icodes
warn(("float codes will be disallowed in the future and "
"raise a ValueError"), FutureWarning, stacklevel=2)
if msg:
raise ValueError(msg)
if len(codes) and (
codes.max() >= len(dtype.categories) or codes.min() < -1):
raise ValueError("codes need to be between -1 and "
"len(categories)-1")
return cls(codes, dtype=dtype, fastpath=True)
|
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] |
Make a Categorical type from codes and categories or dtype.
This constructor is useful if you already have codes and
categories/dtype and so do not need the (computation intensive)
factorization step, which is usually done on the constructor.
If your data does not follow this convention, please use the normal
constructor.
Parameters
----------
codes : array-like, integers
An integer array, where each integer points to a category in
categories or dtype.categories, or else is -1 for NaN.
categories : index-like, optional
The categories for the categorical. Items need to be unique.
If the categories are not given here, then they must be provided
in `dtype`.
ordered : bool, optional
Whether or not this categorical is treated as an ordered
categorical. If not given here or in `dtype`, the resulting
categorical will be unordered.
dtype : CategoricalDtype or the string "category", optional
If :class:`CategoricalDtype`, cannot be used together with
`categories` or `ordered`.
.. versionadded:: 0.24.0
When `dtype` is provided, neither `categories` nor `ordered`
should be provided.
Examples
--------
>>> dtype = pd.CategoricalDtype(['a', 'b'], ordered=True)
>>> pd.Categorical.from_codes(codes=[0, 1, 0, 1], dtype=dtype)
[a, b, a, b]
Categories (2, object): [a < b]
|
[
"Make",
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"Categorical",
"type",
"from",
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"and",
"categories",
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"dtype",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/arrays/categorical.py#L589-L655
|
train
|
Create a new instance of the class with the given codes and categories and dtype.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b10100 + 0o34) + chr(0b1101111) + chr(2201 - 2152) + chr(53) + chr(0b110010), 0o10), ehT0Px3KOsy9('\060' + chr(0b10110 + 0o131) + chr(0b110011) + chr(0b110000) + '\x31', 0b1000), ehT0Px3KOsy9(chr(85 - 37) + '\157' + chr(0b110010) + chr(54) + '\x30', 0b1000), ehT0Px3KOsy9('\060' + chr(3171 - 3060) + '\x33' + chr(0b101010 + 0o11) + '\067', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x35' + chr(72 - 23), 0o10), ehT0Px3KOsy9('\x30' + chr(5124 - 5013) + chr(0b11011 + 0o27) + chr(0b110000) + chr(0b110011), 0b1000), ehT0Px3KOsy9(chr(48) + chr(9764 - 9653) + chr(51) + chr(1500 - 1448) + chr(0b1110 + 0o42), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(1401 - 1352) + chr(1588 - 1540) + chr(663 - 608), 0b1000), ehT0Px3KOsy9(chr(0b101101 + 0o3) + '\x6f' + '\x31' + chr(0b110111) + '\x34', 0b1000), ehT0Px3KOsy9(chr(0b101010 + 0o6) + chr(7402 - 7291) + chr(2480 - 2425), 0b1000), ehT0Px3KOsy9(chr(1853 - 1805) + chr(5745 - 5634) + '\x33' + '\065', 12427 - 12419), ehT0Px3KOsy9(chr(0b100100 + 0o14) + '\157' + chr(51) + chr(0b110110) + chr(288 - 233), ord("\x08")), ehT0Px3KOsy9(chr(212 - 164) + chr(111) + chr(50) + chr(673 - 622) + chr(0b10010 + 0o36), 60784 - 60776), ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(3053 - 2942) + chr(50) + chr(0b100 + 0o61) + '\064', 63060 - 63052), ehT0Px3KOsy9(chr(0b100010 + 0o16) + '\157' + chr(983 - 933) + chr(64 - 13) + chr(0b11010 + 0o30), 0b1000), ehT0Px3KOsy9(chr(0b1 + 0o57) + chr(0b1101111) + chr(0b101000 + 0o11) + chr(1253 - 1202) + chr(0b1011 + 0o54), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(51) + '\x31' + '\x37', 0o10), ehT0Px3KOsy9('\060' + chr(0b101100 + 0o103) + chr(0b10001 + 0o42) + '\066' + chr(414 - 363), 34631 - 34623), ehT0Px3KOsy9(chr(0b101011 + 0o5) + '\157' + '\x31' + chr(1260 - 1211) + chr(49), 0b1000), ehT0Px3KOsy9(chr(1443 - 1395) + '\x6f' + chr(0b110011) + chr(0b110100) + '\062', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b110101 + 0o72) + chr(1675 - 1620) + chr(1090 - 1042), 2207 - 2199), ehT0Px3KOsy9('\060' + chr(0b100 + 0o153) + '\062' + '\062' + chr(0b11110 + 0o30), ord("\x08")), ehT0Px3KOsy9(chr(0b110000 + 0o0) + '\x6f' + chr(0b110010) + '\062' + '\065', ord("\x08")), ehT0Px3KOsy9(chr(0b100111 + 0o11) + '\x6f' + chr(237 - 188) + chr(0b110100), 24406 - 24398), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110101) + '\066', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x32' + '\061' + chr(0b110100), 37293 - 37285), ehT0Px3KOsy9(chr(484 - 436) + chr(0b1101111) + chr(50 - 1) + '\067' + chr(54), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101010 + 0o5) + chr(49) + chr(872 - 817) + '\x35', 33807 - 33799), ehT0Px3KOsy9(chr(48) + '\157' + '\061', 44982 - 44974), ehT0Px3KOsy9('\x30' + '\x6f' + '\x31' + chr(0b110100) + chr(0b110100 + 0o2), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111 + 0o0) + chr(1797 - 1745) + chr(50), 20231 - 20223), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(53) + chr(0b10 + 0o62), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + '\x32' + '\061' + '\065', ord("\x08")), ehT0Px3KOsy9(chr(0b100 + 0o54) + chr(111) + chr(0b110110) + chr(55), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + '\065' + '\x34', 8), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(50) + chr(1503 - 1452) + chr(0b1100 + 0o52), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\063' + chr(0b10 + 0o61) + chr(0b11001 + 0o33), 0o10), ehT0Px3KOsy9('\060' + chr(0b10010 + 0o135) + chr(0b110001) + chr(1767 - 1715) + chr(947 - 895), 53989 - 53981), ehT0Px3KOsy9(chr(797 - 749) + chr(1621 - 1510) + chr(51) + '\066', 48196 - 48188), ehT0Px3KOsy9(chr(0b110000) + chr(0b110001 + 0o76) + chr(0b110010) + chr(1321 - 1273) + chr(0b110010), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110101) + chr(48), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'D'), chr(0b1100100) + chr(0b1100101) + '\143' + '\x6f' + chr(9346 - 9246) + '\145')(chr(4744 - 4627) + chr(0b1100011 + 0o21) + chr(102) + chr(0b100 + 0o51) + chr(1819 - 1763)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def AEefMUpzcPbT(NSstowUUZlxS, AoWJEgIAbHh_, mZZDAT49UzAb=None, TillFngeGqII=None, jSV9IKnemH7K=None):
jSV9IKnemH7K = CBSVoRj_kvTn._from_values_or_dtype(categories=mZZDAT49UzAb, ordered=TillFngeGqII, dtype=jSV9IKnemH7K)
if xafqLlk3kkUe(jSV9IKnemH7K, xafqLlk3kkUe(SXOLrMavuUCe(b'\t\xa0\xc4\xbaN\xec\x92.\x19t'), chr(0b1100100) + '\145' + chr(0b1100011) + chr(0b1010011 + 0o34) + '\x64' + '\x65')(chr(117) + chr(116) + chr(0b11001 + 0o115) + chr(0b101101) + '\070')) is None:
jtbovtaIYjRB = xafqLlk3kkUe(SXOLrMavuUCe(b'>\xa9\xd5\xffJ\xe2\x94"\x1bho\x9e\xfd\xdf\xba2\xba\x80=\xc2Z\xf3\xb5|\\\xe3\x08\x14e\x03F\x0c\xe4Y\x0c\xb9\xbf\x05j\xe7\r\xae\xc2\xb6L\xf0\xc7g\x13u=\xd0\xfc\xd8\xe3/\xaa\xd4g\xc2z\xf9\xe1d\x0e\xfb\x1b\x0fdFlC\xe3R\x02'), chr(0b111011 + 0o51) + '\x65' + '\x63' + chr(0b1101111) + chr(0b1100100) + chr(0b110000 + 0o65))(chr(0b1110101) + chr(7040 - 6924) + chr(0b1010011 + 0o23) + chr(341 - 296) + chr(0b111000))
raise q1QCh3W88sgk(jtbovtaIYjRB)
AoWJEgIAbHh_ = WqUC3KWvYVup.asarray(AoWJEgIAbHh_)
if not vbqhcY5kX820(AoWJEgIAbHh_):
jtbovtaIYjRB = xafqLlk3kkUe(SXOLrMavuUCe(b'\t\xae\xd4\xbaZ\xa3\x8e"\x19c=\x83\xf7\x8c\xf8:\xef\x92;\x90Y\xef\xb8`G\xe7\x1b]h\x08VI\xeaR^\xed'), chr(100) + chr(101) + chr(577 - 478) + chr(0b1011101 + 0o22) + '\x64' + chr(101))(chr(117) + chr(7138 - 7022) + chr(5933 - 5831) + '\055' + chr(213 - 157))
if GID6_fWM6lkY(AoWJEgIAbHh_):
W2PA20tqRUOX = AoWJEgIAbHh_.astype(xafqLlk3kkUe(SXOLrMavuUCe(b'\x03\xf9'), chr(0b1011010 + 0o12) + chr(101) + '\143' + chr(0b1101111) + chr(1751 - 1651) + '\145')(chr(117) + chr(116) + '\x66' + '\055' + chr(0b111000)))
if xafqLlk3kkUe(W2PA20tqRUOX == AoWJEgIAbHh_, xafqLlk3kkUe(SXOLrMavuUCe(b'.\xad\x84\xe7G\xe9\xd15\x1en/\xc4'), '\144' + chr(0b1100101) + '\143' + chr(3659 - 3548) + chr(6465 - 6365) + '\x65')(chr(117) + chr(0b11111 + 0o125) + chr(0b1100110) + chr(0b10010 + 0o33) + chr(0b101000 + 0o20)))():
jtbovtaIYjRB = None
AoWJEgIAbHh_ = W2PA20tqRUOX
nDEnNBabFNKm(xafqLlk3kkUe(SXOLrMavuUCe(b'\x0c\xad\xdf\xbe]\xa3\x83(\x18bn\xd7\xef\xc5\xf63\xef\x91,\xc2\\\xff\xe6mB\xe0\x11\nd\x02\x02E\xe3\x17X\xf6\xb9Dx\xf7\x1e\xb4\xc2\xba\t\xe2\x8e#\\u|\x9e\xeb\xc9\xba>\xef\xa5(\x8eM\xf3\xd0~\\\xe3\x0c'), '\x64' + chr(0b1100101) + '\x63' + chr(0b1000101 + 0o52) + chr(0b100011 + 0o101) + '\145')(chr(0b10011 + 0o142) + chr(116) + chr(0b1100 + 0o132) + chr(1732 - 1687) + chr(0b0 + 0o70)), VHAt7CcYKC2T, stacklevel=ehT0Px3KOsy9('\060' + chr(11832 - 11721) + chr(0b100111 + 0o13), 31745 - 31737))
if jtbovtaIYjRB:
raise q1QCh3W88sgk(jtbovtaIYjRB)
if c2A0yzQpDQB3(AoWJEgIAbHh_) and (xafqLlk3kkUe(AoWJEgIAbHh_, xafqLlk3kkUe(SXOLrMavuUCe(b'\x1e\xb2\xd4\xb5_\xef\x87/E`Y\xa7'), chr(599 - 499) + chr(3474 - 3373) + '\x63' + '\x6f' + '\x64' + chr(6228 - 6127))(chr(0b1110101) + chr(0b101001 + 0o113) + chr(102) + chr(0b101101) + '\x38'))() >= c2A0yzQpDQB3(xafqLlk3kkUe(jSV9IKnemH7K, xafqLlk3kkUe(SXOLrMavuUCe(b'\t\xa0\xc4\xbaN\xec\x92.\x19t'), chr(0b101111 + 0o65) + chr(0b1100101) + chr(99) + chr(111) + chr(0b1100100) + chr(0b1100101))(chr(0b100001 + 0o124) + '\164' + chr(102) + '\x2d' + chr(56)))) or xafqLlk3kkUe(AoWJEgIAbHh_, xafqLlk3kkUe(SXOLrMavuUCe(b'.\xb9\x82\xedK\xe8\xab\x17\x18s(\x93'), chr(0b1100100) + chr(0b1100101) + chr(0b10100 + 0o117) + chr(111) + '\144' + '\145')(chr(0b1110101) + chr(0b1110100) + chr(0b1100110) + '\055' + '\x38'))() < -ehT0Px3KOsy9('\060' + '\x6f' + chr(1079 - 1030), 8)):
raise q1QCh3W88sgk(xafqLlk3kkUe(SXOLrMavuUCe(b'\t\xae\xd4\xbaZ\xa3\x8e"\x19c=\x83\xf7\x8c\xf8:\xef\x91,\x96O\xf3\xf0b\x0e\xa1O]`\x08F\x0c\xe1RB\xb6\xbf\x05j\xe7\r\xae\xc2\xb6L\xf0\xc9jM'), '\144' + chr(109 - 8) + chr(99) + chr(0b1011011 + 0o24) + chr(0b111101 + 0o47) + chr(0b1100101))(chr(117) + '\164' + chr(7843 - 7741) + chr(0b101101) + chr(0b111000)))
return NSstowUUZlxS(AoWJEgIAbHh_, dtype=jSV9IKnemH7K, fastpath=ehT0Px3KOsy9('\060' + chr(0b110011 + 0o74) + chr(1636 - 1587), 8))
|
pandas-dev/pandas
|
pandas/core/arrays/categorical.py
|
Categorical._get_codes
|
def _get_codes(self):
"""
Get the codes.
Returns
-------
codes : integer array view
A non writable view of the `codes` array.
"""
v = self._codes.view()
v.flags.writeable = False
return v
|
python
|
def _get_codes(self):
"""
Get the codes.
Returns
-------
codes : integer array view
A non writable view of the `codes` array.
"""
v = self._codes.view()
v.flags.writeable = False
return v
|
[
"def",
"_get_codes",
"(",
"self",
")",
":",
"v",
"=",
"self",
".",
"_codes",
".",
"view",
"(",
")",
"v",
".",
"flags",
".",
"writeable",
"=",
"False",
"return",
"v"
] |
Get the codes.
Returns
-------
codes : integer array view
A non writable view of the `codes` array.
|
[
"Get",
"the",
"codes",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/arrays/categorical.py#L659-L670
|
train
|
Returns a view of the codes array.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\x30' + chr(111) + chr(249 - 198) + chr(0b110110) + chr(344 - 296), 52346 - 52338), ehT0Px3KOsy9(chr(1402 - 1354) + chr(111) + '\067' + chr(48), 0o10), ehT0Px3KOsy9(chr(0b1100 + 0o44) + chr(0b1101111) + '\x34' + chr(0b110101), 0o10), ehT0Px3KOsy9(chr(72 - 24) + chr(111) + chr(0b1111 + 0o42) + chr(0b110110) + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1001100 + 0o43) + chr(0b10000 + 0o41) + '\061' + '\x32', 0o10), ehT0Px3KOsy9(chr(102 - 54) + '\x6f' + chr(50) + chr(52) + '\x35', 0b1000), ehT0Px3KOsy9(chr(0b11 + 0o55) + chr(111) + chr(299 - 246) + chr(0b11011 + 0o25), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110001) + '\x31' + chr(0b110110), 0o10), ehT0Px3KOsy9('\060' + chr(9116 - 9005) + chr(0b110001) + chr(0b110101) + '\x33', 0b1000), ehT0Px3KOsy9('\x30' + '\157' + '\061' + chr(0b10000 + 0o41) + chr(1305 - 1252), 0o10), ehT0Px3KOsy9(chr(0b101000 + 0o10) + chr(7621 - 7510) + chr(49), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110110) + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(0b1101111) + '\062' + chr(0b110101) + chr(0b11011 + 0o26), 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110111) + chr(0b110000), 8), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\063' + chr(0b110110) + chr(48), 8), ehT0Px3KOsy9('\x30' + chr(111) + '\061' + chr(52) + '\x36', 1953 - 1945), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110011) + chr(1968 - 1919) + '\x33', 25999 - 25991), ehT0Px3KOsy9(chr(1103 - 1055) + chr(0b1100011 + 0o14) + '\x33', 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110000 + 0o3) + chr(0b110110) + chr(52), 0o10), ehT0Px3KOsy9(chr(69 - 21) + '\157' + '\062' + chr(0b110011) + chr(0b110000), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b11110 + 0o25) + chr(2346 - 2295) + '\063', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(2317 - 2267) + chr(0b110101) + chr(2834 - 2780), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b10 + 0o155) + chr(51) + '\x31', 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(546 - 492) + chr(305 - 257), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110010) + chr(1411 - 1356) + '\064', 27480 - 27472), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b1100 + 0o46) + '\066' + chr(1347 - 1299), 0b1000), ehT0Px3KOsy9(chr(1512 - 1464) + chr(10642 - 10531) + chr(885 - 835) + '\x33' + '\061', 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(51) + '\065', 37163 - 37155), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(158 - 108) + '\x34' + '\x35', 8), ehT0Px3KOsy9('\060' + chr(0b1000011 + 0o54) + chr(0b110011) + chr(0b110000) + '\x37', 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(1444 - 1390), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + '\062' + chr(699 - 646) + chr(1339 - 1286), 0b1000), ehT0Px3KOsy9(chr(0b1 + 0o57) + chr(5694 - 5583) + '\x33' + '\060' + '\061', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b10010 + 0o135) + '\062' + '\066' + chr(0b110011), 6303 - 6295), ehT0Px3KOsy9(chr(48) + chr(10365 - 10254) + chr(153 - 104) + chr(50) + chr(0b101010 + 0o7), 0b1000), ehT0Px3KOsy9('\x30' + chr(7843 - 7732) + chr(0b110011) + chr(49) + chr(0b100011 + 0o17), 0b1000), ehT0Px3KOsy9(chr(0b101111 + 0o1) + '\157' + chr(49) + chr(315 - 261) + '\067', 0o10), ehT0Px3KOsy9(chr(2099 - 2051) + chr(6279 - 6168) + '\x31' + chr(53), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(906 - 856) + chr(0b110010) + chr(2880 - 2826), 0o10), ehT0Px3KOsy9('\x30' + chr(0b110111 + 0o70) + '\065' + chr(1841 - 1786), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + chr(111) + chr(0b1001 + 0o54) + '\x30', 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xde'), '\x64' + chr(101) + chr(0b101101 + 0o66) + chr(111) + '\x64' + chr(9885 - 9784))(chr(4704 - 4587) + '\164' + chr(2079 - 1977) + chr(0b11101 + 0o20) + chr(0b101111 + 0o11)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def BbN0WlDsCeqK(oVre8I6UXc3b):
cMbll0QYhULo = oVre8I6UXc3b._codes.view()
cMbll0QYhULo.flags.rdGsi_SWQw7q = ehT0Px3KOsy9('\x30' + chr(6941 - 6830) + chr(0b100110 + 0o12), ord("\x08"))
return cMbll0QYhULo
|
pandas-dev/pandas
|
pandas/core/arrays/categorical.py
|
Categorical._set_categories
|
def _set_categories(self, categories, fastpath=False):
"""
Sets new categories inplace
Parameters
----------
fastpath : bool, default False
Don't perform validation of the categories for uniqueness or nulls
Examples
--------
>>> c = pd.Categorical(['a', 'b'])
>>> c
[a, b]
Categories (2, object): [a, b]
>>> c._set_categories(pd.Index(['a', 'c']))
>>> c
[a, c]
Categories (2, object): [a, c]
"""
if fastpath:
new_dtype = CategoricalDtype._from_fastpath(categories,
self.ordered)
else:
new_dtype = CategoricalDtype(categories, ordered=self.ordered)
if (not fastpath and self.dtype.categories is not None and
len(new_dtype.categories) != len(self.dtype.categories)):
raise ValueError("new categories need to have the same number of "
"items than the old categories!")
self._dtype = new_dtype
|
python
|
def _set_categories(self, categories, fastpath=False):
"""
Sets new categories inplace
Parameters
----------
fastpath : bool, default False
Don't perform validation of the categories for uniqueness or nulls
Examples
--------
>>> c = pd.Categorical(['a', 'b'])
>>> c
[a, b]
Categories (2, object): [a, b]
>>> c._set_categories(pd.Index(['a', 'c']))
>>> c
[a, c]
Categories (2, object): [a, c]
"""
if fastpath:
new_dtype = CategoricalDtype._from_fastpath(categories,
self.ordered)
else:
new_dtype = CategoricalDtype(categories, ordered=self.ordered)
if (not fastpath and self.dtype.categories is not None and
len(new_dtype.categories) != len(self.dtype.categories)):
raise ValueError("new categories need to have the same number of "
"items than the old categories!")
self._dtype = new_dtype
|
[
"def",
"_set_categories",
"(",
"self",
",",
"categories",
",",
"fastpath",
"=",
"False",
")",
":",
"if",
"fastpath",
":",
"new_dtype",
"=",
"CategoricalDtype",
".",
"_from_fastpath",
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"categories",
",",
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"new_dtype",
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"categories",
",",
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"self",
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"ordered",
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"if",
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".",
"dtype",
".",
"categories",
"is",
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"len",
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"!=",
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"(",
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")",
")",
":",
"raise",
"ValueError",
"(",
"\"new categories need to have the same number of \"",
"\"items than the old categories!\"",
")",
"self",
".",
"_dtype",
"=",
"new_dtype"
] |
Sets new categories inplace
Parameters
----------
fastpath : bool, default False
Don't perform validation of the categories for uniqueness or nulls
Examples
--------
>>> c = pd.Categorical(['a', 'b'])
>>> c
[a, b]
Categories (2, object): [a, b]
>>> c._set_categories(pd.Index(['a', 'c']))
>>> c
[a, c]
Categories (2, object): [a, c]
|
[
"Sets",
"new",
"categories",
"inplace"
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/arrays/categorical.py#L680-L712
|
train
|
Sets new categories in the current object.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(48) + '\157' + chr(49) + '\x35' + chr(0b101000 + 0o15), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1100011 + 0o14) + chr(0b110011 + 0o0) + '\067' + '\066', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(51) + '\066' + chr(50), ord("\x08")), ehT0Px3KOsy9(chr(0b11111 + 0o21) + '\x6f' + '\061' + chr(1583 - 1529) + chr(495 - 443), 0b1000), ehT0Px3KOsy9(chr(1820 - 1772) + chr(5523 - 5412) + chr(1125 - 1072), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(51) + '\x35' + '\063', 0b1000), ehT0Px3KOsy9(chr(2004 - 1956) + '\x6f' + '\x37' + '\x36', 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110001) + '\066' + chr(2292 - 2244), 34211 - 34203), ehT0Px3KOsy9(chr(48) + chr(3336 - 3225) + '\x35' + chr(0b110011), 5115 - 5107), ehT0Px3KOsy9(chr(0b1 + 0o57) + chr(0b10001 + 0o136) + '\x32' + chr(52) + chr(0b1000 + 0o56), 58916 - 58908), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(51) + chr(2239 - 2190) + chr(51), 1152 - 1144), ehT0Px3KOsy9(chr(48) + chr(0b1010101 + 0o32) + chr(0b110001) + '\060' + chr(1451 - 1396), 0b1000), ehT0Px3KOsy9(chr(0b10011 + 0o35) + chr(0b1101110 + 0o1) + '\062' + '\x37' + chr(0b110 + 0o53), 25209 - 25201), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x32' + '\x37' + chr(0b110101), 64259 - 64251), ehT0Px3KOsy9(chr(1971 - 1923) + chr(9422 - 9311) + chr(50) + chr(52) + '\x34', 13163 - 13155), ehT0Px3KOsy9(chr(2227 - 2179) + chr(7219 - 7108) + '\x32' + chr(0b110011) + chr(49), 0o10), ehT0Px3KOsy9(chr(976 - 928) + chr(0b111001 + 0o66) + chr(51), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x31' + chr(48) + chr(0b110001), 5319 - 5311), ehT0Px3KOsy9(chr(0b101 + 0o53) + '\x6f' + chr(0b110001) + '\x34' + '\066', 33003 - 32995), ehT0Px3KOsy9(chr(0b11 + 0o55) + chr(111) + '\x36', ord("\x08")), ehT0Px3KOsy9(chr(1955 - 1907) + chr(0b11111 + 0o120) + chr(0b100011 + 0o22) + '\x36', 7933 - 7925), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\062' + '\x34' + chr(48), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + '\x32' + chr(0b1111 + 0o46) + chr(54), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b100111 + 0o110) + '\061' + chr(0b10010 + 0o40) + '\065', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(54) + chr(0b110101), 18790 - 18782), ehT0Px3KOsy9(chr(48) + chr(410 - 299) + chr(0b110101) + '\062', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b1100 + 0o47) + '\x33' + chr(49), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110000 + 0o0), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b100 + 0o153) + chr(51) + chr(54) + '\066', 19139 - 19131), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\063' + '\x30' + '\061', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(51) + chr(0b110101) + chr(0b10111 + 0o40), 0o10), ehT0Px3KOsy9(chr(0b100100 + 0o14) + chr(0b110111 + 0o70) + chr(0b100111 + 0o12) + chr(0b110010) + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(0b100011 + 0o15) + '\157' + chr(879 - 830) + chr(0b11 + 0o61) + chr(848 - 796), 4747 - 4739), ehT0Px3KOsy9(chr(0b10011 + 0o35) + chr(0b1101111) + chr(0b110011) + chr(0b110011) + chr(0b1101 + 0o46), 0o10), ehT0Px3KOsy9(chr(0b10011 + 0o35) + '\x6f' + chr(279 - 230) + chr(51) + '\x37', 0o10), ehT0Px3KOsy9('\x30' + chr(10027 - 9916) + '\x33' + '\x32' + '\x31', 0o10), ehT0Px3KOsy9('\060' + chr(10257 - 10146) + '\063' + chr(54) + chr(0b110010), 8), ehT0Px3KOsy9(chr(1412 - 1364) + chr(0b10110 + 0o131) + chr(49) + '\061' + '\064', 63433 - 63425), ehT0Px3KOsy9('\060' + chr(111) + chr(51) + '\060' + '\x32', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x33' + chr(54) + chr(0b110011), 46092 - 46084)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(1081 - 1033) + '\157' + chr(53) + chr(1482 - 1434), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'C'), '\x64' + chr(101) + chr(0b1100011) + '\157' + '\144' + chr(0b1100101))('\165' + '\x74' + chr(0b1100110) + chr(1916 - 1871) + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def SAjQFizxjgt3(oVre8I6UXc3b, mZZDAT49UzAb, pc1tSsQK7sha=ehT0Px3KOsy9(chr(0b10011 + 0o35) + chr(0b1101111) + chr(0b110000), 8)):
if pc1tSsQK7sha:
H6Aqpf9qhdEs = CBSVoRj_kvTn._from_fastpath(mZZDAT49UzAb, oVre8I6UXc3b.ordered)
else:
H6Aqpf9qhdEs = CBSVoRj_kvTn(mZZDAT49UzAb, ordered=oVre8I6UXc3b.ordered)
if not pc1tSsQK7sha and xafqLlk3kkUe(oVre8I6UXc3b.dtype, xafqLlk3kkUe(SXOLrMavuUCe(b'\x0e\x9f\x86\x11b\x84L\x19N\xd5'), '\144' + chr(101) + chr(7404 - 7305) + chr(9178 - 9067) + chr(0b1100100) + chr(0b0 + 0o145))(chr(0b1110101) + chr(0b1101001 + 0o13) + chr(9433 - 9331) + '\055' + '\070')) is not None and (c2A0yzQpDQB3(xafqLlk3kkUe(H6Aqpf9qhdEs, xafqLlk3kkUe(SXOLrMavuUCe(b'\x0e\x9f\x86\x11b\x84L\x19N\xd5'), '\144' + chr(0b1100101) + chr(8058 - 7959) + chr(4433 - 4322) + chr(0b111000 + 0o54) + '\145')(chr(117) + chr(0b1110100) + chr(0b1010111 + 0o17) + chr(0b1111 + 0o36) + chr(56)))) != c2A0yzQpDQB3(xafqLlk3kkUe(oVre8I6UXc3b.dtype, xafqLlk3kkUe(SXOLrMavuUCe(b'\x0e\x9f\x86\x11b\x84L\x19N\xd5'), chr(100) + chr(0b1000001 + 0o44) + '\143' + chr(4186 - 4075) + chr(0b1100100) + chr(0b100100 + 0o101))(chr(0b101100 + 0o111) + chr(10867 - 10751) + chr(102) + chr(45) + '\x38')))):
raise q1QCh3W88sgk(xafqLlk3kkUe(SXOLrMavuUCe(b'\x03\x9b\x85Tf\x8aJ\x15L\xc9\xb9.\xdc\xce\x84\xf7f$\x02&Z\xcf\x8e=T\\\xbc \x82\xa9\x8ar\x17\xba2\xb4\xd2"\xb7\x9e\x0f\x9b\x80Tj\x8d\x1e\x19_\xc3\xa64\x99\xc9\xcc\xf8ma\x12nK\x80\xc19Q\n\xbaa\x82\xa4\x88=\x16\xb2:\xa2\xd3'), '\x64' + chr(7531 - 7430) + chr(99) + chr(0b1101111) + chr(0b100111 + 0o75) + chr(0b110 + 0o137))('\165' + chr(0b1000101 + 0o57) + '\x66' + chr(1370 - 1325) + chr(56)))
oVre8I6UXc3b.z2oVGDR5m1eh = H6Aqpf9qhdEs
|
pandas-dev/pandas
|
pandas/core/arrays/categorical.py
|
Categorical._set_dtype
|
def _set_dtype(self, dtype):
"""
Internal method for directly updating the CategoricalDtype
Parameters
----------
dtype : CategoricalDtype
Notes
-----
We don't do any validation here. It's assumed that the dtype is
a (valid) instance of `CategoricalDtype`.
"""
codes = _recode_for_categories(self.codes, self.categories,
dtype.categories)
return type(self)(codes, dtype=dtype, fastpath=True)
|
python
|
def _set_dtype(self, dtype):
"""
Internal method for directly updating the CategoricalDtype
Parameters
----------
dtype : CategoricalDtype
Notes
-----
We don't do any validation here. It's assumed that the dtype is
a (valid) instance of `CategoricalDtype`.
"""
codes = _recode_for_categories(self.codes, self.categories,
dtype.categories)
return type(self)(codes, dtype=dtype, fastpath=True)
|
[
"def",
"_set_dtype",
"(",
"self",
",",
"dtype",
")",
":",
"codes",
"=",
"_recode_for_categories",
"(",
"self",
".",
"codes",
",",
"self",
".",
"categories",
",",
"dtype",
".",
"categories",
")",
"return",
"type",
"(",
"self",
")",
"(",
"codes",
",",
"dtype",
"=",
"dtype",
",",
"fastpath",
"=",
"True",
")"
] |
Internal method for directly updating the CategoricalDtype
Parameters
----------
dtype : CategoricalDtype
Notes
-----
We don't do any validation here. It's assumed that the dtype is
a (valid) instance of `CategoricalDtype`.
|
[
"Internal",
"method",
"for",
"directly",
"updating",
"the",
"CategoricalDtype"
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/arrays/categorical.py#L714-L729
|
train
|
Internal method for directly updating the CategoricalDtype object.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + '\x6f' + chr(2470 - 2420) + chr(270 - 216) + '\061', 0o10), ehT0Px3KOsy9('\060' + chr(11446 - 11335) + chr(1111 - 1061) + chr(0b11000 + 0o30) + '\060', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(2038 - 1927) + '\x33' + '\x35', ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(0b100110 + 0o15) + '\x30' + '\x30', 43835 - 43827), ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(0b1101111) + chr(0b1011 + 0o46) + chr(1175 - 1124) + chr(0b110111), 9210 - 9202), ehT0Px3KOsy9('\060' + '\x6f' + chr(1609 - 1558) + chr(1502 - 1453) + '\063', 0o10), ehT0Px3KOsy9(chr(0b100000 + 0o20) + '\x6f' + '\061' + chr(962 - 912) + '\x35', 20523 - 20515), ehT0Px3KOsy9(chr(0b1010 + 0o46) + chr(0b1101111) + chr(0b110111) + '\067', 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110001) + '\x36' + chr(54), 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110100) + '\067', ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + '\x31' + chr(48) + chr(0b10 + 0o56), 21945 - 21937), ehT0Px3KOsy9('\x30' + chr(10977 - 10866) + chr(0b110101) + '\067', 0b1000), ehT0Px3KOsy9(chr(1958 - 1910) + chr(0b10111 + 0o130) + chr(55) + '\067', 8), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(51) + chr(0b110100) + '\067', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(88 - 38) + '\060' + chr(0b110001), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b110100 + 0o73) + chr(1514 - 1459) + chr(0b110100), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1111 + 0o140) + '\063' + chr(0b1010 + 0o53), 8), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110111) + chr(0b110111), 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b1001101 + 0o42) + chr(0b110001) + '\x31' + chr(48), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b101110 + 0o101) + chr(0b110010) + chr(1781 - 1732), 0b1000), ehT0Px3KOsy9('\x30' + chr(6774 - 6663) + chr(0b1111 + 0o43) + '\063' + chr(54), 4738 - 4730), ehT0Px3KOsy9(chr(878 - 830) + chr(0b1101111) + chr(0b10111 + 0o36) + '\x31', 0o10), ehT0Px3KOsy9(chr(1518 - 1470) + chr(11759 - 11648) + '\x31' + chr(0b101000 + 0o15) + '\x30', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b10010 + 0o135) + chr(0b110100) + chr(0b100100 + 0o21), 0o10), ehT0Px3KOsy9(chr(1705 - 1657) + chr(0b1000000 + 0o57) + '\063' + chr(0b110010) + chr(2350 - 2295), 10359 - 10351), ehT0Px3KOsy9(chr(1936 - 1888) + chr(0b110111 + 0o70) + '\062' + chr(593 - 539) + chr(0b1100 + 0o51), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b10111 + 0o33) + chr(212 - 157) + chr(55), 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110101) + '\x35', 28440 - 28432), ehT0Px3KOsy9(chr(807 - 759) + '\157' + '\063' + chr(0b10001 + 0o44) + chr(1037 - 988), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + '\x32', ord("\x08")), ehT0Px3KOsy9(chr(316 - 268) + '\x6f' + chr(50) + chr(478 - 426) + '\x37', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\064' + chr(55), 8), ehT0Px3KOsy9(chr(1995 - 1947) + chr(111) + chr(0b110100) + chr(0b1001 + 0o54), 8), ehT0Px3KOsy9('\060' + chr(8564 - 8453) + '\x33' + '\067' + chr(1353 - 1299), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\062' + chr(206 - 154) + chr(0b1000 + 0o50), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b100010 + 0o115) + chr(0b101100 + 0o12) + chr(0b110101), 55482 - 55474), ehT0Px3KOsy9(chr(0b100001 + 0o17) + '\x6f' + chr(357 - 309), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b1001 + 0o54) + '\x31', 8), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110011) + chr(746 - 692), 0b1000), ehT0Px3KOsy9(chr(1651 - 1603) + chr(0b1101111) + '\066' + chr(0b110011), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + '\157' + chr(0b1001 + 0o54) + '\x30', 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x9f'), '\x64' + chr(4773 - 4672) + '\143' + chr(111) + '\x64' + chr(101))(chr(0b1110101) + '\164' + chr(2808 - 2706) + chr(0b101010 + 0o3) + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def G5nLqUq0Bn7h(oVre8I6UXc3b, jSV9IKnemH7K):
AoWJEgIAbHh_ = V3m1SlhRYSW0(oVre8I6UXc3b.codes, oVre8I6UXc3b.categories, jSV9IKnemH7K.categories)
return wmQmyeWBmUpv(oVre8I6UXc3b)(AoWJEgIAbHh_, dtype=jSV9IKnemH7K, fastpath=ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(111) + chr(0b110001), ord("\x08")))
|
pandas-dev/pandas
|
pandas/core/arrays/categorical.py
|
Categorical.set_ordered
|
def set_ordered(self, value, inplace=False):
"""
Set the ordered attribute to the boolean value.
Parameters
----------
value : bool
Set whether this categorical is ordered (True) or not (False).
inplace : bool, default False
Whether or not to set the ordered attribute in-place or return
a copy of this categorical with ordered set to the value.
"""
inplace = validate_bool_kwarg(inplace, 'inplace')
new_dtype = CategoricalDtype(self.categories, ordered=value)
cat = self if inplace else self.copy()
cat._dtype = new_dtype
if not inplace:
return cat
|
python
|
def set_ordered(self, value, inplace=False):
"""
Set the ordered attribute to the boolean value.
Parameters
----------
value : bool
Set whether this categorical is ordered (True) or not (False).
inplace : bool, default False
Whether or not to set the ordered attribute in-place or return
a copy of this categorical with ordered set to the value.
"""
inplace = validate_bool_kwarg(inplace, 'inplace')
new_dtype = CategoricalDtype(self.categories, ordered=value)
cat = self if inplace else self.copy()
cat._dtype = new_dtype
if not inplace:
return cat
|
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",",
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] |
Set the ordered attribute to the boolean value.
Parameters
----------
value : bool
Set whether this categorical is ordered (True) or not (False).
inplace : bool, default False
Whether or not to set the ordered attribute in-place or return
a copy of this categorical with ordered set to the value.
|
[
"Set",
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"ordered",
"attribute",
"to",
"the",
"boolean",
"value",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/arrays/categorical.py#L731-L748
|
train
|
Sets the ordered attribute of the categorical.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + chr(10537 - 10426) + chr(1878 - 1829) + '\x34' + '\064', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(50) + chr(50) + chr(1400 - 1349), ord("\x08")), ehT0Px3KOsy9(chr(509 - 461) + chr(0b1101110 + 0o1) + '\063' + chr(52) + '\x30', 0o10), ehT0Px3KOsy9(chr(0b10100 + 0o34) + chr(10464 - 10353) + '\x33' + chr(1734 - 1682) + chr(0b11110 + 0o31), 22965 - 22957), ehT0Px3KOsy9('\060' + '\x6f' + chr(549 - 498) + '\x36' + chr(1213 - 1163), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\067' + chr(495 - 446), 14150 - 14142), ehT0Px3KOsy9('\x30' + chr(111) + chr(49) + chr(534 - 484) + '\x31', 0o10), ehT0Px3KOsy9(chr(0b1000 + 0o50) + chr(0b1001101 + 0o42) + chr(0b11100 + 0o27) + chr(0b1111 + 0o41) + '\066', 42287 - 42279), ehT0Px3KOsy9(chr(0b1010 + 0o46) + '\x6f' + chr(49) + chr(0b101100 + 0o12) + '\x32', 0o10), ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(0b1101111) + chr(0b110010) + chr(55) + chr(52), 0o10), ehT0Px3KOsy9('\x30' + chr(0b101100 + 0o103) + '\061' + chr(0b100 + 0o60) + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\063' + chr(975 - 922) + chr(0b100001 + 0o17), 0o10), ehT0Px3KOsy9('\060' + chr(111) + '\x32' + '\x34' + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(407 - 359) + chr(111) + '\061' + chr(0b110000) + chr(1113 - 1062), 0b1000), ehT0Px3KOsy9(chr(1097 - 1049) + chr(111) + chr(50) + '\x30' + chr(1725 - 1671), 0b1000), ehT0Px3KOsy9(chr(0b1100 + 0o44) + chr(111) + chr(65 - 15) + chr(0b11011 + 0o25) + chr(273 - 224), 0b1000), ehT0Px3KOsy9(chr(0b1110 + 0o42) + '\x6f' + '\061' + chr(0b110001) + chr(1702 - 1650), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(2106 - 2057) + chr(0b110101), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + '\063' + chr(0b110101), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\061' + chr(0b110100) + '\060', 0o10), ehT0Px3KOsy9('\060' + chr(0b1101011 + 0o4) + '\061' + chr(755 - 703) + chr(0b1010 + 0o46), 8), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b10110 + 0o34) + '\063' + chr(48), 57985 - 57977), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\063' + chr(1891 - 1842) + chr(1485 - 1431), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(703 - 652), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(1331 - 1281) + chr(0b101111 + 0o1), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x37' + chr(0b10101 + 0o33), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110001) + chr(1051 - 998) + chr(0b100100 + 0o17), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x31' + '\x34' + chr(51), 8), ehT0Px3KOsy9(chr(2002 - 1954) + '\157' + chr(49) + chr(0b10110 + 0o41) + chr(48), 57230 - 57222), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110111) + chr(1229 - 1178), 0o10), ehT0Px3KOsy9(chr(1831 - 1783) + '\x6f' + '\x31' + chr(50) + chr(0b110111), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(1056 - 945) + chr(0b1110 + 0o45) + chr(1671 - 1620) + chr(2213 - 2161), 46140 - 46132), ehT0Px3KOsy9('\060' + '\x6f' + chr(1531 - 1476) + chr(0b110011), 8), ehT0Px3KOsy9(chr(0b1000 + 0o50) + chr(0b1101111) + chr(0b11011 + 0o27) + '\x37' + chr(0b110111), 0o10), ehT0Px3KOsy9(chr(1230 - 1182) + '\x6f' + chr(50) + chr(53) + '\x36', 20808 - 20800), ehT0Px3KOsy9(chr(0b10010 + 0o36) + chr(111) + chr(0b110011) + chr(1432 - 1382) + chr(50), 36119 - 36111), ehT0Px3KOsy9(chr(0b11111 + 0o21) + chr(0b1101111) + '\061' + chr(327 - 278) + chr(53), 29258 - 29250), ehT0Px3KOsy9(chr(0b110000) + chr(150 - 39) + chr(51) + chr(0b11010 + 0o34) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(2190 - 2142) + '\x6f' + chr(49) + chr(638 - 583) + chr(55), 58604 - 58596), ehT0Px3KOsy9('\060' + '\157' + chr(0b110010) + chr(0b110110) + chr(0b1000 + 0o50), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + chr(1142 - 1031) + chr(1739 - 1686) + '\060', 22904 - 22896)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'J'), chr(100) + chr(0b100 + 0o141) + chr(287 - 188) + chr(111) + '\144' + '\145')(chr(11505 - 11388) + chr(0b1110100) + '\x66' + '\x2d' + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def p1ml1ttknzuh(oVre8I6UXc3b, QmmgWUB13VCJ, KhzrMpzISODo=ehT0Px3KOsy9('\060' + chr(111) + '\060', 54415 - 54407)):
KhzrMpzISODo = LYHx5VlCvmk_(KhzrMpzISODo, xafqLlk3kkUe(SXOLrMavuUCe(b'\r\xfd\x90\x8b\x93Z4'), chr(3422 - 3322) + chr(101) + chr(2517 - 2418) + '\157' + chr(0b1100100) + chr(0b1111 + 0o126))(chr(3521 - 3404) + chr(116) + '\x66' + chr(45) + chr(0b111000)))
H6Aqpf9qhdEs = CBSVoRj_kvTn(oVre8I6UXc3b.categories, ordered=QmmgWUB13VCJ)
re0VVGAVKu27 = oVre8I6UXc3b if KhzrMpzISODo else oVre8I6UXc3b.igThHS4jwVsa()
re0VVGAVKu27.z2oVGDR5m1eh = H6Aqpf9qhdEs
if not KhzrMpzISODo:
return re0VVGAVKu27
|
pandas-dev/pandas
|
pandas/core/arrays/categorical.py
|
Categorical.as_ordered
|
def as_ordered(self, inplace=False):
"""
Set the Categorical to be ordered.
Parameters
----------
inplace : bool, default False
Whether or not to set the ordered attribute in-place or return
a copy of this categorical with ordered set to True.
"""
inplace = validate_bool_kwarg(inplace, 'inplace')
return self.set_ordered(True, inplace=inplace)
|
python
|
def as_ordered(self, inplace=False):
"""
Set the Categorical to be ordered.
Parameters
----------
inplace : bool, default False
Whether or not to set the ordered attribute in-place or return
a copy of this categorical with ordered set to True.
"""
inplace = validate_bool_kwarg(inplace, 'inplace')
return self.set_ordered(True, inplace=inplace)
|
[
"def",
"as_ordered",
"(",
"self",
",",
"inplace",
"=",
"False",
")",
":",
"inplace",
"=",
"validate_bool_kwarg",
"(",
"inplace",
",",
"'inplace'",
")",
"return",
"self",
".",
"set_ordered",
"(",
"True",
",",
"inplace",
"=",
"inplace",
")"
] |
Set the Categorical to be ordered.
Parameters
----------
inplace : bool, default False
Whether or not to set the ordered attribute in-place or return
a copy of this categorical with ordered set to True.
|
[
"Set",
"the",
"Categorical",
"to",
"be",
"ordered",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/arrays/categorical.py#L750-L761
|
train
|
Set the Categorical to be ordered.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(48) + chr(111) + '\x37' + chr(0b110001), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x31' + chr(1105 - 1057) + chr(209 - 158), 0o10), ehT0Px3KOsy9(chr(1334 - 1286) + chr(0b10100 + 0o133) + chr(0b110010) + chr(0b101100 + 0o12), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(50) + '\066' + chr(0b1110 + 0o51), ord("\x08")), ehT0Px3KOsy9(chr(1404 - 1356) + '\157' + '\061' + chr(1496 - 1444) + chr(0b1 + 0o57), ord("\x08")), ehT0Px3KOsy9(chr(1250 - 1202) + chr(111) + chr(291 - 242) + chr(1129 - 1080) + chr(0b101110 + 0o7), 64208 - 64200), ehT0Px3KOsy9(chr(0b101010 + 0o6) + chr(3250 - 3139) + chr(0b110011) + chr(51) + '\067', ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(51) + '\x34' + chr(0b101100 + 0o7), ord("\x08")), ehT0Px3KOsy9(chr(0b11011 + 0o25) + chr(0b1101111) + '\x33' + '\060' + chr(0b110100), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(655 - 605) + chr(1705 - 1657) + '\x32', 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\063' + chr(49) + chr(0b11100 + 0o24), 0b1000), ehT0Px3KOsy9('\x30' + chr(7818 - 7707) + chr(50) + chr(984 - 936) + chr(2030 - 1979), 40188 - 40180), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110000), 0o10), ehT0Px3KOsy9(chr(0b1101 + 0o43) + chr(111) + '\061' + chr(1173 - 1123) + chr(1811 - 1759), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1000010 + 0o55) + chr(0b110001) + chr(806 - 752) + chr(50), 10247 - 10239), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110001) + chr(0b110001) + chr(52), 18785 - 18777), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110001 + 0o6) + '\062', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(1003 - 951) + chr(1788 - 1734), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(50) + chr(2080 - 2025) + '\x33', 20877 - 20869), ehT0Px3KOsy9(chr(0b110000) + chr(0b1010010 + 0o35) + chr(1248 - 1193) + '\x35', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b10111 + 0o130) + chr(0b110001) + chr(1060 - 1006) + '\x32', 8), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(145 - 92) + chr(0b1100 + 0o50), 10022 - 10014), ehT0Px3KOsy9(chr(0b111 + 0o51) + chr(111) + '\x33' + chr(0b100010 + 0o20) + chr(0b10001 + 0o46), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(0b110001 + 0o4) + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(51) + chr(0b110011) + chr(177 - 124), ord("\x08")), ehT0Px3KOsy9(chr(1477 - 1429) + chr(111) + chr(0b11001 + 0o27), 8), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b100100 + 0o15) + chr(0b1010 + 0o54) + '\x31', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1010100 + 0o33) + '\067', 8275 - 8267), ehT0Px3KOsy9(chr(48) + chr(0b100100 + 0o113) + chr(243 - 191) + chr(54), 8), ehT0Px3KOsy9(chr(0b110000) + chr(6757 - 6646) + chr(371 - 321) + '\060' + '\x37', 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110000 + 0o1) + '\067' + chr(0b110111), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b11111 + 0o24) + '\064' + chr(0b11011 + 0o31), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x32' + chr(0b110101) + '\x35', 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + '\x33' + chr(0b110001) + chr(996 - 944), 43991 - 43983), ehT0Px3KOsy9(chr(0b11111 + 0o21) + chr(111) + chr(0b11101 + 0o25) + '\067' + chr(0b110010), 0o10), ehT0Px3KOsy9('\060' + chr(11135 - 11024) + chr(0b100000 + 0o21) + chr(0b110011) + '\063', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b101 + 0o55) + chr(50) + '\x36', 57238 - 57230), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\063' + chr(52) + chr(599 - 547), 8), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110000), 8), ehT0Px3KOsy9(chr(207 - 159) + chr(111) + '\063' + chr(55) + chr(0b110100), 37853 - 37845)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(53) + chr(2124 - 2076), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x17'), '\144' + chr(2401 - 2300) + chr(0b11110 + 0o105) + '\157' + '\x64' + chr(0b1100101))(chr(0b1110101) + chr(0b1110 + 0o146) + chr(950 - 848) + chr(45) + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def kBRXWRM8mmjl(oVre8I6UXc3b, KhzrMpzISODo=ehT0Px3KOsy9(chr(0b110000) + chr(0b11110 + 0o121) + chr(0b101011 + 0o5), 8)):
KhzrMpzISODo = LYHx5VlCvmk_(KhzrMpzISODo, xafqLlk3kkUe(SXOLrMavuUCe(b'P-f\xdb\x01.\xba'), '\x64' + chr(101) + '\x63' + chr(0b1011000 + 0o27) + chr(5486 - 5386) + chr(101))(chr(0b10100 + 0o141) + chr(9742 - 9626) + chr(0b1100110) + chr(1225 - 1180) + '\x38'))
return xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'J&b\xe8\x0f?\xbb\x86\xb6\xe7\xac'), '\x64' + chr(0b1100101) + chr(0b11101 + 0o106) + chr(0b111111 + 0o60) + chr(100) + chr(0b1000 + 0o135))(chr(0b110111 + 0o76) + chr(116) + '\146' + '\x2d' + '\070'))(ehT0Px3KOsy9('\x30' + '\157' + chr(1656 - 1607), 0o10), inplace=KhzrMpzISODo)
|
pandas-dev/pandas
|
pandas/core/arrays/categorical.py
|
Categorical.as_unordered
|
def as_unordered(self, inplace=False):
"""
Set the Categorical to be unordered.
Parameters
----------
inplace : bool, default False
Whether or not to set the ordered attribute in-place or return
a copy of this categorical with ordered set to False.
"""
inplace = validate_bool_kwarg(inplace, 'inplace')
return self.set_ordered(False, inplace=inplace)
|
python
|
def as_unordered(self, inplace=False):
"""
Set the Categorical to be unordered.
Parameters
----------
inplace : bool, default False
Whether or not to set the ordered attribute in-place or return
a copy of this categorical with ordered set to False.
"""
inplace = validate_bool_kwarg(inplace, 'inplace')
return self.set_ordered(False, inplace=inplace)
|
[
"def",
"as_unordered",
"(",
"self",
",",
"inplace",
"=",
"False",
")",
":",
"inplace",
"=",
"validate_bool_kwarg",
"(",
"inplace",
",",
"'inplace'",
")",
"return",
"self",
".",
"set_ordered",
"(",
"False",
",",
"inplace",
"=",
"inplace",
")"
] |
Set the Categorical to be unordered.
Parameters
----------
inplace : bool, default False
Whether or not to set the ordered attribute in-place or return
a copy of this categorical with ordered set to False.
|
[
"Set",
"the",
"Categorical",
"to",
"be",
"unordered",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/arrays/categorical.py#L763-L774
|
train
|
Set the Categorical to be unordered.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b100001 + 0o17) + chr(0b1000011 + 0o54) + chr(0b100110 + 0o13) + chr(0b1 + 0o57) + chr(55), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + '\066' + '\x34', 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b11010 + 0o30) + chr(0b110111) + chr(0b110000), 0b1000), ehT0Px3KOsy9('\060' + '\157' + '\x33' + chr(48) + chr(50), 0o10), ehT0Px3KOsy9(chr(0b10001 + 0o37) + chr(0b110000 + 0o77) + '\x31' + chr(0b11001 + 0o30), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + '\062' + chr(1935 - 1881), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(50) + chr(0b101000 + 0o13) + '\x30', 22186 - 22178), ehT0Px3KOsy9(chr(48) + chr(0b1001011 + 0o44) + chr(0b110001) + chr(0b110101) + chr(0b110111), 45856 - 45848), ehT0Px3KOsy9('\060' + chr(0b1000001 + 0o56) + '\066' + chr(83 - 35), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x33' + chr(53) + '\x33', 0o10), ehT0Px3KOsy9(chr(990 - 942) + chr(0b11110 + 0o121) + chr(0b110001) + chr(0b110110) + '\x33', 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + '\x37' + '\063', 0o10), ehT0Px3KOsy9('\x30' + chr(111) + chr(2041 - 1988) + '\063', 39139 - 39131), ehT0Px3KOsy9('\x30' + '\x6f' + chr(51) + '\062' + chr(0b1111 + 0o42), 3617 - 3609), ehT0Px3KOsy9('\x30' + chr(2174 - 2063) + chr(2462 - 2411) + chr(0b110100) + chr(635 - 584), 0b1000), ehT0Px3KOsy9(chr(0b11001 + 0o27) + chr(111) + chr(49) + chr(0b101100 + 0o7) + chr(0b10101 + 0o35), 59933 - 59925), ehT0Px3KOsy9(chr(0b1001 + 0o47) + '\x6f' + '\063' + chr(0b100110 + 0o16) + chr(0b110111), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b110111 + 0o70) + '\x31', 0b1000), ehT0Px3KOsy9(chr(0b101000 + 0o10) + chr(0b1100 + 0o143) + '\062' + '\x31' + chr(0b1000 + 0o57), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x36' + chr(55), 0b1000), ehT0Px3KOsy9(chr(0b0 + 0o60) + chr(0b1101111) + chr(1175 - 1124) + chr(0b100000 + 0o20) + chr(361 - 313), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b100000 + 0o22), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(10350 - 10239) + chr(988 - 938) + chr(0b110001) + '\062', 829 - 821), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\061', 8), ehT0Px3KOsy9(chr(344 - 296) + chr(111) + chr(0b110001) + chr(0b100110 + 0o16) + '\x32', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b101011 + 0o10) + chr(48) + chr(327 - 274), 36600 - 36592), ehT0Px3KOsy9(chr(0b110000) + chr(0b1111 + 0o140) + chr(0b110011) + chr(365 - 311) + '\x35', 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\062' + chr(1545 - 1491), 8), ehT0Px3KOsy9(chr(48) + chr(0b1011110 + 0o21) + '\x34' + chr(2192 - 2143), ord("\x08")), ehT0Px3KOsy9(chr(2274 - 2226) + '\x6f' + '\065' + chr(0b10001 + 0o44), 0b1000), ehT0Px3KOsy9(chr(0b110000 + 0o0) + chr(111) + chr(0b110010) + '\x35' + chr(48), ord("\x08")), ehT0Px3KOsy9(chr(680 - 632) + chr(0b1100100 + 0o13) + '\062' + '\066' + chr(0b110011), 0o10), ehT0Px3KOsy9(chr(48) + chr(5171 - 5060) + '\x33' + chr(1285 - 1237) + chr(0b110110), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + '\062' + chr(0b110011) + chr(1088 - 1037), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x32' + '\066', 8), ehT0Px3KOsy9('\060' + chr(0b1011000 + 0o27) + '\061' + chr(0b1110 + 0o51) + '\x32', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110011) + chr(1751 - 1702) + '\064', ord("\x08")), ehT0Px3KOsy9(chr(1706 - 1658) + chr(7633 - 7522) + '\066' + '\067', 8), ehT0Px3KOsy9('\x30' + chr(111) + '\x32' + '\063' + chr(49), 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(0b110011) + chr(0b110111) + '\x36', 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110101) + '\060', 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'i'), chr(100) + chr(0b1100101) + chr(0b1100011) + '\157' + chr(100) + chr(101))('\165' + chr(116) + chr(102) + '\x2d' + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def aRDmNSIrUzoV(oVre8I6UXc3b, KhzrMpzISODo=ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(48), 0b1000)):
KhzrMpzISODo = LYHx5VlCvmk_(KhzrMpzISODo, xafqLlk3kkUe(SXOLrMavuUCe(b'.Z\xc8\xaehu\xfd'), '\144' + chr(0b1100101) + '\x63' + '\157' + chr(7551 - 7451) + '\x65')(chr(0b1110101) + chr(0b110 + 0o156) + '\146' + '\055' + chr(0b10 + 0o66)))
return xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'4Q\xcc\x9dfd\xfc\nB\x8e\x17'), chr(0b1100100) + chr(1591 - 1490) + chr(0b1100011) + '\x6f' + chr(100) + chr(0b1100101))('\x75' + chr(0b1110100) + chr(6581 - 6479) + chr(45) + '\x38'))(ehT0Px3KOsy9(chr(1906 - 1858) + chr(111) + chr(315 - 267), 8), inplace=KhzrMpzISODo)
|
pandas-dev/pandas
|
pandas/core/arrays/categorical.py
|
Categorical.set_categories
|
def set_categories(self, new_categories, ordered=None, rename=False,
inplace=False):
"""
Set the categories to the specified new_categories.
`new_categories` can include new categories (which will result in
unused categories) or remove old categories (which results in values
set to NaN). If `rename==True`, the categories will simple be renamed
(less or more items than in old categories will result in values set to
NaN or in unused categories respectively).
This method can be used to perform more than one action of adding,
removing, and reordering simultaneously and is therefore faster than
performing the individual steps via the more specialised methods.
On the other hand this methods does not do checks (e.g., whether the
old categories are included in the new categories on a reorder), which
can result in surprising changes, for example when using special string
dtypes on python3, which does not considers a S1 string equal to a
single char python string.
Parameters
----------
new_categories : Index-like
The categories in new order.
ordered : bool, default False
Whether or not the categorical is treated as a ordered categorical.
If not given, do not change the ordered information.
rename : bool, default False
Whether or not the new_categories should be considered as a rename
of the old categories or as reordered categories.
inplace : bool, default False
Whether or not to reorder the categories in-place or return a copy
of this categorical with reordered categories.
Returns
-------
Categorical with reordered categories or None if inplace.
Raises
------
ValueError
If new_categories does not validate as categories
See Also
--------
rename_categories
reorder_categories
add_categories
remove_categories
remove_unused_categories
"""
inplace = validate_bool_kwarg(inplace, 'inplace')
if ordered is None:
ordered = self.dtype.ordered
new_dtype = CategoricalDtype(new_categories, ordered=ordered)
cat = self if inplace else self.copy()
if rename:
if (cat.dtype.categories is not None and
len(new_dtype.categories) < len(cat.dtype.categories)):
# remove all _codes which are larger and set to -1/NaN
cat._codes[cat._codes >= len(new_dtype.categories)] = -1
else:
codes = _recode_for_categories(cat.codes, cat.categories,
new_dtype.categories)
cat._codes = codes
cat._dtype = new_dtype
if not inplace:
return cat
|
python
|
def set_categories(self, new_categories, ordered=None, rename=False,
inplace=False):
"""
Set the categories to the specified new_categories.
`new_categories` can include new categories (which will result in
unused categories) or remove old categories (which results in values
set to NaN). If `rename==True`, the categories will simple be renamed
(less or more items than in old categories will result in values set to
NaN or in unused categories respectively).
This method can be used to perform more than one action of adding,
removing, and reordering simultaneously and is therefore faster than
performing the individual steps via the more specialised methods.
On the other hand this methods does not do checks (e.g., whether the
old categories are included in the new categories on a reorder), which
can result in surprising changes, for example when using special string
dtypes on python3, which does not considers a S1 string equal to a
single char python string.
Parameters
----------
new_categories : Index-like
The categories in new order.
ordered : bool, default False
Whether or not the categorical is treated as a ordered categorical.
If not given, do not change the ordered information.
rename : bool, default False
Whether or not the new_categories should be considered as a rename
of the old categories or as reordered categories.
inplace : bool, default False
Whether or not to reorder the categories in-place or return a copy
of this categorical with reordered categories.
Returns
-------
Categorical with reordered categories or None if inplace.
Raises
------
ValueError
If new_categories does not validate as categories
See Also
--------
rename_categories
reorder_categories
add_categories
remove_categories
remove_unused_categories
"""
inplace = validate_bool_kwarg(inplace, 'inplace')
if ordered is None:
ordered = self.dtype.ordered
new_dtype = CategoricalDtype(new_categories, ordered=ordered)
cat = self if inplace else self.copy()
if rename:
if (cat.dtype.categories is not None and
len(new_dtype.categories) < len(cat.dtype.categories)):
# remove all _codes which are larger and set to -1/NaN
cat._codes[cat._codes >= len(new_dtype.categories)] = -1
else:
codes = _recode_for_categories(cat.codes, cat.categories,
new_dtype.categories)
cat._codes = codes
cat._dtype = new_dtype
if not inplace:
return cat
|
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] |
Set the categories to the specified new_categories.
`new_categories` can include new categories (which will result in
unused categories) or remove old categories (which results in values
set to NaN). If `rename==True`, the categories will simple be renamed
(less or more items than in old categories will result in values set to
NaN or in unused categories respectively).
This method can be used to perform more than one action of adding,
removing, and reordering simultaneously and is therefore faster than
performing the individual steps via the more specialised methods.
On the other hand this methods does not do checks (e.g., whether the
old categories are included in the new categories on a reorder), which
can result in surprising changes, for example when using special string
dtypes on python3, which does not considers a S1 string equal to a
single char python string.
Parameters
----------
new_categories : Index-like
The categories in new order.
ordered : bool, default False
Whether or not the categorical is treated as a ordered categorical.
If not given, do not change the ordered information.
rename : bool, default False
Whether or not the new_categories should be considered as a rename
of the old categories or as reordered categories.
inplace : bool, default False
Whether or not to reorder the categories in-place or return a copy
of this categorical with reordered categories.
Returns
-------
Categorical with reordered categories or None if inplace.
Raises
------
ValueError
If new_categories does not validate as categories
See Also
--------
rename_categories
reorder_categories
add_categories
remove_categories
remove_unused_categories
|
[
"Set",
"the",
"categories",
"to",
"the",
"specified",
"new_categories",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/arrays/categorical.py#L776-L846
|
train
|
Set the categories of the current entry.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(1223 - 1174) + chr(54) + '\x34', 0b1000), ehT0Px3KOsy9(chr(0b11101 + 0o23) + '\157' + chr(1576 - 1526) + chr(51), 0o10), ehT0Px3KOsy9('\060' + chr(0b1010011 + 0o34) + chr(53) + chr(0b100010 + 0o25), 37298 - 37290), ehT0Px3KOsy9('\060' + '\157' + chr(0b101111 + 0o2) + '\067' + '\x30', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(2586 - 2534) + '\064', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(1272 - 1161) + chr(0b11000 + 0o31) + '\065' + '\x36', 44020 - 44012), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\063' + chr(0b110010) + chr(0b110101), 58283 - 58275), ehT0Px3KOsy9(chr(0b11 + 0o55) + chr(681 - 570) + chr(0b110101) + chr(2534 - 2481), 0o10), ehT0Px3KOsy9(chr(0b11101 + 0o23) + '\157' + '\x32' + chr(55), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\063' + chr(0b110010) + '\066', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101101 + 0o2) + '\063' + '\066' + chr(50), 57560 - 57552), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(632 - 583) + chr(0b10001 + 0o37) + '\063', 0b1000), ehT0Px3KOsy9(chr(0b10 + 0o56) + '\x6f' + '\x33' + chr(50) + chr(48), 0o10), ehT0Px3KOsy9('\x30' + '\157' + '\062' + chr(0b110101) + '\065', 3582 - 3574), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110111), 48324 - 48316), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\061' + chr(2803 - 2748) + chr(474 - 422), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1000111 + 0o50) + chr(49) + '\067' + chr(52), 8), ehT0Px3KOsy9(chr(1068 - 1020) + '\157' + chr(1347 - 1297) + chr(52) + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(1377 - 1329) + chr(111) + '\061' + chr(294 - 242) + chr(0b110100), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b11101 + 0o24) + '\064' + '\x32', 7449 - 7441), ehT0Px3KOsy9('\060' + '\x6f' + '\x32' + chr(52), 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(0b100000 + 0o22) + chr(1620 - 1570) + chr(0b110100), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110010) + chr(1979 - 1925) + '\063', 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b10101 + 0o34) + chr(48) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(1529 - 1418) + '\061', ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(1733 - 1679) + chr(0b110011), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x33' + chr(1603 - 1552) + '\x33', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110001 + 0o0) + '\067' + '\x32', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\063' + chr(52) + '\064', 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110001) + chr(2002 - 1949) + chr(693 - 640), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b100011 + 0o20) + chr(51) + '\x34', ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(332 - 281) + chr(0b110100) + chr(0b11011 + 0o26), 63424 - 63416), ehT0Px3KOsy9('\060' + '\157' + '\061' + '\x35' + '\064', 37009 - 37001), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110011) + '\x31' + '\062', 0b1000), ehT0Px3KOsy9(chr(0b10100 + 0o34) + chr(0b1101111) + chr(51) + chr(53) + chr(0b110011), 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(49) + chr(1699 - 1649) + chr(49), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b1100 + 0o47) + '\064' + chr(0b0 + 0o63), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + '\061' + chr(0b11110 + 0o26) + chr(697 - 646), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b11011 + 0o27) + '\x30', 0b1000), ehT0Px3KOsy9(chr(0b11110 + 0o22) + '\x6f' + '\063' + chr(52) + chr(0b110101), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + '\157' + chr(0b110000 + 0o5) + '\060', 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'Z'), chr(100) + chr(0b101000 + 0o75) + chr(6176 - 6077) + '\x6f' + chr(100) + '\x65')(chr(8207 - 8090) + '\x74' + '\146' + chr(0b1010 + 0o43) + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def KzgqdkB_rZuv(oVre8I6UXc3b, QVK8u7RnAnpO, TillFngeGqII=None, WOgai73LTEHG=ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\060', 0o10), KhzrMpzISODo=ehT0Px3KOsy9(chr(48) + chr(3841 - 3730) + chr(1387 - 1339), 8)):
KhzrMpzISODo = LYHx5VlCvmk_(KhzrMpzISODo, xafqLlk3kkUe(SXOLrMavuUCe(b'\x1d}_\x14E\r\xb0'), chr(0b1100100) + chr(0b1100101) + chr(99) + chr(7674 - 7563) + chr(0b111001 + 0o53) + chr(101))('\x75' + chr(9697 - 9581) + chr(0b1100110) + chr(0b101101) + '\x38'))
if TillFngeGqII is None:
TillFngeGqII = oVre8I6UXc3b.dtype.ordered
H6Aqpf9qhdEs = CBSVoRj_kvTn(QVK8u7RnAnpO, ordered=TillFngeGqII)
re0VVGAVKu27 = oVre8I6UXc3b if KhzrMpzISODo else oVre8I6UXc3b.igThHS4jwVsa()
if WOgai73LTEHG:
if xafqLlk3kkUe(re0VVGAVKu27.dtype, xafqLlk3kkUe(SXOLrMavuUCe(b'\x17r[\x1dC\x01\xa7Dr\xa5'), '\144' + chr(101) + chr(0b1100011) + '\157' + '\x64' + chr(3052 - 2951))(chr(0b1110101) + chr(116) + chr(0b1 + 0o145) + '\055' + chr(1539 - 1483))) is not None and c2A0yzQpDQB3(xafqLlk3kkUe(H6Aqpf9qhdEs, xafqLlk3kkUe(SXOLrMavuUCe(b'\x17r[\x1dC\x01\xa7Dr\xa5'), '\144' + chr(6248 - 6147) + chr(0b101001 + 0o72) + chr(111) + chr(0b1100100) + chr(0b1100010 + 0o3))(chr(2451 - 2334) + chr(530 - 414) + chr(287 - 185) + chr(45) + chr(2738 - 2682)))) < c2A0yzQpDQB3(xafqLlk3kkUe(re0VVGAVKu27.dtype, xafqLlk3kkUe(SXOLrMavuUCe(b'\x17r[\x1dC\x01\xa7Dr\xa5'), '\x64' + chr(0b1100101) + chr(0b1100011) + '\157' + '\x64' + chr(0b1100101))(chr(117) + '\164' + chr(3441 - 3339) + chr(45) + chr(0b1010 + 0o56)))):
re0VVGAVKu27.d5BDZJl_zDsu[re0VVGAVKu27.d5BDZJl_zDsu >= c2A0yzQpDQB3(H6Aqpf9qhdEs.mZZDAT49UzAb)] = -ehT0Px3KOsy9(chr(0b11011 + 0o25) + '\x6f' + '\061', 8)
else:
AoWJEgIAbHh_ = V3m1SlhRYSW0(re0VVGAVKu27.codes, re0VVGAVKu27.mZZDAT49UzAb, H6Aqpf9qhdEs.mZZDAT49UzAb)
re0VVGAVKu27.d5BDZJl_zDsu = AoWJEgIAbHh_
re0VVGAVKu27.z2oVGDR5m1eh = H6Aqpf9qhdEs
if not KhzrMpzISODo:
return re0VVGAVKu27
|
pandas-dev/pandas
|
pandas/core/arrays/categorical.py
|
Categorical.rename_categories
|
def rename_categories(self, new_categories, inplace=False):
"""
Rename categories.
Parameters
----------
new_categories : list-like, dict-like or callable
* list-like: all items must be unique and the number of items in
the new categories must match the existing number of categories.
* dict-like: specifies a mapping from
old categories to new. Categories not contained in the mapping
are passed through and extra categories in the mapping are
ignored.
.. versionadded:: 0.21.0
* callable : a callable that is called on all items in the old
categories and whose return values comprise the new categories.
.. versionadded:: 0.23.0
.. warning::
Currently, Series are considered list like. In a future version
of pandas they'll be considered dict-like.
inplace : bool, default False
Whether or not to rename the categories inplace or return a copy of
this categorical with renamed categories.
Returns
-------
cat : Categorical or None
With ``inplace=False``, the new categorical is returned.
With ``inplace=True``, there is no return value.
Raises
------
ValueError
If new categories are list-like and do not have the same number of
items than the current categories or do not validate as categories
See Also
--------
reorder_categories
add_categories
remove_categories
remove_unused_categories
set_categories
Examples
--------
>>> c = pd.Categorical(['a', 'a', 'b'])
>>> c.rename_categories([0, 1])
[0, 0, 1]
Categories (2, int64): [0, 1]
For dict-like ``new_categories``, extra keys are ignored and
categories not in the dictionary are passed through
>>> c.rename_categories({'a': 'A', 'c': 'C'})
[A, A, b]
Categories (2, object): [A, b]
You may also provide a callable to create the new categories
>>> c.rename_categories(lambda x: x.upper())
[A, A, B]
Categories (2, object): [A, B]
"""
inplace = validate_bool_kwarg(inplace, 'inplace')
cat = self if inplace else self.copy()
if isinstance(new_categories, ABCSeries):
msg = ("Treating Series 'new_categories' as a list-like and using "
"the values. In a future version, 'rename_categories' will "
"treat Series like a dictionary.\n"
"For dict-like, use 'new_categories.to_dict()'\n"
"For list-like, use 'new_categories.values'.")
warn(msg, FutureWarning, stacklevel=2)
new_categories = list(new_categories)
if is_dict_like(new_categories):
cat.categories = [new_categories.get(item, item)
for item in cat.categories]
elif callable(new_categories):
cat.categories = [new_categories(item) for item in cat.categories]
else:
cat.categories = new_categories
if not inplace:
return cat
|
python
|
def rename_categories(self, new_categories, inplace=False):
"""
Rename categories.
Parameters
----------
new_categories : list-like, dict-like or callable
* list-like: all items must be unique and the number of items in
the new categories must match the existing number of categories.
* dict-like: specifies a mapping from
old categories to new. Categories not contained in the mapping
are passed through and extra categories in the mapping are
ignored.
.. versionadded:: 0.21.0
* callable : a callable that is called on all items in the old
categories and whose return values comprise the new categories.
.. versionadded:: 0.23.0
.. warning::
Currently, Series are considered list like. In a future version
of pandas they'll be considered dict-like.
inplace : bool, default False
Whether or not to rename the categories inplace or return a copy of
this categorical with renamed categories.
Returns
-------
cat : Categorical or None
With ``inplace=False``, the new categorical is returned.
With ``inplace=True``, there is no return value.
Raises
------
ValueError
If new categories are list-like and do not have the same number of
items than the current categories or do not validate as categories
See Also
--------
reorder_categories
add_categories
remove_categories
remove_unused_categories
set_categories
Examples
--------
>>> c = pd.Categorical(['a', 'a', 'b'])
>>> c.rename_categories([0, 1])
[0, 0, 1]
Categories (2, int64): [0, 1]
For dict-like ``new_categories``, extra keys are ignored and
categories not in the dictionary are passed through
>>> c.rename_categories({'a': 'A', 'c': 'C'})
[A, A, b]
Categories (2, object): [A, b]
You may also provide a callable to create the new categories
>>> c.rename_categories(lambda x: x.upper())
[A, A, B]
Categories (2, object): [A, B]
"""
inplace = validate_bool_kwarg(inplace, 'inplace')
cat = self if inplace else self.copy()
if isinstance(new_categories, ABCSeries):
msg = ("Treating Series 'new_categories' as a list-like and using "
"the values. In a future version, 'rename_categories' will "
"treat Series like a dictionary.\n"
"For dict-like, use 'new_categories.to_dict()'\n"
"For list-like, use 'new_categories.values'.")
warn(msg, FutureWarning, stacklevel=2)
new_categories = list(new_categories)
if is_dict_like(new_categories):
cat.categories = [new_categories.get(item, item)
for item in cat.categories]
elif callable(new_categories):
cat.categories = [new_categories(item) for item in cat.categories]
else:
cat.categories = new_categories
if not inplace:
return cat
|
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"[",
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"new_categories",
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] |
Rename categories.
Parameters
----------
new_categories : list-like, dict-like or callable
* list-like: all items must be unique and the number of items in
the new categories must match the existing number of categories.
* dict-like: specifies a mapping from
old categories to new. Categories not contained in the mapping
are passed through and extra categories in the mapping are
ignored.
.. versionadded:: 0.21.0
* callable : a callable that is called on all items in the old
categories and whose return values comprise the new categories.
.. versionadded:: 0.23.0
.. warning::
Currently, Series are considered list like. In a future version
of pandas they'll be considered dict-like.
inplace : bool, default False
Whether or not to rename the categories inplace or return a copy of
this categorical with renamed categories.
Returns
-------
cat : Categorical or None
With ``inplace=False``, the new categorical is returned.
With ``inplace=True``, there is no return value.
Raises
------
ValueError
If new categories are list-like and do not have the same number of
items than the current categories or do not validate as categories
See Also
--------
reorder_categories
add_categories
remove_categories
remove_unused_categories
set_categories
Examples
--------
>>> c = pd.Categorical(['a', 'a', 'b'])
>>> c.rename_categories([0, 1])
[0, 0, 1]
Categories (2, int64): [0, 1]
For dict-like ``new_categories``, extra keys are ignored and
categories not in the dictionary are passed through
>>> c.rename_categories({'a': 'A', 'c': 'C'})
[A, A, b]
Categories (2, object): [A, b]
You may also provide a callable to create the new categories
>>> c.rename_categories(lambda x: x.upper())
[A, A, B]
Categories (2, object): [A, B]
|
[
"Rename",
"categories",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/arrays/categorical.py#L848-L940
|
train
|
Returns a new categorical with renamed categories.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(48) + '\157' + '\063' + '\x31' + '\x31', 0o10), ehT0Px3KOsy9(chr(0b111 + 0o51) + chr(6075 - 5964) + '\063' + chr(0b110101), 19700 - 19692), ehT0Px3KOsy9('\060' + '\157' + chr(1375 - 1322) + chr(0b110110), 62347 - 62339), ehT0Px3KOsy9('\x30' + '\x6f' + '\063' + chr(48) + '\063', 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(422 - 373) + '\064' + '\067', 63214 - 63206), ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(0b111 + 0o150) + '\x31' + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(6225 - 6114) + chr(54) + '\065', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(49) + chr(0b10000 + 0o43) + chr(0b110110), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(51) + chr(51) + chr(0b110010 + 0o2), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(49) + '\x30' + chr(54), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b100011 + 0o16) + chr(0b110101), 0b1000), ehT0Px3KOsy9(chr(1659 - 1611) + '\157' + chr(1459 - 1404) + chr(50), 0o10), ehT0Px3KOsy9(chr(0b11011 + 0o25) + chr(0b1101111) + chr(0b101111 + 0o2) + '\x32' + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1001110 + 0o41) + '\x33' + chr(54) + '\066', 37242 - 37234), ehT0Px3KOsy9(chr(0b11010 + 0o26) + '\157' + chr(54) + chr(53), 8), ehT0Px3KOsy9('\060' + '\x6f' + '\061' + '\065', 8), ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(0b1101111) + chr(0b100010 + 0o25) + chr(0b10011 + 0o35), 0b1000), ehT0Px3KOsy9(chr(461 - 413) + chr(0b1101111) + chr(972 - 921) + chr(52) + '\x35', 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(2211 - 2160) + chr(51) + chr(48), 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(0b1000 + 0o53) + chr(0b110111), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(11887 - 11776) + chr(717 - 667) + chr(54) + '\x31', 18456 - 18448), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\062' + chr(53) + '\x36', 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110001) + '\067', 8), ehT0Px3KOsy9(chr(0b10011 + 0o35) + chr(5591 - 5480) + chr(0b1011 + 0o46) + chr(0b110000) + '\x32', 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(96 - 47) + '\066' + chr(51), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1100 + 0o143) + chr(0b101010 + 0o10) + chr(53) + chr(478 - 426), 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b10000 + 0o43) + chr(1106 - 1053) + '\x33', 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(428 - 379) + chr(431 - 380) + chr(0b1101 + 0o52), ord("\x08")), ehT0Px3KOsy9(chr(1212 - 1164) + chr(111) + chr(51) + '\x30' + chr(0b110000), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b11101 + 0o122) + chr(1051 - 1000), ord("\x08")), ehT0Px3KOsy9(chr(0b101 + 0o53) + chr(0b1101111) + '\064' + chr(363 - 314), 0b1000), ehT0Px3KOsy9('\x30' + chr(2077 - 1966) + '\x34' + chr(2100 - 2046), 0o10), ehT0Px3KOsy9(chr(0b1110 + 0o42) + '\x6f' + chr(0b100100 + 0o23) + chr(1706 - 1651), 33354 - 33346), ehT0Px3KOsy9('\060' + '\x6f' + chr(2274 - 2219), 48930 - 48922), ehT0Px3KOsy9(chr(2148 - 2100) + chr(111) + '\061' + chr(1286 - 1231), 8), ehT0Px3KOsy9('\060' + chr(111) + chr(49) + chr(564 - 514) + chr(0b110110), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x34' + chr(251 - 196), 0o10), ehT0Px3KOsy9(chr(1789 - 1741) + chr(0b1101111) + chr(0b10011 + 0o40) + chr(477 - 427) + chr(0b110110), 22879 - 22871), ehT0Px3KOsy9(chr(48) + chr(0b1010010 + 0o35) + '\061' + chr(50) + chr(0b1010 + 0o47), ord("\x08"))][WVxHKyX45z_L % ehT0Px3KOsy9(chr(236 - 188) + chr(0b1101111) + chr(0b110101) + chr(48), 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xe7'), chr(0b1100100) + '\x65' + chr(4190 - 4091) + '\x6f' + '\144' + '\145')('\x75' + '\x74' + '\146' + '\x2d' + chr(0b0 + 0o70)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def l2WwN095Ives(oVre8I6UXc3b, QVK8u7RnAnpO, KhzrMpzISODo=ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b100011 + 0o15), 0o10)):
KhzrMpzISODo = LYHx5VlCvmk_(KhzrMpzISODo, xafqLlk3kkUe(SXOLrMavuUCe(b'\xa0s^\xaf\x06lP'), chr(100) + '\x65' + chr(99) + '\x6f' + chr(0b1100100) + chr(0b1001001 + 0o34))('\x75' + chr(7720 - 7604) + '\146' + chr(0b101101) + chr(0b110001 + 0o7)))
re0VVGAVKu27 = oVre8I6UXc3b if KhzrMpzISODo else oVre8I6UXc3b.igThHS4jwVsa()
if PlSM16l2KDPD(QVK8u7RnAnpO, essMXh4s9f1w):
jtbovtaIYjRB = xafqLlk3kkUe(SXOLrMavuUCe(b'\x9doK\xa2\x13f[9\xfc\x15hH>\x93F-\x1f\x8b\xbdh\xee\xcdn6\x16\xcbi\x996\xa5p\x06\x06^t/7\x07\xba8\xbai\x03\xaf\x0edP~\xbd(i\x1a"\x85\\c_\xc5\xacw\xd4\x8ey#\x1f\xd9c\x98q\xe0JO\x06^\'i#S\xa3#\xac=X\xa6\x15|\\1\xb2j-\x1d%\x93[lU\x80\x87|\xd0\xdaj%\x1c\xdeo\x8e,\xe7#VOSk/"U\xb30\xbd=}\xa6\x15fP-\xfc*dQ2\xd6T-\\\x8c\xbbk\xd8\xc1a#\x01\xd5(\xe1\x19\xafq\x01BVd{{K\xbf:\xac1\x0e\xb6\x14j\x15y\xb2#ze4\x97Ah_\x8a\xaav\xd4\xdd!6\x1c\xf3b\x82<\xb4+\x08\x015A`$\x07\xba8\xbai\x03\xaf\x0edPr\xfc3~_w\xd1[hO\xba\xbb~\xc5\xcbh-\x01\xc5c\x98q\xb6bMSZt(x'), chr(0b1100100) + '\145' + '\143' + chr(9936 - 9825) + chr(0b1100100) + chr(0b1100101))(chr(0b100101 + 0o120) + '\164' + chr(9871 - 9769) + '\x2d' + chr(0b10110 + 0o42))
nDEnNBabFNKm(jtbovtaIYjRB, VHAt7CcYKC2T, stacklevel=ehT0Px3KOsy9(chr(48) + '\157' + chr(0b1000 + 0o52), ord("\x08")))
QVK8u7RnAnpO = YyaZ4tpXu4lf(QVK8u7RnAnpO)
if KwJXno8t8wVV(QVK8u7RnAnpO):
re0VVGAVKu27.mZZDAT49UzAb = [QVK8u7RnAnpO.get(N7j7ePTXzzI0, N7j7ePTXzzI0) for N7j7ePTXzzI0 in re0VVGAVKu27.mZZDAT49UzAb]
elif tzcpInYwBvYW(QVK8u7RnAnpO):
re0VVGAVKu27.mZZDAT49UzAb = [QVK8u7RnAnpO(N7j7ePTXzzI0) for N7j7ePTXzzI0 in re0VVGAVKu27.mZZDAT49UzAb]
else:
re0VVGAVKu27.mZZDAT49UzAb = QVK8u7RnAnpO
if not KhzrMpzISODo:
return re0VVGAVKu27
|
pandas-dev/pandas
|
pandas/core/arrays/categorical.py
|
Categorical.reorder_categories
|
def reorder_categories(self, new_categories, ordered=None, inplace=False):
"""
Reorder categories as specified in new_categories.
`new_categories` need to include all old categories and no new category
items.
Parameters
----------
new_categories : Index-like
The categories in new order.
ordered : bool, optional
Whether or not the categorical is treated as a ordered categorical.
If not given, do not change the ordered information.
inplace : bool, default False
Whether or not to reorder the categories inplace or return a copy of
this categorical with reordered categories.
Returns
-------
cat : Categorical with reordered categories or None if inplace.
Raises
------
ValueError
If the new categories do not contain all old category items or any
new ones
See Also
--------
rename_categories
add_categories
remove_categories
remove_unused_categories
set_categories
"""
inplace = validate_bool_kwarg(inplace, 'inplace')
if set(self.dtype.categories) != set(new_categories):
raise ValueError("items in new_categories are not the same as in "
"old categories")
return self.set_categories(new_categories, ordered=ordered,
inplace=inplace)
|
python
|
def reorder_categories(self, new_categories, ordered=None, inplace=False):
"""
Reorder categories as specified in new_categories.
`new_categories` need to include all old categories and no new category
items.
Parameters
----------
new_categories : Index-like
The categories in new order.
ordered : bool, optional
Whether or not the categorical is treated as a ordered categorical.
If not given, do not change the ordered information.
inplace : bool, default False
Whether or not to reorder the categories inplace or return a copy of
this categorical with reordered categories.
Returns
-------
cat : Categorical with reordered categories or None if inplace.
Raises
------
ValueError
If the new categories do not contain all old category items or any
new ones
See Also
--------
rename_categories
add_categories
remove_categories
remove_unused_categories
set_categories
"""
inplace = validate_bool_kwarg(inplace, 'inplace')
if set(self.dtype.categories) != set(new_categories):
raise ValueError("items in new_categories are not the same as in "
"old categories")
return self.set_categories(new_categories, ordered=ordered,
inplace=inplace)
|
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Reorder categories as specified in new_categories.
`new_categories` need to include all old categories and no new category
items.
Parameters
----------
new_categories : Index-like
The categories in new order.
ordered : bool, optional
Whether or not the categorical is treated as a ordered categorical.
If not given, do not change the ordered information.
inplace : bool, default False
Whether or not to reorder the categories inplace or return a copy of
this categorical with reordered categories.
Returns
-------
cat : Categorical with reordered categories or None if inplace.
Raises
------
ValueError
If the new categories do not contain all old category items or any
new ones
See Also
--------
rename_categories
add_categories
remove_categories
remove_unused_categories
set_categories
|
[
"Reorder",
"categories",
"as",
"specified",
"in",
"new_categories",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/arrays/categorical.py#L942-L983
|
train
|
Reorder the categories of the current object.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + chr(111) + '\062' + chr(0b1011 + 0o53) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110011) + chr(48) + chr(0b110101), 0o10), ehT0Px3KOsy9(chr(344 - 296) + chr(0b1001110 + 0o41) + chr(0b10101 + 0o41) + chr(124 - 75), 0o10), ehT0Px3KOsy9(chr(0b1000 + 0o50) + chr(111) + chr(0b110011) + '\x37' + chr(51), 0b1000), ehT0Px3KOsy9(chr(2017 - 1969) + chr(1532 - 1421) + chr(0b110010) + chr(1056 - 1008) + chr(0b110001 + 0o0), 0b1000), ehT0Px3KOsy9('\060' + '\157' + '\063' + chr(0b110001) + chr(55), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x32' + chr(0b110011) + '\x36', ord("\x08")), ehT0Px3KOsy9(chr(0b100110 + 0o12) + '\x6f' + '\x33' + '\060' + chr(1930 - 1880), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(7008 - 6897) + chr(0b11000 + 0o36) + '\x31', 8), ehT0Px3KOsy9(chr(0b111 + 0o51) + chr(5071 - 4960) + chr(1413 - 1362) + chr(2340 - 2286) + chr(0b110000), 57397 - 57389), ehT0Px3KOsy9(chr(1099 - 1051) + '\157' + chr(0b1000 + 0o53) + chr(1347 - 1298) + '\060', 0b1000), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110110) + '\x35', 0o10), ehT0Px3KOsy9('\x30' + chr(11669 - 11558) + chr(1854 - 1805) + chr(0b10010 + 0o42) + '\x35', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1100110 + 0o11) + '\062' + chr(0b110 + 0o54), ord("\x08")), ehT0Px3KOsy9(chr(0b11011 + 0o25) + chr(111) + chr(0b110010) + '\x36' + chr(0b100011 + 0o24), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x32' + '\061' + chr(0b110001 + 0o5), ord("\x08")), ehT0Px3KOsy9(chr(989 - 941) + chr(0b1101010 + 0o5) + chr(0b110001) + '\x35' + chr(51), 34059 - 34051), ehT0Px3KOsy9(chr(0b100001 + 0o17) + chr(111) + chr(1236 - 1185) + chr(52), 56568 - 56560), ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(6849 - 6738) + chr(0b10100 + 0o36) + chr(0b101 + 0o53) + chr(605 - 551), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b1001 + 0o53) + '\062', 60363 - 60355), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b1 + 0o61) + chr(49) + chr(2331 - 2281), 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(1354 - 1305) + chr(53) + '\x30', 5671 - 5663), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110001) + chr(0b110000 + 0o0) + '\065', 0b1000), ehT0Px3KOsy9('\060' + chr(8001 - 7890) + chr(0b110010) + '\x30' + chr(0b110111), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + '\062' + '\x37' + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(0b1110 + 0o42) + '\x6f' + '\x33' + '\x32', 0b1000), ehT0Px3KOsy9('\x30' + chr(0b111000 + 0o67) + chr(0b100001 + 0o21) + chr(1316 - 1262) + '\066', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b10000 + 0o42) + chr(0b101100 + 0o5) + chr(0b10100 + 0o41), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b11010 + 0o30) + '\x31' + chr(0b110101), 8), ehT0Px3KOsy9(chr(964 - 916) + chr(0b0 + 0o157) + '\063' + chr(0b100 + 0o62) + chr(0b11000 + 0o34), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(645 - 534) + '\x34' + chr(51), 0o10), ehT0Px3KOsy9(chr(0b1000 + 0o50) + chr(0b1011010 + 0o25) + chr(181 - 128) + chr(55), 55001 - 54993), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(1780 - 1730) + chr(560 - 511) + chr(1312 - 1261), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1100111 + 0o10) + chr(2085 - 2036) + chr(51) + '\x32', ord("\x08")), ehT0Px3KOsy9(chr(153 - 105) + chr(1045 - 934) + chr(1116 - 1067) + chr(0b11100 + 0o31) + '\x32', 27676 - 27668), ehT0Px3KOsy9('\x30' + chr(2772 - 2661) + chr(0b110001) + chr(0b110001) + '\x34', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b11000 + 0o35) + '\065', 46079 - 46071), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b1101 + 0o46) + chr(1102 - 1050) + chr(577 - 529), 53397 - 53389), ehT0Px3KOsy9(chr(1895 - 1847) + chr(0b110001 + 0o76) + chr(50) + chr(0b110001) + chr(50), 8), ehT0Px3KOsy9(chr(0b110000) + chr(8033 - 7922) + chr(246 - 192) + chr(0b11100 + 0o24), 21194 - 21186)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(2152 - 2104) + chr(10825 - 10714) + '\065' + chr(1916 - 1868), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x9e'), chr(0b1011110 + 0o6) + chr(0b101011 + 0o72) + chr(0b1100011) + chr(685 - 574) + '\x64' + '\x65')(chr(0b1011110 + 0o27) + '\164' + chr(102) + chr(0b1011 + 0o42) + chr(2604 - 2548)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def ess1BMPfSOtZ(oVre8I6UXc3b, QVK8u7RnAnpO, TillFngeGqII=None, KhzrMpzISODo=ehT0Px3KOsy9(chr(195 - 147) + chr(0b1101111) + chr(0b110000), 0o10)):
KhzrMpzISODo = LYHx5VlCvmk_(KhzrMpzISODo, xafqLlk3kkUe(SXOLrMavuUCe(b'\xd9\xabA\x97\xe0\xac\xfb'), chr(100) + chr(101) + chr(0b101000 + 0o73) + chr(0b10100 + 0o133) + chr(0b1000100 + 0o40) + chr(0b111110 + 0o47))('\165' + chr(0b1110100) + chr(0b101011 + 0o73) + '\055' + '\070'))
if MVEN8G6CxlvR(xafqLlk3kkUe(oVre8I6UXc3b.dtype, xafqLlk3kkUe(SXOLrMavuUCe(b'\xdd\x9fk\xbf\xc0\x9b\xaa\xfbd\x8a\x89W'), '\144' + chr(0b1100101) + '\x63' + '\157' + chr(6135 - 6035) + '\x65')(chr(2801 - 2684) + '\x74' + '\146' + chr(0b10110 + 0o27) + '\x38'))) != MVEN8G6CxlvR(QVK8u7RnAnpO):
raise q1QCh3W88sgk(xafqLlk3kkUe(SXOLrMavuUCe(b'\xd9\xb1T\x96\xf2\xef\xf7\xac\x11\x9e\xadB:q\xd6\xfa\x0e{\xe9P\xe3\r6\xa7\xd8h\xd3\xad\xe3\x9bW\x0f\xff2\x0fl^\x81\xe7U\x90\xa4B\xdb\xe8\xa1\xbe\xad]\x94\xe8V\x04f\xd2\xe9\x04n\xefG\xf9'), chr(1634 - 1534) + chr(101) + chr(3533 - 3434) + chr(0b1101111) + chr(9728 - 9628) + '\145')(chr(0b1011101 + 0o30) + '\x74' + chr(0b1001010 + 0o34) + chr(45) + '\070'))
return xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\xc3\xa0E\xa4\xe2\xae\xea\xa7V\x9f\xba\\\x00a'), chr(100) + chr(101) + chr(7466 - 7367) + chr(0b1001100 + 0o43) + chr(4250 - 4150) + '\x65')(chr(117) + chr(0b1110100) + '\x66' + chr(45) + chr(0b100 + 0o64)))(QVK8u7RnAnpO, ordered=TillFngeGqII, inplace=KhzrMpzISODo)
|
pandas-dev/pandas
|
pandas/core/arrays/categorical.py
|
Categorical.add_categories
|
def add_categories(self, new_categories, inplace=False):
"""
Add new categories.
`new_categories` will be included at the last/highest place in the
categories and will be unused directly after this call.
Parameters
----------
new_categories : category or list-like of category
The new categories to be included.
inplace : bool, default False
Whether or not to add the categories inplace or return a copy of
this categorical with added categories.
Returns
-------
cat : Categorical with new categories added or None if inplace.
Raises
------
ValueError
If the new categories include old categories or do not validate as
categories
See Also
--------
rename_categories
reorder_categories
remove_categories
remove_unused_categories
set_categories
"""
inplace = validate_bool_kwarg(inplace, 'inplace')
if not is_list_like(new_categories):
new_categories = [new_categories]
already_included = set(new_categories) & set(self.dtype.categories)
if len(already_included) != 0:
msg = ("new categories must not include old categories: "
"{already_included!s}")
raise ValueError(msg.format(already_included=already_included))
new_categories = list(self.dtype.categories) + list(new_categories)
new_dtype = CategoricalDtype(new_categories, self.ordered)
cat = self if inplace else self.copy()
cat._dtype = new_dtype
cat._codes = coerce_indexer_dtype(cat._codes, new_dtype.categories)
if not inplace:
return cat
|
python
|
def add_categories(self, new_categories, inplace=False):
"""
Add new categories.
`new_categories` will be included at the last/highest place in the
categories and will be unused directly after this call.
Parameters
----------
new_categories : category or list-like of category
The new categories to be included.
inplace : bool, default False
Whether or not to add the categories inplace or return a copy of
this categorical with added categories.
Returns
-------
cat : Categorical with new categories added or None if inplace.
Raises
------
ValueError
If the new categories include old categories or do not validate as
categories
See Also
--------
rename_categories
reorder_categories
remove_categories
remove_unused_categories
set_categories
"""
inplace = validate_bool_kwarg(inplace, 'inplace')
if not is_list_like(new_categories):
new_categories = [new_categories]
already_included = set(new_categories) & set(self.dtype.categories)
if len(already_included) != 0:
msg = ("new categories must not include old categories: "
"{already_included!s}")
raise ValueError(msg.format(already_included=already_included))
new_categories = list(self.dtype.categories) + list(new_categories)
new_dtype = CategoricalDtype(new_categories, self.ordered)
cat = self if inplace else self.copy()
cat._dtype = new_dtype
cat._codes = coerce_indexer_dtype(cat._codes, new_dtype.categories)
if not inplace:
return cat
|
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":",
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"cat"
] |
Add new categories.
`new_categories` will be included at the last/highest place in the
categories and will be unused directly after this call.
Parameters
----------
new_categories : category or list-like of category
The new categories to be included.
inplace : bool, default False
Whether or not to add the categories inplace or return a copy of
this categorical with added categories.
Returns
-------
cat : Categorical with new categories added or None if inplace.
Raises
------
ValueError
If the new categories include old categories or do not validate as
categories
See Also
--------
rename_categories
reorder_categories
remove_categories
remove_unused_categories
set_categories
|
[
"Add",
"new",
"categories",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/arrays/categorical.py#L985-L1033
|
train
|
Add new categories to the internal Categorical.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + chr(111) + '\x36' + chr(0b110000), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110001) + chr(0b100111 + 0o11) + '\063', ord("\x08")), ehT0Px3KOsy9(chr(0b11 + 0o55) + '\x6f' + chr(51) + chr(0b101 + 0o53) + chr(55), 24515 - 24507), ehT0Px3KOsy9(chr(48) + chr(0b1001011 + 0o44) + '\x31' + '\061' + chr(0b110001), 1910 - 1902), ehT0Px3KOsy9(chr(48) + chr(5309 - 5198) + chr(486 - 431), 59981 - 59973), ehT0Px3KOsy9('\060' + '\157' + chr(2411 - 2358) + chr(54), 0b1000), ehT0Px3KOsy9('\060' + chr(0b100111 + 0o110) + chr(0b11101 + 0o25) + chr(0b100 + 0o54) + '\062', 15492 - 15484), ehT0Px3KOsy9(chr(0b110000) + chr(0b11110 + 0o121) + chr(51) + chr(0b101000 + 0o15) + chr(0b110111), 25927 - 25919), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110010) + chr(2378 - 2324) + chr(0b110101), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110110) + '\064', 0b1000), ehT0Px3KOsy9('\060' + chr(11289 - 11178) + chr(0b110011) + '\067' + chr(53), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b10 + 0o62) + chr(645 - 593), 42073 - 42065), ehT0Px3KOsy9(chr(621 - 573) + chr(111) + '\061' + chr(1109 - 1061) + '\x33', 8), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b101110 + 0o3) + chr(52) + '\x36', 0o10), ehT0Px3KOsy9(chr(1065 - 1017) + '\x6f' + '\066' + chr(0b101001 + 0o13), 8), ehT0Px3KOsy9('\x30' + '\157' + chr(0b10111 + 0o35) + chr(52), 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b11110 + 0o24) + chr(0b110000) + chr(1667 - 1615), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + '\x32' + chr(0b10010 + 0o37) + '\065', 50513 - 50505), ehT0Px3KOsy9(chr(0b10001 + 0o37) + chr(0b1101011 + 0o4) + chr(0b110010) + '\062' + '\x37', 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b11101 + 0o26) + chr(1524 - 1474) + '\060', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\x33' + chr(0b110100) + chr(0b110011), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\061' + '\061' + '\x32', 31661 - 31653), ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(111) + chr(51) + chr(55) + chr(923 - 868), 0o10), ehT0Px3KOsy9(chr(1055 - 1007) + chr(0b1101111) + '\062' + chr(0b11101 + 0o24) + chr(1777 - 1725), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x31' + '\065', 0o10), ehT0Px3KOsy9(chr(1417 - 1369) + chr(4679 - 4568) + chr(0b1011 + 0o52) + '\063', 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110010) + chr(48) + '\062', 8), ehT0Px3KOsy9('\x30' + chr(7907 - 7796) + chr(51) + '\x33' + chr(48), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110011) + '\x34' + chr(0b110001), 26567 - 26559), ehT0Px3KOsy9(chr(1670 - 1622) + '\157' + chr(0b110011) + chr(49) + chr(50), 30099 - 30091), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b100101 + 0o16) + chr(51), 0b1000), ehT0Px3KOsy9(chr(1627 - 1579) + chr(0b1101111) + '\061' + chr(2221 - 2173) + '\x31', 28290 - 28282), ehT0Px3KOsy9('\060' + chr(0b111100 + 0o63) + chr(0b110011) + chr(0b101 + 0o62), 0o10), ehT0Px3KOsy9('\060' + chr(0b1001101 + 0o42) + chr(51) + chr(54) + chr(1185 - 1133), 0o10), ehT0Px3KOsy9(chr(48) + chr(10403 - 10292) + chr(0b11 + 0o60) + chr(0b110001) + chr(765 - 717), 26318 - 26310), ehT0Px3KOsy9('\060' + chr(8948 - 8837) + '\062' + '\062' + chr(2235 - 2181), 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(53) + '\066', 8), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\062' + chr(49) + chr(1269 - 1221), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(11187 - 11076) + chr(752 - 703) + chr(0b110000) + '\x30', 63905 - 63897), ehT0Px3KOsy9(chr(0b100111 + 0o11) + chr(0b1101111) + chr(0b10110 + 0o35) + '\x32' + '\066', 1834 - 1826)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + chr(558 - 447) + chr(0b110101) + '\x30', 0o10)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x1e'), chr(100) + '\x65' + '\143' + '\x6f' + '\144' + '\x65')('\x75' + chr(0b100111 + 0o115) + chr(0b1000 + 0o136) + '\055' + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def T12YUpmkwUUQ(oVre8I6UXc3b, QVK8u7RnAnpO, KhzrMpzISODo=ehT0Px3KOsy9(chr(0b111 + 0o51) + chr(111) + chr(48), 48223 - 48215)):
KhzrMpzISODo = LYHx5VlCvmk_(KhzrMpzISODo, xafqLlk3kkUe(SXOLrMavuUCe(b'Y-\xb7%fM\xe7'), '\x64' + chr(0b1100101) + chr(0b1100011) + '\157' + chr(1567 - 1467) + chr(101))(chr(0b1100110 + 0o17) + chr(12995 - 12879) + '\x66' + '\055' + chr(0b110001 + 0o7)))
if not bAgBF7jXI53B(QVK8u7RnAnpO):
QVK8u7RnAnpO = [QVK8u7RnAnpO]
nJumMb6bGXlz = MVEN8G6CxlvR(QVK8u7RnAnpO) & MVEN8G6CxlvR(oVre8I6UXc3b.dtype.mZZDAT49UzAb)
if c2A0yzQpDQB3(nJumMb6bGXlz) != ehT0Px3KOsy9(chr(791 - 743) + chr(111) + '\x30', 8):
jtbovtaIYjRB = xafqLlk3kkUe(SXOLrMavuUCe(b'^&\xb0idO\xf6\x8a\xd2[\x8fM&\x15\x14I\xf1\xfe\xe3\xf0\x8d%\x8b\xacdE\xe1\xb4\x94\xae~ap\x98\xac\xb6M\xe94\xb3W,\xb5 b]\xb8\xcf\xceU\x91V&\x07P]\xdb\xe4\xf9\xb3\x8f?\x9b\xe9i\n\xf1\xa5'), '\144' + chr(0b1100101 + 0o0) + '\143' + chr(111) + chr(0b10101 + 0o117) + '\145')(chr(0b1110101) + chr(116) + '\x66' + chr(45) + chr(56))
raise q1QCh3W88sgk(xafqLlk3kkUe(jtbovtaIYjRB, xafqLlk3kkUe(SXOLrMavuUCe(b'V,\xb5$fZ'), '\x64' + chr(7022 - 6921) + chr(99) + chr(0b100010 + 0o115) + chr(0b1100100) + chr(101))('\165' + '\x74' + '\146' + '\055' + '\x38'))(already_included=nJumMb6bGXlz))
QVK8u7RnAnpO = YyaZ4tpXu4lf(oVre8I6UXc3b.dtype.mZZDAT49UzAb) + YyaZ4tpXu4lf(QVK8u7RnAnpO)
H6Aqpf9qhdEs = CBSVoRj_kvTn(QVK8u7RnAnpO, oVre8I6UXc3b.ordered)
re0VVGAVKu27 = oVre8I6UXc3b if KhzrMpzISODo else oVre8I6UXc3b.igThHS4jwVsa()
re0VVGAVKu27.z2oVGDR5m1eh = H6Aqpf9qhdEs
re0VVGAVKu27.d5BDZJl_zDsu = IhoUBFeIAvnv(re0VVGAVKu27.d5BDZJl_zDsu, H6Aqpf9qhdEs.mZZDAT49UzAb)
if not KhzrMpzISODo:
return re0VVGAVKu27
|
pandas-dev/pandas
|
pandas/core/arrays/categorical.py
|
Categorical.remove_categories
|
def remove_categories(self, removals, inplace=False):
"""
Remove the specified categories.
`removals` must be included in the old categories. Values which were in
the removed categories will be set to NaN
Parameters
----------
removals : category or list of categories
The categories which should be removed.
inplace : bool, default False
Whether or not to remove the categories inplace or return a copy of
this categorical with removed categories.
Returns
-------
cat : Categorical with removed categories or None if inplace.
Raises
------
ValueError
If the removals are not contained in the categories
See Also
--------
rename_categories
reorder_categories
add_categories
remove_unused_categories
set_categories
"""
inplace = validate_bool_kwarg(inplace, 'inplace')
if not is_list_like(removals):
removals = [removals]
removal_set = set(list(removals))
not_included = removal_set - set(self.dtype.categories)
new_categories = [c for c in self.dtype.categories
if c not in removal_set]
# GH 10156
if any(isna(removals)):
not_included = [x for x in not_included if notna(x)]
new_categories = [x for x in new_categories if notna(x)]
if len(not_included) != 0:
msg = "removals must all be in old categories: {not_included!s}"
raise ValueError(msg.format(not_included=not_included))
return self.set_categories(new_categories, ordered=self.ordered,
rename=False, inplace=inplace)
|
python
|
def remove_categories(self, removals, inplace=False):
"""
Remove the specified categories.
`removals` must be included in the old categories. Values which were in
the removed categories will be set to NaN
Parameters
----------
removals : category or list of categories
The categories which should be removed.
inplace : bool, default False
Whether or not to remove the categories inplace or return a copy of
this categorical with removed categories.
Returns
-------
cat : Categorical with removed categories or None if inplace.
Raises
------
ValueError
If the removals are not contained in the categories
See Also
--------
rename_categories
reorder_categories
add_categories
remove_unused_categories
set_categories
"""
inplace = validate_bool_kwarg(inplace, 'inplace')
if not is_list_like(removals):
removals = [removals]
removal_set = set(list(removals))
not_included = removal_set - set(self.dtype.categories)
new_categories = [c for c in self.dtype.categories
if c not in removal_set]
# GH 10156
if any(isna(removals)):
not_included = [x for x in not_included if notna(x)]
new_categories = [x for x in new_categories if notna(x)]
if len(not_included) != 0:
msg = "removals must all be in old categories: {not_included!s}"
raise ValueError(msg.format(not_included=not_included))
return self.set_categories(new_categories, ordered=self.ordered,
rename=False, inplace=inplace)
|
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] |
Remove the specified categories.
`removals` must be included in the old categories. Values which were in
the removed categories will be set to NaN
Parameters
----------
removals : category or list of categories
The categories which should be removed.
inplace : bool, default False
Whether or not to remove the categories inplace or return a copy of
this categorical with removed categories.
Returns
-------
cat : Categorical with removed categories or None if inplace.
Raises
------
ValueError
If the removals are not contained in the categories
See Also
--------
rename_categories
reorder_categories
add_categories
remove_unused_categories
set_categories
|
[
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] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/arrays/categorical.py#L1035-L1086
|
train
|
Removes the specified categories from the internal set.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + chr(111) + '\061' + chr(55) + chr(54), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110001) + chr(0b110011), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(2030 - 1980) + chr(0b110111) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(52) + chr(586 - 537), 0b1000), ehT0Px3KOsy9('\060' + '\157' + '\x33' + chr(0b110001) + chr(1955 - 1902), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(995 - 946) + '\063' + chr(0b10 + 0o65), 56222 - 56214), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110001) + chr(628 - 576), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + '\x31' + chr(0b110011), 8), ehT0Px3KOsy9('\x30' + chr(0b101110 + 0o101) + chr(50) + '\x35' + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110010) + chr(0b110011) + '\062', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + '\061' + '\x31' + chr(1026 - 973), ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + '\062' + '\060' + chr(0b110100), 0o10), ehT0Px3KOsy9(chr(0b1001 + 0o47) + chr(0b1101111) + chr(54) + chr(55), 0b1000), ehT0Px3KOsy9(chr(1297 - 1249) + chr(7716 - 7605) + chr(0b110010) + chr(800 - 745), ord("\x08")), ehT0Px3KOsy9(chr(0b101101 + 0o3) + '\157' + '\x33' + '\066' + chr(0b1 + 0o63), 0b1000), ehT0Px3KOsy9(chr(48) + chr(9367 - 9256) + chr(566 - 515) + chr(0b110110) + '\x37', ord("\x08")), ehT0Px3KOsy9(chr(1834 - 1786) + '\x6f' + '\x33' + chr(0b110111) + chr(0b100101 + 0o22), 53139 - 53131), ehT0Px3KOsy9(chr(0b10001 + 0o37) + chr(3383 - 3272) + chr(0b110010) + chr(2500 - 2447) + chr(0b110010), 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b1000 + 0o53) + '\067' + '\x30', 0b1000), ehT0Px3KOsy9(chr(876 - 828) + '\x6f' + '\063' + chr(0b100101 + 0o16), 12803 - 12795), ehT0Px3KOsy9(chr(0b110000) + chr(11460 - 11349) + chr(49) + '\x35' + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b110111 + 0o70) + chr(0b100010 + 0o20) + chr(0b101001 + 0o11) + chr(2868 - 2814), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(51) + chr(50), 0b1000), ehT0Px3KOsy9(chr(0b100111 + 0o11) + '\x6f' + chr(0b110011) + '\x37', 58511 - 58503), ehT0Px3KOsy9(chr(0b10000 + 0o40) + '\157' + chr(1976 - 1927) + chr(55) + chr(51), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1001110 + 0o41) + '\063' + chr(417 - 364) + chr(0b110110), 0b1000), ehT0Px3KOsy9(chr(303 - 255) + chr(2966 - 2855) + chr(0b110011) + '\x36' + chr(50), 0o10), ehT0Px3KOsy9(chr(0b101010 + 0o6) + chr(0b1101111) + chr(0b110001) + chr(54) + '\060', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\061' + chr(48) + chr(226 - 176), 0b1000), ehT0Px3KOsy9(chr(0b1000 + 0o50) + '\x6f' + chr(51) + '\062' + chr(55), 0b1000), ehT0Px3KOsy9(chr(1618 - 1570) + chr(0b1101111) + '\x32' + chr(2687 - 2635) + chr(0b110100), 45418 - 45410), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110011) + chr(0b110000) + chr(55), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110010) + chr(55) + chr(1398 - 1346), 0b1000), ehT0Px3KOsy9(chr(499 - 451) + chr(2568 - 2457) + chr(0b110010) + chr(0b110111) + chr(49), 25872 - 25864), ehT0Px3KOsy9('\060' + chr(0b1011010 + 0o25) + '\063' + '\x36' + chr(1115 - 1063), 8), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\x34' + chr(0b100001 + 0o20), 8), ehT0Px3KOsy9(chr(271 - 223) + '\157' + '\x36' + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b101101 + 0o102) + chr(0b110011) + chr(0b101 + 0o56) + chr(0b110111), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(11490 - 11379) + '\063' + '\x34' + chr(0b10100 + 0o37), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1001010 + 0o45) + '\061' + chr(0b110110) + chr(676 - 624), 55627 - 55619)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + '\x6f' + chr(2542 - 2489) + '\060', 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'P'), chr(100) + chr(101) + chr(0b1011001 + 0o12) + '\x6f' + '\144' + '\145')(chr(117) + chr(0b10100 + 0o140) + '\146' + '\x2d' + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def eI3weCqOA7C6(oVre8I6UXc3b, R6218UBYa3T8, KhzrMpzISODo=ehT0Px3KOsy9('\060' + chr(111) + chr(0b110000), 0o10)):
KhzrMpzISODo = LYHx5VlCvmk_(KhzrMpzISODo, xafqLlk3kkUe(SXOLrMavuUCe(b'\x17e\xc8M\xac<i'), chr(0b1100100) + chr(101) + chr(0b1111 + 0o124) + '\157' + chr(100) + '\x65')('\165' + chr(0b1010111 + 0o35) + chr(0b1100110) + chr(45) + chr(2467 - 2411)))
if not bAgBF7jXI53B(R6218UBYa3T8):
R6218UBYa3T8 = [R6218UBYa3T8]
vtFm0h5piBgB = MVEN8G6CxlvR(YyaZ4tpXu4lf(R6218UBYa3T8))
NYdqA7LfA4xB = vtFm0h5piBgB - MVEN8G6CxlvR(oVre8I6UXc3b.dtype.mZZDAT49UzAb)
QVK8u7RnAnpO = [qzn1Ctg9WgNh for qzn1Ctg9WgNh in oVre8I6UXc3b.dtype.mZZDAT49UzAb if qzn1Ctg9WgNh not in vtFm0h5piBgB]
if UVSi4XW7eBIM(yBUx5qcFiTz6(R6218UBYa3T8)):
NYdqA7LfA4xB = [OeWW0F1dBPRQ for OeWW0F1dBPRQ in NYdqA7LfA4xB if QYo7qglrtH1q(OeWW0F1dBPRQ)]
QVK8u7RnAnpO = [OeWW0F1dBPRQ for OeWW0F1dBPRQ in QVK8u7RnAnpO if QYo7qglrtH1q(OeWW0F1dBPRQ)]
if c2A0yzQpDQB3(NYdqA7LfA4xB) != ehT0Px3KOsy9(chr(106 - 58) + '\157' + '\060', 8):
jtbovtaIYjRB = xafqLlk3kkUe(SXOLrMavuUCe(b'\x0cn\xd5N\xbb>`x\x8e\xf78\xf7C7\x95\x9b\x93\x8a\x9a~J\xfft?\x14\x82\x96P!\xb6\xd0\xa2\xdb\xd6\x86HW\xac\xd9T\x05e\xd7U\x926bh\xc2\xef)\xe1S6\x87\x8a'), chr(100) + '\x65' + chr(0b1100011) + '\x6f' + chr(100) + '\145')(chr(708 - 591) + chr(116) + chr(102) + chr(0b101000 + 0o5) + '\x38')
raise q1QCh3W88sgk(xafqLlk3kkUe(jtbovtaIYjRB, xafqLlk3kkUe(SXOLrMavuUCe(b'\x18d\xcaL\xac+'), chr(0b1100100) + '\x65' + chr(99) + chr(0b1101111) + chr(0b111111 + 0o45) + '\x65')('\x75' + chr(116) + chr(0b1100110) + chr(1769 - 1724) + chr(56)))(not_included=NYdqA7LfA4xB))
return xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\rn\xcc~\xae>xn\xc9\xf5?\xedRd'), chr(7552 - 7452) + chr(0b1100101) + chr(0b1100011) + '\157' + chr(7506 - 7406) + '\x65')(chr(0b1110101) + chr(0b1110100) + '\146' + chr(45) + chr(0b111000)))(QVK8u7RnAnpO, ordered=xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\x11y\xdcD\xbf:h'), '\x64' + chr(0b0 + 0o145) + chr(0b11011 + 0o110) + '\157' + chr(7133 - 7033) + '\x65')('\165' + chr(0b1110100) + '\x66' + chr(0b101101) + chr(1696 - 1640))), rename=ehT0Px3KOsy9(chr(0b101110 + 0o2) + chr(0b110011 + 0o74) + chr(0b110000), 8), inplace=KhzrMpzISODo)
|
pandas-dev/pandas
|
pandas/core/arrays/categorical.py
|
Categorical.remove_unused_categories
|
def remove_unused_categories(self, inplace=False):
"""
Remove categories which are not used.
Parameters
----------
inplace : bool, default False
Whether or not to drop unused categories inplace or return a copy of
this categorical with unused categories dropped.
Returns
-------
cat : Categorical with unused categories dropped or None if inplace.
See Also
--------
rename_categories
reorder_categories
add_categories
remove_categories
set_categories
"""
inplace = validate_bool_kwarg(inplace, 'inplace')
cat = self if inplace else self.copy()
idx, inv = np.unique(cat._codes, return_inverse=True)
if idx.size != 0 and idx[0] == -1: # na sentinel
idx, inv = idx[1:], inv - 1
new_categories = cat.dtype.categories.take(idx)
new_dtype = CategoricalDtype._from_fastpath(new_categories,
ordered=self.ordered)
cat._dtype = new_dtype
cat._codes = coerce_indexer_dtype(inv, new_dtype.categories)
if not inplace:
return cat
|
python
|
def remove_unused_categories(self, inplace=False):
"""
Remove categories which are not used.
Parameters
----------
inplace : bool, default False
Whether or not to drop unused categories inplace or return a copy of
this categorical with unused categories dropped.
Returns
-------
cat : Categorical with unused categories dropped or None if inplace.
See Also
--------
rename_categories
reorder_categories
add_categories
remove_categories
set_categories
"""
inplace = validate_bool_kwarg(inplace, 'inplace')
cat = self if inplace else self.copy()
idx, inv = np.unique(cat._codes, return_inverse=True)
if idx.size != 0 and idx[0] == -1: # na sentinel
idx, inv = idx[1:], inv - 1
new_categories = cat.dtype.categories.take(idx)
new_dtype = CategoricalDtype._from_fastpath(new_categories,
ordered=self.ordered)
cat._dtype = new_dtype
cat._codes = coerce_indexer_dtype(inv, new_dtype.categories)
if not inplace:
return cat
|
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] |
Remove categories which are not used.
Parameters
----------
inplace : bool, default False
Whether or not to drop unused categories inplace or return a copy of
this categorical with unused categories dropped.
Returns
-------
cat : Categorical with unused categories dropped or None if inplace.
See Also
--------
rename_categories
reorder_categories
add_categories
remove_categories
set_categories
|
[
"Remove",
"categories",
"which",
"are",
"not",
"used",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/arrays/categorical.py#L1088-L1124
|
train
|
Returns a copy of the Categorical with unused categories dropped.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\x30' + '\157' + chr(51) + chr(0b101101 + 0o12) + chr(1007 - 954), 30763 - 30755), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b100000 + 0o21) + '\x35' + chr(1758 - 1709), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b10000 + 0o43) + chr(0b11001 + 0o27) + '\x36', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\062' + chr(2012 - 1959) + chr(0b110011), 0b1000), ehT0Px3KOsy9(chr(466 - 418) + chr(0b1101111) + chr(51) + chr(0b110110) + chr(48), 35799 - 35791), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(51) + chr(0b110000) + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(1057 - 1009) + chr(8928 - 8817) + '\x31' + chr(0b1001 + 0o50) + chr(0b110001), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x33' + chr(0b11010 + 0o33), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b100001 + 0o22) + '\066', 39601 - 39593), ehT0Px3KOsy9(chr(0b1001 + 0o47) + '\x6f' + chr(0b110000 + 0o2) + '\x31' + chr(0b1111 + 0o50), 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + '\x32' + '\066', 0b1000), ehT0Px3KOsy9(chr(69 - 21) + chr(0b1011010 + 0o25) + chr(2326 - 2277) + chr(0b10 + 0o65) + chr(0b10001 + 0o44), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(9749 - 9638) + '\x33' + chr(0b110101), 8), ehT0Px3KOsy9(chr(48) + chr(0b10101 + 0o132) + chr(0b111 + 0o53) + chr(55) + '\063', 65070 - 65062), ehT0Px3KOsy9('\x30' + chr(0b1011101 + 0o22) + chr(0b110110) + chr(54), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\063' + '\065', 8), ehT0Px3KOsy9(chr(0b11101 + 0o23) + chr(0b1100010 + 0o15) + chr(163 - 112) + chr(55) + chr(283 - 233), ord("\x08")), ehT0Px3KOsy9(chr(1962 - 1914) + chr(0b110101 + 0o72) + '\067' + chr(0b110100), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1011 + 0o144) + '\067' + chr(1801 - 1746), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(55) + '\066', ord("\x08")), ehT0Px3KOsy9(chr(831 - 783) + chr(111) + '\061' + '\x37' + '\x36', 17711 - 17703), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(93 - 43) + chr(794 - 740) + chr(2320 - 2266), 0o10), ehT0Px3KOsy9('\060' + chr(10708 - 10597) + '\062' + '\066' + chr(51), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b100101 + 0o16) + '\067' + chr(2888 - 2834), ord("\x08")), ehT0Px3KOsy9(chr(2231 - 2183) + chr(111) + '\x37' + '\063', 27140 - 27132), ehT0Px3KOsy9('\060' + chr(0b111011 + 0o64) + chr(0b100001 + 0o22) + '\x33' + chr(0b110010), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111 + 0o0) + chr(0b1101 + 0o50) + '\061', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110111) + chr(0b110001 + 0o1), 0b1000), ehT0Px3KOsy9(chr(0b1 + 0o57) + chr(7580 - 7469) + chr(1287 - 1237) + chr(0b110011) + '\x35', 0o10), ehT0Px3KOsy9('\060' + chr(0b111110 + 0o61) + chr(0b110011) + '\060' + chr(1391 - 1337), 8), ehT0Px3KOsy9('\060' + chr(0b110111 + 0o70) + '\063' + chr(0b1110 + 0o44) + chr(0b110001), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + '\x31' + chr(54) + '\x33', 53961 - 53953), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110011) + chr(0b110111) + '\061', 0o10), ehT0Px3KOsy9(chr(0b100001 + 0o17) + chr(11163 - 11052) + chr(1094 - 1045) + '\060' + chr(0b110011), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(49) + chr(0b110100) + chr(0b101 + 0o56), 0o10), ehT0Px3KOsy9(chr(1312 - 1264) + '\x6f' + chr(0b110000 + 0o3) + chr(2058 - 2007) + chr(0b101001 + 0o13), 17812 - 17804), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(55) + chr(0b1001 + 0o56), 8), ehT0Px3KOsy9('\060' + '\x6f' + chr(296 - 246) + chr(49) + chr(0b110 + 0o52), 0b1000), ehT0Px3KOsy9(chr(1354 - 1306) + chr(281 - 170) + chr(0b11100 + 0o27) + chr(0b1001 + 0o47), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(412 - 359), 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b100 + 0o54) + chr(11802 - 11691) + chr(53) + chr(0b10111 + 0o31), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xd3'), '\x64' + chr(101) + '\x63' + chr(9936 - 9825) + '\x64' + chr(0b1000111 + 0o36))('\165' + '\164' + chr(0b1100110) + chr(0b101101) + chr(0b11100 + 0o34)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def ZUGds4TDZ2hq(oVre8I6UXc3b, KhzrMpzISODo=ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\060', 0b1000)):
KhzrMpzISODo = LYHx5VlCvmk_(KhzrMpzISODo, xafqLlk3kkUe(SXOLrMavuUCe(b'\x94\x07\xb6\xc7\x91\xa7,'), '\x64' + chr(0b1100101) + chr(0b1100011) + '\157' + chr(0b1100100) + chr(101))(chr(0b1001011 + 0o52) + '\x74' + '\146' + chr(45) + chr(2687 - 2631)))
re0VVGAVKu27 = oVre8I6UXc3b if KhzrMpzISODo else oVre8I6UXc3b.igThHS4jwVsa()
(YlqusYB6InkM, b4EpukviFgdO) = WqUC3KWvYVup.unique(re0VVGAVKu27.d5BDZJl_zDsu, return_inverse=ehT0Px3KOsy9('\060' + '\157' + '\061', 0o10))
if xafqLlk3kkUe(YlqusYB6InkM, xafqLlk3kkUe(SXOLrMavuUCe(b'\x8e\x00\xbc\xce'), chr(0b100011 + 0o101) + '\x65' + '\x63' + '\157' + '\x64' + chr(101))(chr(117) + '\164' + '\x66' + '\x2d' + chr(0b110101 + 0o3))) != ehT0Px3KOsy9(chr(0b1001 + 0o47) + chr(0b1101111) + '\060', 8) and YlqusYB6InkM[ehT0Px3KOsy9(chr(0b10 + 0o56) + chr(0b1101111) + chr(2047 - 1999), 8)] == -ehT0Px3KOsy9('\060' + '\x6f' + chr(49), 8):
(YlqusYB6InkM, b4EpukviFgdO) = (YlqusYB6InkM[ehT0Px3KOsy9(chr(0b101010 + 0o6) + '\157' + chr(0b110001), 8):], b4EpukviFgdO - ehT0Px3KOsy9(chr(1116 - 1068) + chr(111) + chr(0b110001), 8))
QVK8u7RnAnpO = re0VVGAVKu27.dtype.categories.take(YlqusYB6InkM)
H6Aqpf9qhdEs = CBSVoRj_kvTn._from_fastpath(QVK8u7RnAnpO, ordered=oVre8I6UXc3b.ordered)
re0VVGAVKu27.z2oVGDR5m1eh = H6Aqpf9qhdEs
re0VVGAVKu27.d5BDZJl_zDsu = IhoUBFeIAvnv(b4EpukviFgdO, H6Aqpf9qhdEs.mZZDAT49UzAb)
if not KhzrMpzISODo:
return re0VVGAVKu27
|
pandas-dev/pandas
|
pandas/core/arrays/categorical.py
|
Categorical.map
|
def map(self, mapper):
"""
Map categories using input correspondence (dict, Series, or function).
Maps the categories to new categories. If the mapping correspondence is
one-to-one the result is a :class:`~pandas.Categorical` which has the
same order property as the original, otherwise a :class:`~pandas.Index`
is returned. NaN values are unaffected.
If a `dict` or :class:`~pandas.Series` is used any unmapped category is
mapped to `NaN`. Note that if this happens an :class:`~pandas.Index`
will be returned.
Parameters
----------
mapper : function, dict, or Series
Mapping correspondence.
Returns
-------
pandas.Categorical or pandas.Index
Mapped categorical.
See Also
--------
CategoricalIndex.map : Apply a mapping correspondence on a
:class:`~pandas.CategoricalIndex`.
Index.map : Apply a mapping correspondence on an
:class:`~pandas.Index`.
Series.map : Apply a mapping correspondence on a
:class:`~pandas.Series`.
Series.apply : Apply more complex functions on a
:class:`~pandas.Series`.
Examples
--------
>>> cat = pd.Categorical(['a', 'b', 'c'])
>>> cat
[a, b, c]
Categories (3, object): [a, b, c]
>>> cat.map(lambda x: x.upper())
[A, B, C]
Categories (3, object): [A, B, C]
>>> cat.map({'a': 'first', 'b': 'second', 'c': 'third'})
[first, second, third]
Categories (3, object): [first, second, third]
If the mapping is one-to-one the ordering of the categories is
preserved:
>>> cat = pd.Categorical(['a', 'b', 'c'], ordered=True)
>>> cat
[a, b, c]
Categories (3, object): [a < b < c]
>>> cat.map({'a': 3, 'b': 2, 'c': 1})
[3, 2, 1]
Categories (3, int64): [3 < 2 < 1]
If the mapping is not one-to-one an :class:`~pandas.Index` is returned:
>>> cat.map({'a': 'first', 'b': 'second', 'c': 'first'})
Index(['first', 'second', 'first'], dtype='object')
If a `dict` is used, all unmapped categories are mapped to `NaN` and
the result is an :class:`~pandas.Index`:
>>> cat.map({'a': 'first', 'b': 'second'})
Index(['first', 'second', nan], dtype='object')
"""
new_categories = self.categories.map(mapper)
try:
return self.from_codes(self._codes.copy(),
categories=new_categories,
ordered=self.ordered)
except ValueError:
# NA values are represented in self._codes with -1
# np.take causes NA values to take final element in new_categories
if np.any(self._codes == -1):
new_categories = new_categories.insert(len(new_categories),
np.nan)
return np.take(new_categories, self._codes)
|
python
|
def map(self, mapper):
"""
Map categories using input correspondence (dict, Series, or function).
Maps the categories to new categories. If the mapping correspondence is
one-to-one the result is a :class:`~pandas.Categorical` which has the
same order property as the original, otherwise a :class:`~pandas.Index`
is returned. NaN values are unaffected.
If a `dict` or :class:`~pandas.Series` is used any unmapped category is
mapped to `NaN`. Note that if this happens an :class:`~pandas.Index`
will be returned.
Parameters
----------
mapper : function, dict, or Series
Mapping correspondence.
Returns
-------
pandas.Categorical or pandas.Index
Mapped categorical.
See Also
--------
CategoricalIndex.map : Apply a mapping correspondence on a
:class:`~pandas.CategoricalIndex`.
Index.map : Apply a mapping correspondence on an
:class:`~pandas.Index`.
Series.map : Apply a mapping correspondence on a
:class:`~pandas.Series`.
Series.apply : Apply more complex functions on a
:class:`~pandas.Series`.
Examples
--------
>>> cat = pd.Categorical(['a', 'b', 'c'])
>>> cat
[a, b, c]
Categories (3, object): [a, b, c]
>>> cat.map(lambda x: x.upper())
[A, B, C]
Categories (3, object): [A, B, C]
>>> cat.map({'a': 'first', 'b': 'second', 'c': 'third'})
[first, second, third]
Categories (3, object): [first, second, third]
If the mapping is one-to-one the ordering of the categories is
preserved:
>>> cat = pd.Categorical(['a', 'b', 'c'], ordered=True)
>>> cat
[a, b, c]
Categories (3, object): [a < b < c]
>>> cat.map({'a': 3, 'b': 2, 'c': 1})
[3, 2, 1]
Categories (3, int64): [3 < 2 < 1]
If the mapping is not one-to-one an :class:`~pandas.Index` is returned:
>>> cat.map({'a': 'first', 'b': 'second', 'c': 'first'})
Index(['first', 'second', 'first'], dtype='object')
If a `dict` is used, all unmapped categories are mapped to `NaN` and
the result is an :class:`~pandas.Index`:
>>> cat.map({'a': 'first', 'b': 'second'})
Index(['first', 'second', nan], dtype='object')
"""
new_categories = self.categories.map(mapper)
try:
return self.from_codes(self._codes.copy(),
categories=new_categories,
ordered=self.ordered)
except ValueError:
# NA values are represented in self._codes with -1
# np.take causes NA values to take final element in new_categories
if np.any(self._codes == -1):
new_categories = new_categories.insert(len(new_categories),
np.nan)
return np.take(new_categories, self._codes)
|
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] |
Map categories using input correspondence (dict, Series, or function).
Maps the categories to new categories. If the mapping correspondence is
one-to-one the result is a :class:`~pandas.Categorical` which has the
same order property as the original, otherwise a :class:`~pandas.Index`
is returned. NaN values are unaffected.
If a `dict` or :class:`~pandas.Series` is used any unmapped category is
mapped to `NaN`. Note that if this happens an :class:`~pandas.Index`
will be returned.
Parameters
----------
mapper : function, dict, or Series
Mapping correspondence.
Returns
-------
pandas.Categorical or pandas.Index
Mapped categorical.
See Also
--------
CategoricalIndex.map : Apply a mapping correspondence on a
:class:`~pandas.CategoricalIndex`.
Index.map : Apply a mapping correspondence on an
:class:`~pandas.Index`.
Series.map : Apply a mapping correspondence on a
:class:`~pandas.Series`.
Series.apply : Apply more complex functions on a
:class:`~pandas.Series`.
Examples
--------
>>> cat = pd.Categorical(['a', 'b', 'c'])
>>> cat
[a, b, c]
Categories (3, object): [a, b, c]
>>> cat.map(lambda x: x.upper())
[A, B, C]
Categories (3, object): [A, B, C]
>>> cat.map({'a': 'first', 'b': 'second', 'c': 'third'})
[first, second, third]
Categories (3, object): [first, second, third]
If the mapping is one-to-one the ordering of the categories is
preserved:
>>> cat = pd.Categorical(['a', 'b', 'c'], ordered=True)
>>> cat
[a, b, c]
Categories (3, object): [a < b < c]
>>> cat.map({'a': 3, 'b': 2, 'c': 1})
[3, 2, 1]
Categories (3, int64): [3 < 2 < 1]
If the mapping is not one-to-one an :class:`~pandas.Index` is returned:
>>> cat.map({'a': 'first', 'b': 'second', 'c': 'first'})
Index(['first', 'second', 'first'], dtype='object')
If a `dict` is used, all unmapped categories are mapped to `NaN` and
the result is an :class:`~pandas.Index`:
>>> cat.map({'a': 'first', 'b': 'second'})
Index(['first', 'second', nan], dtype='object')
|
[
"Map",
"categories",
"using",
"input",
"correspondence",
"(",
"dict",
"Series",
"or",
"function",
")",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/arrays/categorical.py#L1126-L1206
|
train
|
Maps the categories of the a log entry to new categories.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(1871 - 1823) + chr(1001 - 890) + '\x31' + '\x35' + chr(0b100100 + 0o14), 38838 - 38830), ehT0Px3KOsy9(chr(48) + '\157' + '\062' + '\x33' + '\065', 24040 - 24032), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\062' + '\x31' + '\x35', 60250 - 60242), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b100010 + 0o20) + '\x37' + chr(0b10101 + 0o33), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(1567 - 1518) + '\x35' + '\x34', 63465 - 63457), ehT0Px3KOsy9(chr(1364 - 1316) + '\157' + chr(0b100100 + 0o15) + chr(52) + chr(0b110100), 43647 - 43639), ehT0Px3KOsy9(chr(65 - 17) + chr(0b1001100 + 0o43) + chr(709 - 660) + chr(0b100110 + 0o15) + '\066', 9761 - 9753), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(49) + '\x35' + '\x34', 8), ehT0Px3KOsy9(chr(48) + chr(0b10011 + 0o134) + '\061' + chr(0b100100 + 0o16) + '\x34', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b10011 + 0o36) + '\x34' + chr(0b110101), ord("\x08")), ehT0Px3KOsy9(chr(0b100011 + 0o15) + '\157' + chr(0b11001 + 0o30) + chr(731 - 683) + '\063', 33352 - 33344), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(50) + chr(1212 - 1161) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(0b1 + 0o57) + '\x6f' + '\063' + '\066' + chr(0b110001 + 0o5), 0o10), ehT0Px3KOsy9('\x30' + chr(2680 - 2569) + '\x33' + chr(51) + chr(488 - 437), 0b1000), ehT0Px3KOsy9(chr(0b100111 + 0o11) + '\157' + '\065' + '\x31', 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + '\x32' + '\x37' + '\x30', 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110011) + chr(52) + chr(52), ord("\x08")), ehT0Px3KOsy9(chr(1997 - 1949) + chr(0b110111 + 0o70) + chr(0b11001 + 0o30) + '\063' + chr(0b10110 + 0o33), 0o10), ehT0Px3KOsy9(chr(0b10 + 0o56) + '\x6f' + chr(995 - 944) + '\x31' + chr(53), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(2422 - 2371) + chr(0b11010 + 0o31) + chr(48), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110011) + chr(823 - 774) + chr(1266 - 1212), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + '\x37' + '\063', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x31' + '\067' + '\062', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b111010 + 0o65) + chr(683 - 631) + chr(329 - 279), 11550 - 11542), ehT0Px3KOsy9(chr(0b10001 + 0o37) + '\157' + chr(0b110010) + chr(0b1001 + 0o54) + chr(55), 17243 - 17235), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110010) + chr(0b110001 + 0o2) + '\066', 0o10), ehT0Px3KOsy9(chr(2081 - 2033) + '\157' + '\061' + chr(0b110111) + chr(2296 - 2247), 55738 - 55730), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b11100 + 0o25) + chr(1249 - 1198) + chr(51), 0o10), ehT0Px3KOsy9('\060' + chr(3804 - 3693) + '\061' + chr(53), 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(822 - 772) + chr(0b110000) + chr(0b110111), 61863 - 61855), ehT0Px3KOsy9(chr(0b110000) + chr(0b110010 + 0o75) + chr(0b11011 + 0o27) + chr(0b1011 + 0o53) + chr(356 - 303), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(990 - 939) + '\x30' + chr(55), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b1001 + 0o52) + '\061' + '\063', 0b1000), ehT0Px3KOsy9(chr(1643 - 1595) + chr(111) + chr(1011 - 960) + chr(51) + chr(0b10110 + 0o41), 0o10), ehT0Px3KOsy9('\x30' + '\157' + '\063', 0b1000), ehT0Px3KOsy9('\x30' + chr(10203 - 10092) + chr(49) + chr(0b110010) + chr(0b110001), 29522 - 29514), ehT0Px3KOsy9(chr(2150 - 2102) + chr(11346 - 11235) + chr(0b11100 + 0o25) + '\062' + chr(0b110000), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x32' + chr(1864 - 1813) + chr(0b110010), 8), ehT0Px3KOsy9(chr(372 - 324) + chr(0b10011 + 0o134) + '\x31' + chr(2429 - 2377) + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(3481 - 3370) + '\x31' + chr(50) + '\061', 8)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(2005 - 1957) + '\x6f' + chr(53) + chr(212 - 164), 65536 - 65528)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'F'), '\144' + '\x65' + chr(7525 - 7426) + chr(111) + chr(0b1100100) + '\145')(chr(0b100000 + 0o125) + chr(13119 - 13003) + chr(0b1100110) + chr(333 - 288) + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def abA97kOQKaLo(oVre8I6UXc3b, vfywGHKHySeN):
QVK8u7RnAnpO = oVre8I6UXc3b.categories.map(vfywGHKHySeN)
try:
return xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\x0e\xef\xe2\xd53\x071\x081\x16'), '\x64' + '\145' + '\143' + chr(111) + '\144' + '\x65')(chr(10635 - 10518) + chr(0b11010 + 0o132) + '\x66' + '\x2d' + chr(56)))(xafqLlk3kkUe(oVre8I6UXc3b._codes, xafqLlk3kkUe(SXOLrMavuUCe(b'\x01\xfa\xd9\xd0$7j\x06#30\xfb'), chr(0b1010001 + 0o23) + '\145' + chr(0b1100011) + chr(111) + chr(100) + chr(9453 - 9352))(chr(117) + chr(0b1010 + 0o152) + chr(0b1100110) + chr(45) + chr(0b111000)))(), categories=QVK8u7RnAnpO, ordered=xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\x07\xef\xe9\xdd\x1e\x01:'), chr(0b1100100 + 0o0) + '\x65' + '\143' + chr(0b1011001 + 0o26) + chr(100) + chr(0b1100101))(chr(7003 - 6886) + chr(0b1000111 + 0o55) + chr(0b1100110) + chr(0b1111 + 0o36) + chr(0b11100 + 0o34))))
except q1QCh3W88sgk:
if xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b"=\xcb\xde\xd1X<\t[1'\n\xd7"), chr(0b1011000 + 0o14) + chr(101) + chr(0b1000110 + 0o35) + '\x6f' + chr(100) + chr(3093 - 2992))(chr(2782 - 2665) + chr(116) + chr(0b10110 + 0o120) + chr(0b101101 + 0o0) + chr(1579 - 1523)))(xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\x0c\xa8\xcf\xfc6.23.!0\xef'), '\144' + chr(101) + chr(0b1100011) + chr(4277 - 4166) + chr(7462 - 7362) + chr(5736 - 5635))('\x75' + '\164' + chr(2274 - 2172) + chr(558 - 513) + chr(2179 - 2123))) == -ehT0Px3KOsy9(chr(1365 - 1317) + chr(0b1101111) + chr(1001 - 952), 0o10)):
QVK8u7RnAnpO = QVK8u7RnAnpO.insert(c2A0yzQpDQB3(QVK8u7RnAnpO), WqUC3KWvYVup.nan)
return xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\x1c\xfc\xe6\xdd'), '\144' + chr(101) + '\143' + '\x6f' + '\144' + chr(0b1100101))(chr(5687 - 5570) + chr(0b1110100) + chr(0b1100101 + 0o1) + chr(0b101101) + '\070'))(QVK8u7RnAnpO, xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\x0c\xa8\xcf\xfc6.23.!0\xef'), chr(0b1100100) + '\145' + chr(99) + '\x6f' + '\x64' + chr(101))('\165' + chr(0b1110100) + '\146' + '\055' + '\070')))
|
pandas-dev/pandas
|
pandas/core/arrays/categorical.py
|
Categorical.shift
|
def shift(self, periods, fill_value=None):
"""
Shift Categorical by desired number of periods.
Parameters
----------
periods : int
Number of periods to move, can be positive or negative
fill_value : object, optional
The scalar value to use for newly introduced missing values.
.. versionadded:: 0.24.0
Returns
-------
shifted : Categorical
"""
# since categoricals always have ndim == 1, an axis parameter
# doesn't make any sense here.
codes = self.codes
if codes.ndim > 1:
raise NotImplementedError("Categorical with ndim > 1.")
if np.prod(codes.shape) and (periods != 0):
codes = np.roll(codes, ensure_platform_int(periods), axis=0)
if isna(fill_value):
fill_value = -1
elif fill_value in self.categories:
fill_value = self.categories.get_loc(fill_value)
else:
raise ValueError("'fill_value={}' is not present "
"in this Categorical's "
"categories".format(fill_value))
if periods > 0:
codes[:periods] = fill_value
else:
codes[periods:] = fill_value
return self.from_codes(codes, dtype=self.dtype)
|
python
|
def shift(self, periods, fill_value=None):
"""
Shift Categorical by desired number of periods.
Parameters
----------
periods : int
Number of periods to move, can be positive or negative
fill_value : object, optional
The scalar value to use for newly introduced missing values.
.. versionadded:: 0.24.0
Returns
-------
shifted : Categorical
"""
# since categoricals always have ndim == 1, an axis parameter
# doesn't make any sense here.
codes = self.codes
if codes.ndim > 1:
raise NotImplementedError("Categorical with ndim > 1.")
if np.prod(codes.shape) and (periods != 0):
codes = np.roll(codes, ensure_platform_int(periods), axis=0)
if isna(fill_value):
fill_value = -1
elif fill_value in self.categories:
fill_value = self.categories.get_loc(fill_value)
else:
raise ValueError("'fill_value={}' is not present "
"in this Categorical's "
"categories".format(fill_value))
if periods > 0:
codes[:periods] = fill_value
else:
codes[periods:] = fill_value
return self.from_codes(codes, dtype=self.dtype)
|
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] |
Shift Categorical by desired number of periods.
Parameters
----------
periods : int
Number of periods to move, can be positive or negative
fill_value : object, optional
The scalar value to use for newly introduced missing values.
.. versionadded:: 0.24.0
Returns
-------
shifted : Categorical
|
[
"Shift",
"Categorical",
"by",
"desired",
"number",
"of",
"periods",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/arrays/categorical.py#L1230-L1267
|
train
|
Shifts the categorical by desired number of periods.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(1882 - 1834) + '\157' + '\x33' + chr(48), 57860 - 57852), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110011) + chr(0b11001 + 0o35) + chr(54), 0o10), ehT0Px3KOsy9('\060' + '\157' + '\062' + chr(2653 - 2601), ord("\x08")), ehT0Px3KOsy9('\060' + chr(6970 - 6859) + chr(49) + '\x31' + chr(53), 5144 - 5136), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101010 + 0o5) + '\x33' + '\065' + chr(0b111 + 0o57), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(0b100111 + 0o14) + '\061' + chr(2023 - 1973), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110110) + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(1599 - 1549) + chr(51) + chr(1966 - 1914), 0o10), ehT0Px3KOsy9(chr(504 - 456) + chr(0b1101111) + '\063' + chr(0b110010) + chr(0b100110 + 0o15), 58288 - 58280), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b10001 + 0o42) + chr(0b1010 + 0o51) + chr(54), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(50) + chr(0b101110 + 0o4) + chr(48), 0o10), ehT0Px3KOsy9(chr(0b11101 + 0o23) + chr(0b1101111) + chr(0b111 + 0o54) + chr(0b110101) + '\x34', 0o10), ehT0Px3KOsy9(chr(0b1110 + 0o42) + chr(4090 - 3979) + '\x31' + '\x33', 0b1000), ehT0Px3KOsy9(chr(1556 - 1508) + chr(111) + '\x31' + chr(0b110010) + chr(0b110100), 17890 - 17882), ehT0Px3KOsy9(chr(0b1010 + 0o46) + '\157' + chr(49) + chr(0b1011 + 0o45) + chr(710 - 656), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b0 + 0o62) + '\x33' + '\x37', ord("\x08")), ehT0Px3KOsy9(chr(0b101110 + 0o2) + chr(0b1101111) + '\063' + chr(55) + '\x35', 0b1000), ehT0Px3KOsy9(chr(800 - 752) + chr(0b11110 + 0o121) + '\061' + chr(0b1010 + 0o54) + '\x35', 35131 - 35123), ehT0Px3KOsy9('\060' + '\157' + '\061' + '\067' + chr(863 - 812), 0b1000), ehT0Px3KOsy9(chr(715 - 667) + chr(0b1001111 + 0o40) + chr(50) + '\x31' + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(650 - 601) + chr(0b110100) + chr(48), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\065' + chr(53 - 5), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b10111 + 0o130) + chr(0b110001) + '\x36' + chr(53), 8), ehT0Px3KOsy9(chr(48) + chr(111) + '\063' + '\x33' + chr(0b110111), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(49) + chr(0b110111) + chr(1681 - 1633), 0o10), ehT0Px3KOsy9('\x30' + chr(111) + '\x31' + chr(55) + chr(51), 8), ehT0Px3KOsy9('\x30' + chr(9712 - 9601) + chr(1188 - 1138) + chr(0b101100 + 0o12) + chr(53), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b101010 + 0o11) + '\x31' + '\x37', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(49) + chr(0b110100) + '\061', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(1650 - 1601) + chr(451 - 402) + '\x31', ord("\x08")), ehT0Px3KOsy9(chr(1303 - 1255) + '\157' + chr(54) + '\x30', 8), ehT0Px3KOsy9('\060' + chr(111) + '\x34' + '\x35', 23238 - 23230), ehT0Px3KOsy9(chr(2207 - 2159) + '\x6f' + '\063' + '\x31' + chr(1838 - 1783), 8), ehT0Px3KOsy9('\x30' + chr(0b1100 + 0o143) + chr(0b11101 + 0o25) + '\x36' + '\x34', ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b110001) + chr(0b110111) + '\x36', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x31' + '\x30' + chr(0b100110 + 0o14), 0o10), ehT0Px3KOsy9('\060' + '\x6f' + '\063' + chr(0b100000 + 0o22) + chr(0b110010), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b100101 + 0o17) + chr(1023 - 974), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + chr(2598 - 2546) + chr(49), 8), ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(111) + '\x35' + '\x30', 8)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + '\157' + chr(1944 - 1891) + chr(0b100011 + 0o15), 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'6'), chr(0b1100100) + chr(101) + '\x63' + chr(0b1101111) + '\x64' + '\145')(chr(0b1110101) + '\164' + '\146' + '\055' + '\070') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def LnbELFj1hfyx(oVre8I6UXc3b, JSLL1jbGbEMC, RlLNSsrUm3zD=None):
AoWJEgIAbHh_ = oVre8I6UXc3b.codes
if xafqLlk3kkUe(AoWJEgIAbHh_, xafqLlk3kkUe(SXOLrMavuUCe(b'\x7f\x99y=\xa6\x88Y\xc8\xa0\xb8\xda\xb8'), '\144' + chr(0b1100101) + chr(99) + chr(129 - 18) + chr(100) + '\x65')(chr(0b111101 + 0o70) + chr(559 - 443) + chr(7739 - 7637) + '\055' + chr(56))) > ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b101100 + 0o5), 48328 - 48320):
raise _zJ24Vce7wp0(xafqLlk3kkUe(SXOLrMavuUCe(b'[\x97`(\x89\xa5B\xf5\xb0\xbf\xfc\xcc|=2\xf7\xdd\x1b\x1f\xe6\r\x08K\xffIU'), chr(6837 - 6737) + '\x65' + chr(0b1100011) + chr(0b11010 + 0o125) + chr(0b1011100 + 0o10) + chr(101))('\x75' + '\164' + chr(102) + chr(0b101101) + '\x38'))
if xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b't\xb4M&\xd9\xf3\\\xa8\x9d\xb5\xa8\x84'), '\x64' + chr(4581 - 4480) + chr(0b1 + 0o142) + '\x6f' + chr(0b1100100) + chr(0b1100101))(chr(117) + chr(0b1110100) + '\146' + chr(0b101101) + '\x38'))(xafqLlk3kkUe(AoWJEgIAbHh_, xafqLlk3kkUe(SXOLrMavuUCe(b'k\x9eu=\x8b'), '\144' + chr(0b10110 + 0o117) + chr(99) + chr(0b111001 + 0o66) + chr(100) + '\145')(chr(6205 - 6088) + chr(0b1110100) + chr(0b1100110) + '\055' + chr(0b111000)))) and JSLL1jbGbEMC != ehT0Px3KOsy9('\x30' + chr(0b100110 + 0o111) + '\060', ord("\x08")):
AoWJEgIAbHh_ = WqUC3KWvYVup.roll(AoWJEgIAbHh_, lMS4d2uXyrnw(JSLL1jbGbEMC), axis=ehT0Px3KOsy9('\060' + '\157' + chr(505 - 457), 8))
if yBUx5qcFiTz6(RlLNSsrUm3zD):
RlLNSsrUm3zD = -ehT0Px3KOsy9(chr(181 - 133) + chr(6827 - 6716) + chr(1369 - 1320), 8)
elif RlLNSsrUm3zD in xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'u\xacN\t\xaf\x9e\x04\xa5\x86\xa4\xd1\x8e'), '\x64' + '\145' + chr(0b1100011) + chr(111) + chr(2190 - 2090) + chr(8905 - 8804))(chr(0b1001110 + 0o47) + chr(116) + chr(0b1011100 + 0o12) + chr(45) + '\070')):
RlLNSsrUm3zD = oVre8I6UXc3b.categories.get_loc(RlLNSsrUm3zD)
else:
raise q1QCh3W88sgk(xafqLlk3kkUe(xafqLlk3kkUe(SXOLrMavuUCe(b"?\x90}!\x82\x95F\xfd\xbf\xab\xf5\xd1p)a\xbf\x94\x06[\xe1\x0f\\U\xaf\n\x1e\xc6\xaa\x0f=\x10L\xa1\x94\n*\xbbR\x01ky\x82q*\x81\xb8Y\xff\xb2\xb2\xb7\x9f+7'\xeb\x98\x12\x14\xfd\tM\x06"), chr(100) + chr(0b11 + 0o142) + chr(99) + chr(111) + '\144' + '\145')(chr(4854 - 4737) + chr(0b1000101 + 0o57) + chr(0b1100110) + chr(985 - 940) + '\070'), xafqLlk3kkUe(SXOLrMavuUCe(b'~\x99f \x8f\xbe'), chr(100) + '\145' + chr(99) + chr(0b1101111) + chr(100) + chr(0b111100 + 0o51))('\x75' + chr(0b1000101 + 0o57) + '\146' + '\055' + '\070'))(RlLNSsrUm3zD))
if JSLL1jbGbEMC > ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(48), 8):
AoWJEgIAbHh_[:JSLL1jbGbEMC] = RlLNSsrUm3zD
else:
AoWJEgIAbHh_[JSLL1jbGbEMC:] = RlLNSsrUm3zD
return xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'~\x84{ \xb1\xa9_\xf8\xb6\xad'), chr(100) + chr(9946 - 9845) + '\x63' + chr(111) + chr(4738 - 4638) + '\145')(chr(0b1110101) + chr(0b1110100) + chr(102) + chr(0b101001 + 0o4) + chr(0b0 + 0o70)))(AoWJEgIAbHh_, dtype=xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'|\x82m=\x8b'), '\144' + chr(0b110011 + 0o62) + chr(8095 - 7996) + chr(0b1101111) + chr(100) + '\145')(chr(0b1110101) + '\x74' + '\146' + '\055' + chr(388 - 332))))
|
pandas-dev/pandas
|
pandas/core/arrays/categorical.py
|
Categorical.memory_usage
|
def memory_usage(self, deep=False):
"""
Memory usage of my values
Parameters
----------
deep : bool
Introspect the data deeply, interrogate
`object` dtypes for system-level memory consumption
Returns
-------
bytes used
Notes
-----
Memory usage does not include memory consumed by elements that
are not components of the array if deep=False
See Also
--------
numpy.ndarray.nbytes
"""
return self._codes.nbytes + self.dtype.categories.memory_usage(
deep=deep)
|
python
|
def memory_usage(self, deep=False):
"""
Memory usage of my values
Parameters
----------
deep : bool
Introspect the data deeply, interrogate
`object` dtypes for system-level memory consumption
Returns
-------
bytes used
Notes
-----
Memory usage does not include memory consumed by elements that
are not components of the array if deep=False
See Also
--------
numpy.ndarray.nbytes
"""
return self._codes.nbytes + self.dtype.categories.memory_usage(
deep=deep)
|
[
"def",
"memory_usage",
"(",
"self",
",",
"deep",
"=",
"False",
")",
":",
"return",
"self",
".",
"_codes",
".",
"nbytes",
"+",
"self",
".",
"dtype",
".",
"categories",
".",
"memory_usage",
"(",
"deep",
"=",
"deep",
")"
] |
Memory usage of my values
Parameters
----------
deep : bool
Introspect the data deeply, interrogate
`object` dtypes for system-level memory consumption
Returns
-------
bytes used
Notes
-----
Memory usage does not include memory consumed by elements that
are not components of the array if deep=False
See Also
--------
numpy.ndarray.nbytes
|
[
"Memory",
"usage",
"of",
"my",
"values"
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/arrays/categorical.py#L1331-L1355
|
train
|
Return the memory usage of the object.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b10101 + 0o35) + '\064' + chr(0b101100 + 0o13), 0o10), ehT0Px3KOsy9(chr(463 - 415) + chr(111) + '\x33' + chr(157 - 108) + '\x31', 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110010) + chr(1484 - 1433) + '\x37', ord("\x08")), ehT0Px3KOsy9(chr(388 - 340) + chr(8888 - 8777) + '\063' + chr(52) + chr(580 - 532), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(4869 - 4758) + chr(0b110010) + '\063' + chr(1151 - 1097), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(49) + '\x31' + chr(1290 - 1235), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101001 + 0o6) + chr(0b110001) + chr(0b110011), 0o10), ehT0Px3KOsy9(chr(783 - 735) + chr(0b1101111) + chr(1075 - 1023) + chr(0b11010 + 0o27), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(869 - 818) + chr(1212 - 1158) + chr(0b110001 + 0o1), 0b1000), ehT0Px3KOsy9('\x30' + chr(7474 - 7363) + chr(0b110001) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(9232 - 9121) + chr(55), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b110011) + '\x35', 0o10), ehT0Px3KOsy9('\060' + chr(0b10111 + 0o130) + '\062' + chr(54) + chr(0b110010), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b100001 + 0o20) + chr(1170 - 1122) + chr(0b11 + 0o64), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + '\x33' + '\060' + '\062', 0o10), ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(0b1010011 + 0o34) + chr(1247 - 1196) + chr(1050 - 995) + '\063', 0b1000), ehT0Px3KOsy9(chr(0b101100 + 0o4) + chr(0b1 + 0o156) + chr(0b110001) + chr(2165 - 2117) + chr(0b101 + 0o55), 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(0b110111) + '\061', ord("\x08")), ehT0Px3KOsy9(chr(0b101010 + 0o6) + chr(5268 - 5157) + '\x33' + '\064' + '\x33', 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110010) + '\x34' + chr(0b110001), 0b1000), ehT0Px3KOsy9(chr(0b101101 + 0o3) + chr(0b1101111) + '\x31' + '\062', 18790 - 18782), ehT0Px3KOsy9(chr(1172 - 1124) + '\157' + '\062' + chr(0b100001 + 0o22) + chr(2104 - 2049), 8), ehT0Px3KOsy9('\060' + chr(0b11010 + 0o125) + '\065' + chr(52), 0b1000), ehT0Px3KOsy9('\060' + chr(111) + chr(0b11001 + 0o36) + '\x32', 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110010) + chr(0b110010) + chr(54), 8287 - 8279), ehT0Px3KOsy9(chr(0b11100 + 0o24) + chr(0b1101111 + 0o0) + chr(1503 - 1453) + chr(1571 - 1518), 0o10), ehT0Px3KOsy9(chr(0b1010 + 0o46) + '\157' + chr(0b110011) + chr(52) + '\066', 0b1000), ehT0Px3KOsy9(chr(2112 - 2064) + chr(3988 - 3877) + chr(0b110001) + chr(2686 - 2631) + chr(48), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(2144 - 2094) + chr(0b101010 + 0o11) + chr(0b110111), 8), ehT0Px3KOsy9(chr(964 - 916) + chr(0b1100011 + 0o14) + '\x33' + chr(49) + '\062', ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110011) + '\x37' + chr(407 - 352), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1110 + 0o141) + chr(1454 - 1403) + chr(0b110101) + chr(51), ord("\x08")), ehT0Px3KOsy9(chr(0b10011 + 0o35) + chr(0b1101111) + chr(0b110101) + '\061', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1001110 + 0o41) + '\063' + chr(0b110001) + chr(1088 - 1039), 8), ehT0Px3KOsy9(chr(0b1010 + 0o46) + chr(0b1101111) + chr(0b110110) + chr(0b110100), 0b1000), ehT0Px3KOsy9(chr(2158 - 2110) + chr(0b1101111) + chr(0b110110) + '\x32', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\067' + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(48) + chr(6637 - 6526) + '\063' + chr(54) + '\x31', 2732 - 2724), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110001) + chr(1271 - 1220), 8), ehT0Px3KOsy9('\060' + '\157' + chr(50) + chr(0b110000) + '\x33', 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b1011 + 0o45) + '\x6f' + '\x35' + chr(671 - 623), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x89'), chr(1005 - 905) + '\x65' + '\x63' + '\x6f' + '\x64' + '\x65')('\x75' + '\x74' + chr(6885 - 6783) + chr(1180 - 1135) + chr(56)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def tEc7cnZjmQru(oVre8I6UXc3b, _JgLpamLTDEN=ehT0Px3KOsy9('\x30' + chr(0b1101111 + 0o0) + '\060', 0o10)):
return xafqLlk3kkUe(oVre8I6UXc3b._codes, xafqLlk3kkUe(SXOLrMavuUCe(b'\xc9\xab\xe6\x94\xfb<'), chr(8631 - 8531) + '\x65' + chr(0b1100011) + chr(0b1101111) + chr(0b1100100) + chr(0b1010110 + 0o17))('\165' + chr(0b1110100) + chr(0b10000 + 0o126) + chr(1534 - 1489) + chr(56))) + xafqLlk3kkUe(oVre8I6UXc3b.dtype.categories, xafqLlk3kkUe(SXOLrMavuUCe(b'\xca\xac\xf2\x8f\xec6TT\x81i`x'), '\x64' + chr(8844 - 8743) + chr(0b1100011) + '\157' + '\x64' + '\145')(chr(117) + chr(8409 - 8293) + chr(0b100110 + 0o100) + '\x2d' + '\x38'))(deep=_JgLpamLTDEN)
|
pandas-dev/pandas
|
pandas/core/arrays/categorical.py
|
Categorical.value_counts
|
def value_counts(self, dropna=True):
"""
Return a Series containing counts of each category.
Every category will have an entry, even those with a count of 0.
Parameters
----------
dropna : bool, default True
Don't include counts of NaN.
Returns
-------
counts : Series
See Also
--------
Series.value_counts
"""
from numpy import bincount
from pandas import Series, CategoricalIndex
code, cat = self._codes, self.categories
ncat, mask = len(cat), 0 <= code
ix, clean = np.arange(ncat), mask.all()
if dropna or clean:
obs = code if clean else code[mask]
count = bincount(obs, minlength=ncat or None)
else:
count = bincount(np.where(mask, code, ncat))
ix = np.append(ix, -1)
ix = self._constructor(ix, dtype=self.dtype,
fastpath=True)
return Series(count, index=CategoricalIndex(ix), dtype='int64')
|
python
|
def value_counts(self, dropna=True):
"""
Return a Series containing counts of each category.
Every category will have an entry, even those with a count of 0.
Parameters
----------
dropna : bool, default True
Don't include counts of NaN.
Returns
-------
counts : Series
See Also
--------
Series.value_counts
"""
from numpy import bincount
from pandas import Series, CategoricalIndex
code, cat = self._codes, self.categories
ncat, mask = len(cat), 0 <= code
ix, clean = np.arange(ncat), mask.all()
if dropna or clean:
obs = code if clean else code[mask]
count = bincount(obs, minlength=ncat or None)
else:
count = bincount(np.where(mask, code, ncat))
ix = np.append(ix, -1)
ix = self._constructor(ix, dtype=self.dtype,
fastpath=True)
return Series(count, index=CategoricalIndex(ix), dtype='int64')
|
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] |
Return a Series containing counts of each category.
Every category will have an entry, even those with a count of 0.
Parameters
----------
dropna : bool, default True
Don't include counts of NaN.
Returns
-------
counts : Series
See Also
--------
Series.value_counts
|
[
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] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/arrays/categorical.py#L1438-L1475
|
train
|
Return a Series containing counts of each category.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(2034 - 1984) + '\064' + '\063', ord("\x08")), ehT0Px3KOsy9(chr(1610 - 1562) + '\157' + chr(0b101101 + 0o7) + chr(2246 - 2194), 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(50) + chr(2251 - 2198) + chr(0b11111 + 0o24), 0b1000), ehT0Px3KOsy9(chr(1695 - 1647) + chr(111) + chr(0b110001) + '\060' + '\x31', 0b1000), ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(111) + chr(51) + chr(52) + '\061', 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(51) + '\x34' + chr(0b110000 + 0o6), ord("\x08")), ehT0Px3KOsy9('\060' + '\157' + chr(0b110 + 0o54) + chr(0b110001 + 0o1) + chr(51), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(11791 - 11680) + chr(50) + chr(0b110110) + chr(262 - 208), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(1731 - 1682) + chr(0b110101) + '\060', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110000 + 0o1) + chr(303 - 249) + chr(2595 - 2542), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b10111 + 0o33) + chr(0b110111), 0o10), ehT0Px3KOsy9('\060' + chr(5707 - 5596) + chr(0b0 + 0o61) + chr(505 - 451) + '\061', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(12187 - 12076) + chr(50) + '\061' + chr(55), 0o10), ehT0Px3KOsy9(chr(0b1110 + 0o42) + '\157' + '\x32' + chr(0b110111) + chr(0b110001), 26028 - 26020), ehT0Px3KOsy9('\x30' + '\157' + '\062' + chr(0b110101) + chr(1958 - 1907), 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101011 + 0o4) + chr(1134 - 1085) + chr(0b100011 + 0o16) + '\060', 44740 - 44732), ehT0Px3KOsy9(chr(0b100100 + 0o14) + '\x6f' + '\x31' + '\x33' + chr(48), 0o10), ehT0Px3KOsy9(chr(1198 - 1150) + chr(0b1101111) + chr(841 - 790) + chr(529 - 474) + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b100101 + 0o112) + chr(0b110010) + '\066' + '\x30', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b100000 + 0o24), 0o10), ehT0Px3KOsy9(chr(48) + chr(7054 - 6943) + chr(0b10 + 0o60) + '\x36' + chr(0b100010 + 0o20), 0o10), ehT0Px3KOsy9(chr(0b1 + 0o57) + chr(111) + chr(0b101101 + 0o4) + chr(0b10011 + 0o43) + chr(49), 8), ehT0Px3KOsy9(chr(0b11010 + 0o26) + '\157' + chr(0b11100 + 0o27) + chr(0b1 + 0o60) + chr(48), 0o10), ehT0Px3KOsy9(chr(0b11101 + 0o23) + '\x6f' + '\x33' + chr(0b110001) + chr(0b100010 + 0o24), 31522 - 31514), ehT0Px3KOsy9(chr(0b101 + 0o53) + '\157' + chr(0b110001) + chr(55), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b100010 + 0o21) + '\x30' + chr(655 - 605), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(0b11001 + 0o30) + chr(0b110110) + chr(275 - 227), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x32' + chr(0b11010 + 0o33) + chr(0b11101 + 0o26), 8), ehT0Px3KOsy9(chr(48) + chr(6529 - 6418) + '\x33' + '\066', 0o10), ehT0Px3KOsy9('\060' + '\157' + '\063' + chr(1701 - 1648), 0o10), ehT0Px3KOsy9(chr(1245 - 1197) + chr(253 - 142) + chr(1980 - 1931) + '\060' + '\066', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b100001 + 0o21) + '\063' + chr(0b110100), ord("\x08")), ehT0Px3KOsy9('\x30' + '\157' + '\x36' + chr(0b1000 + 0o51), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1000101 + 0o52) + chr(51) + chr(0b110001), ord("\x08")), ehT0Px3KOsy9(chr(211 - 163) + '\157' + chr(49) + '\x33' + chr(54), ord("\x08")), ehT0Px3KOsy9(chr(2230 - 2182) + chr(979 - 868) + chr(0b110010) + chr(363 - 309) + chr(0b101011 + 0o6), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(49) + chr(0b110101) + chr(0b110000), 8), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b100011 + 0o20) + chr(0b11 + 0o63) + chr(48), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b100100 + 0o113) + '\062' + chr(51) + chr(0b110111), 46424 - 46416), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110010) + chr(0b110001) + chr(2093 - 2045), 63350 - 63342)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x35' + chr(48), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x8d'), chr(0b1001100 + 0o30) + chr(2033 - 1932) + chr(4228 - 4129) + chr(11434 - 11323) + chr(100) + chr(0b1100100 + 0o1))('\165' + '\x74' + chr(102) + '\x2d' + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def IQY9HknPWsi9(oVre8I6UXc3b, _zTUd6XPn3WJ=ehT0Px3KOsy9('\060' + '\x6f' + chr(0b100001 + 0o20), 0o10)):
(Ac06e2ekmtL0,) = (xafqLlk3kkUe(NPPHb59961Bv(xafqLlk3kkUe(SXOLrMavuUCe(b'\xcdQ\xc61\x98'), '\x64' + chr(0b1100101) + chr(6551 - 6452) + '\x6f' + chr(100) + chr(0b1100101))(chr(0b1110101) + '\x74' + '\146' + chr(0b10101 + 0o30) + chr(1840 - 1784)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xc1M\xc5"\x8e\x93\xfd\xc2'), chr(4084 - 3984) + '\x65' + chr(0b1100011) + '\157' + chr(0b1100100) + chr(101))('\165' + chr(116) + chr(0b11000 + 0o116) + chr(0b101101) + chr(0b111000))), xafqLlk3kkUe(SXOLrMavuUCe(b'\xc1M\xc5"\x8e\x93\xfd\xc2'), '\144' + '\x65' + chr(8544 - 8445) + chr(5405 - 5294) + chr(6098 - 5998) + chr(0b1100101 + 0o0))(chr(0b1101101 + 0o10) + chr(116) + chr(102) + '\055' + '\070')),)
(I9PbrFvU4NYI, YH_C7u76pUaX) = (xafqLlk3kkUe(NPPHb59961Bv(xafqLlk3kkUe(SXOLrMavuUCe(b'\xd3E\xc5%\x80\x95'), chr(0b1100100) + chr(184 - 83) + chr(99) + chr(111) + '\x64' + chr(0b1000011 + 0o42))(chr(0b1101100 + 0o11) + '\164' + chr(102) + '\x2d' + chr(0b10 + 0o66)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xf0A\xd9(\x84\x95'), chr(0b111111 + 0o45) + '\x65' + '\143' + '\157' + chr(0b1100100) + chr(7859 - 7758))(chr(0b101011 + 0o112) + chr(0b1101010 + 0o12) + '\146' + '\055' + chr(0b111000))), xafqLlk3kkUe(SXOLrMavuUCe(b'\xf0A\xd9(\x84\x95'), '\x64' + chr(0b1100101) + chr(99) + chr(5553 - 5442) + chr(100) + chr(6921 - 6820))(chr(13347 - 13230) + chr(0b1110100) + '\x66' + '\x2d' + '\x38')), xafqLlk3kkUe(NPPHb59961Bv(xafqLlk3kkUe(SXOLrMavuUCe(b'\xd3E\xc5%\x80\x95'), chr(855 - 755) + chr(0b10001 + 0o124) + chr(0b10101 + 0o116) + '\x6f' + '\x64' + chr(0b1100101))(chr(6424 - 6307) + '\x74' + '\x66' + chr(45) + chr(0b111000)), xafqLlk3kkUe(SXOLrMavuUCe(b'\xe0E\xdf$\x86\x89\xe1\xdf\x0b\x14{8\xe1\xdd\xce0'), chr(0b11001 + 0o113) + chr(101) + chr(0b1111 + 0o124) + chr(7257 - 7146) + chr(5093 - 4993) + chr(101))(chr(117) + chr(3854 - 3738) + chr(0b1100110) + chr(0b101101) + chr(0b101110 + 0o12))), xafqLlk3kkUe(SXOLrMavuUCe(b'\xe0E\xdf$\x86\x89\xe1\xdf\x0b\x14{8\xe1\xdd\xce0'), chr(0b101110 + 0o66) + chr(0b11111 + 0o106) + chr(4545 - 4446) + '\157' + chr(100) + chr(0b1100101))(chr(0b1001101 + 0o50) + chr(0b1110100) + '\146' + chr(0b101101) + '\070')))
(ZWRNGxZ3R69y, re0VVGAVKu27) = (oVre8I6UXc3b.d5BDZJl_zDsu, oVre8I6UXc3b.mZZDAT49UzAb)
(ZoAjWXCPp5ln, Iz1jSgUKZDvt) = (c2A0yzQpDQB3(re0VVGAVKu27), ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(0b1000101 + 0o52) + chr(1712 - 1664), ord("\x08")) <= ZWRNGxZ3R69y)
(NhWUxmSUCcoW, pFP9VDRQF23q) = (WqUC3KWvYVup.arange(ZoAjWXCPp5ln), Iz1jSgUKZDvt.Dl48nj1rbi23())
if _zTUd6XPn3WJ or pFP9VDRQF23q:
HUAx0lWcwxPP = ZWRNGxZ3R69y if pFP9VDRQF23q else ZWRNGxZ3R69y[Iz1jSgUKZDvt]
ualWdDeXJEGO = Ac06e2ekmtL0(HUAx0lWcwxPP, minlength=ZoAjWXCPp5ln or None)
else:
ualWdDeXJEGO = Ac06e2ekmtL0(WqUC3KWvYVup.dRFAC59yQBm_(Iz1jSgUKZDvt, ZWRNGxZ3R69y, ZoAjWXCPp5ln))
NhWUxmSUCcoW = WqUC3KWvYVup.append(NhWUxmSUCcoW, -ehT0Px3KOsy9(chr(0b110000 + 0o0) + chr(10006 - 9895) + chr(49), 8))
NhWUxmSUCcoW = oVre8I6UXc3b._constructor(NhWUxmSUCcoW, dtype=oVre8I6UXc3b.dtype, fastpath=ehT0Px3KOsy9(chr(569 - 521) + chr(0b1101111) + chr(0b110001), 8))
return I9PbrFvU4NYI(ualWdDeXJEGO, index=YH_C7u76pUaX(NhWUxmSUCcoW), dtype=xafqLlk3kkUe(SXOLrMavuUCe(b'\xcaJ\xdfw\xd5'), chr(5188 - 5088) + chr(5840 - 5739) + chr(99) + '\x6f' + chr(0b1100100) + '\x65')(chr(2632 - 2515) + chr(0b100110 + 0o116) + chr(102) + '\x2d' + '\x38'))
|
pandas-dev/pandas
|
pandas/core/arrays/categorical.py
|
Categorical.get_values
|
def get_values(self):
"""
Return the values.
For internal compatibility with pandas formatting.
Returns
-------
numpy.array
A numpy array of the same dtype as categorical.categories.dtype or
Index if datetime / periods.
"""
# if we are a datetime and period index, return Index to keep metadata
if is_datetimelike(self.categories):
return self.categories.take(self._codes, fill_value=np.nan)
elif is_integer_dtype(self.categories) and -1 in self._codes:
return self.categories.astype("object").take(self._codes,
fill_value=np.nan)
return np.array(self)
|
python
|
def get_values(self):
"""
Return the values.
For internal compatibility with pandas formatting.
Returns
-------
numpy.array
A numpy array of the same dtype as categorical.categories.dtype or
Index if datetime / periods.
"""
# if we are a datetime and period index, return Index to keep metadata
if is_datetimelike(self.categories):
return self.categories.take(self._codes, fill_value=np.nan)
elif is_integer_dtype(self.categories) and -1 in self._codes:
return self.categories.astype("object").take(self._codes,
fill_value=np.nan)
return np.array(self)
|
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] |
Return the values.
For internal compatibility with pandas formatting.
Returns
-------
numpy.array
A numpy array of the same dtype as categorical.categories.dtype or
Index if datetime / periods.
|
[
"Return",
"the",
"values",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/arrays/categorical.py#L1477-L1495
|
train
|
Return the values of the object as numpy array.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b1100 + 0o44) + chr(0b1010110 + 0o31) + chr(0b110001) + chr(0b110101) + chr(0b110100), 0o10), ehT0Px3KOsy9('\x30' + chr(0b111110 + 0o61) + chr(0b110001) + '\066' + chr(764 - 715), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(0b110011) + chr(50) + chr(0b1101 + 0o46), ord("\x08")), ehT0Px3KOsy9(chr(2073 - 2025) + chr(0b1101111) + chr(0b110011) + chr(50) + chr(55), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b10 + 0o61) + '\065' + chr(0b110 + 0o55), 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(49) + '\064' + chr(0b11000 + 0o37), 19753 - 19745), ehT0Px3KOsy9(chr(2253 - 2205) + chr(0b1101111) + '\063' + chr(0b11101 + 0o31) + '\067', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\066' + chr(0b11110 + 0o27), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\063' + chr(55) + chr(55), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(383 - 332) + chr(2220 - 2172) + chr(0b100 + 0o60), 4321 - 4313), ehT0Px3KOsy9('\060' + chr(111) + chr(0b10101 + 0o35) + chr(0b110010) + '\067', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1100 + 0o143) + chr(0b110011) + chr(0b110100) + chr(0b110010 + 0o5), 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1100010 + 0o15) + '\x32' + chr(0b100110 + 0o16), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\064' + '\061', 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(0b110001) + chr(53) + chr(1837 - 1787), 10526 - 10518), ehT0Px3KOsy9('\060' + chr(0b1011100 + 0o23) + chr(49) + chr(0b1110 + 0o43) + chr(54), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110001) + '\067' + '\064', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1001011 + 0o44) + chr(0b110001) + chr(493 - 445) + '\x33', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1011110 + 0o21) + chr(759 - 708) + chr(1802 - 1750) + chr(48), ord("\x08")), ehT0Px3KOsy9(chr(0b1000 + 0o50) + chr(111) + chr(0b101 + 0o54) + chr(1712 - 1660) + chr(0b10100 + 0o40), ord("\x08")), ehT0Px3KOsy9(chr(0b11 + 0o55) + '\x6f' + chr(0b110001), 61073 - 61065), ehT0Px3KOsy9(chr(563 - 515) + '\157' + chr(0b11110 + 0o25) + chr(48) + chr(0b110001), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110001) + '\x33' + chr(2152 - 2103), 0o10), ehT0Px3KOsy9(chr(926 - 878) + chr(0b1011101 + 0o22) + chr(0b11101 + 0o27) + '\x33', 0b1000), ehT0Px3KOsy9(chr(0b101010 + 0o6) + chr(111) + chr(49) + '\063' + chr(0b10 + 0o65), 0o10), ehT0Px3KOsy9(chr(0b100110 + 0o12) + '\x6f' + '\x31' + '\067' + chr(2452 - 2399), 19760 - 19752), ehT0Px3KOsy9('\x30' + '\157' + chr(494 - 440) + chr(0b101101 + 0o12), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1010011 + 0o34) + chr(439 - 390) + '\064' + chr(0b110111), 8), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(2171 - 2120) + chr(0b110100), ord("\x08")), ehT0Px3KOsy9('\060' + chr(10845 - 10734) + chr(51) + chr(0b110100) + '\x32', 22365 - 22357), ehT0Px3KOsy9(chr(736 - 688) + chr(0b1011101 + 0o22) + '\x32' + '\x36' + '\067', 35786 - 35778), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\061' + '\x30' + '\x33', 8), ehT0Px3KOsy9(chr(1963 - 1915) + '\x6f' + chr(410 - 360) + chr(55) + '\063', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(1434 - 1383) + '\064' + chr(1399 - 1344), 8), ehT0Px3KOsy9(chr(1615 - 1567) + chr(0b1101111) + '\067' + '\x33', 0o10), ehT0Px3KOsy9(chr(1294 - 1246) + chr(0b1001001 + 0o46) + '\x33' + chr(1892 - 1844) + '\067', 0o10), ehT0Px3KOsy9(chr(0b11110 + 0o22) + chr(0b1101111 + 0o0) + chr(1193 - 1140) + '\061', ord("\x08")), ehT0Px3KOsy9(chr(586 - 538) + chr(0b1101111) + chr(0b10100 + 0o37) + chr(0b110101) + chr(0b110001), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\063' + '\064', 8), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b1 + 0o61) + chr(53) + '\x31', 45121 - 45113)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(0b10110 + 0o32) + chr(0b1101111) + chr(53) + '\x30', 32860 - 32852)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'B'), chr(0b1011000 + 0o14) + chr(101) + chr(0b1100011) + chr(111) + chr(100) + chr(101))(chr(13684 - 13567) + '\164' + '\146' + '\055' + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def vF9j7cOSuwTo(oVre8I6UXc3b):
if PUcfBsFlCjpH(xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\x01+\x89\x93\xaa3\xc3\x0c\xaa\xbe\xd6\x85'), chr(100) + '\145' + '\x63' + chr(1710 - 1599) + chr(0b1100100) + '\145')('\x75' + chr(0b1111 + 0o145) + '\146' + chr(0b101101) + chr(0b100111 + 0o21)))):
return xafqLlk3kkUe(oVre8I6UXc3b.categories, xafqLlk3kkUe(SXOLrMavuUCe(b'\x18\x10\xb8\xb2'), chr(0b1100100) + chr(101) + chr(99) + chr(111) + chr(100) + '\145')(chr(0b1110101) + chr(116) + chr(0b11011 + 0o113) + chr(0b101101) + chr(2775 - 2719)))(xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\x08D\x91\x93\xb1-\x9bj\x85\x80\xe4\x92'), chr(100) + chr(0b1100101) + chr(5486 - 5387) + chr(111) + chr(0b100110 + 0o76) + '\x65')(chr(117) + '\x74' + chr(0b110 + 0o140) + '\055' + chr(0b111000))), fill_value=xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\x02\x10\xbd'), chr(100) + chr(0b1100101) + '\143' + chr(0b10000 + 0o137) + chr(0b1011 + 0o131) + '\145')(chr(117) + chr(0b1110100) + '\x66' + '\x2d' + chr(0b10101 + 0o43))))
elif vbqhcY5kX820(xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\x01+\x89\x93\xaa3\xc3\x0c\xaa\xbe\xd6\x85'), chr(0b1100100) + chr(0b1100101) + '\143' + '\x6f' + '\144' + chr(0b1100101))(chr(117) + chr(7311 - 7195) + chr(0b1100110 + 0o0) + chr(1209 - 1164) + chr(0b111000)))) and -ehT0Px3KOsy9(chr(48) + chr(0b10101 + 0o132) + '\x31', 8) in xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\x08D\x91\x93\xb1-\x9bj\x85\x80\xe4\x92'), chr(0b100110 + 0o76) + '\x65' + '\x63' + '\x6f' + '\x64' + '\x65')(chr(0b1110101) + '\164' + chr(0b1011010 + 0o14) + chr(45) + chr(320 - 264))):
return xafqLlk3kkUe(oVre8I6UXc3b.categories.astype(xafqLlk3kkUe(SXOLrMavuUCe(b'\x03\x13\xb9\xb2\x88\x13'), chr(0b101010 + 0o72) + '\145' + '\143' + '\157' + chr(0b1100100) + '\145')('\x75' + chr(0b1110100) + chr(0b1100110) + chr(0b101101) + chr(56))), xafqLlk3kkUe(SXOLrMavuUCe(b'\x18\x10\xb8\xb2'), chr(0b1100100) + '\145' + chr(99) + chr(0b1101111) + '\144' + chr(7710 - 7609))(chr(11618 - 11501) + '\164' + chr(1428 - 1326) + chr(1352 - 1307) + chr(0b111000)))(xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\x08D\x91\x93\xb1-\x9bj\x85\x80\xe4\x92'), chr(100) + chr(0b111 + 0o136) + chr(0b1100011) + chr(0b1101111) + chr(4034 - 3934) + chr(6743 - 6642))(chr(117) + chr(116) + chr(102) + '\x2d' + chr(786 - 730))), fill_value=xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\x02\x10\xbd'), chr(100) + chr(0b1010101 + 0o20) + chr(99) + chr(9422 - 9311) + '\x64' + chr(101))(chr(0b1110101) + chr(3352 - 3236) + '\146' + chr(0b100101 + 0o10) + chr(56))))
return xafqLlk3kkUe(WqUC3KWvYVup, xafqLlk3kkUe(SXOLrMavuUCe(b'\r\x03\xa1\xb6\x92'), chr(5670 - 5570) + '\145' + chr(0b1011010 + 0o11) + '\157' + '\x64' + '\x65')(chr(117) + chr(0b1110010 + 0o2) + chr(0b1100110) + chr(45) + '\x38'))(oVre8I6UXc3b)
|
pandas-dev/pandas
|
pandas/core/arrays/categorical.py
|
Categorical.sort_values
|
def sort_values(self, inplace=False, ascending=True, na_position='last'):
"""
Sort the Categorical by category value returning a new
Categorical by default.
While an ordering is applied to the category values, sorting in this
context refers more to organizing and grouping together based on
matching category values. Thus, this function can be called on an
unordered Categorical instance unlike the functions 'Categorical.min'
and 'Categorical.max'.
Parameters
----------
inplace : bool, default False
Do operation in place.
ascending : bool, default True
Order ascending. Passing False orders descending. The
ordering parameter provides the method by which the
category values are organized.
na_position : {'first', 'last'} (optional, default='last')
'first' puts NaNs at the beginning
'last' puts NaNs at the end
Returns
-------
Categorical or None
See Also
--------
Categorical.sort
Series.sort_values
Examples
--------
>>> c = pd.Categorical([1, 2, 2, 1, 5])
>>> c
[1, 2, 2, 1, 5]
Categories (3, int64): [1, 2, 5]
>>> c.sort_values()
[1, 1, 2, 2, 5]
Categories (3, int64): [1, 2, 5]
>>> c.sort_values(ascending=False)
[5, 2, 2, 1, 1]
Categories (3, int64): [1, 2, 5]
Inplace sorting can be done as well:
>>> c.sort_values(inplace=True)
>>> c
[1, 1, 2, 2, 5]
Categories (3, int64): [1, 2, 5]
>>>
>>> c = pd.Categorical([1, 2, 2, 1, 5])
'sort_values' behaviour with NaNs. Note that 'na_position'
is independent of the 'ascending' parameter:
>>> c = pd.Categorical([np.nan, 2, 2, np.nan, 5])
>>> c
[NaN, 2.0, 2.0, NaN, 5.0]
Categories (2, int64): [2, 5]
>>> c.sort_values()
[2.0, 2.0, 5.0, NaN, NaN]
Categories (2, int64): [2, 5]
>>> c.sort_values(ascending=False)
[5.0, 2.0, 2.0, NaN, NaN]
Categories (2, int64): [2, 5]
>>> c.sort_values(na_position='first')
[NaN, NaN, 2.0, 2.0, 5.0]
Categories (2, int64): [2, 5]
>>> c.sort_values(ascending=False, na_position='first')
[NaN, NaN, 5.0, 2.0, 2.0]
Categories (2, int64): [2, 5]
"""
inplace = validate_bool_kwarg(inplace, 'inplace')
if na_position not in ['last', 'first']:
msg = 'invalid na_position: {na_position!r}'
raise ValueError(msg.format(na_position=na_position))
sorted_idx = nargsort(self,
ascending=ascending,
na_position=na_position)
if inplace:
self._codes = self._codes[sorted_idx]
else:
return self._constructor(values=self._codes[sorted_idx],
dtype=self.dtype,
fastpath=True)
|
python
|
def sort_values(self, inplace=False, ascending=True, na_position='last'):
"""
Sort the Categorical by category value returning a new
Categorical by default.
While an ordering is applied to the category values, sorting in this
context refers more to organizing and grouping together based on
matching category values. Thus, this function can be called on an
unordered Categorical instance unlike the functions 'Categorical.min'
and 'Categorical.max'.
Parameters
----------
inplace : bool, default False
Do operation in place.
ascending : bool, default True
Order ascending. Passing False orders descending. The
ordering parameter provides the method by which the
category values are organized.
na_position : {'first', 'last'} (optional, default='last')
'first' puts NaNs at the beginning
'last' puts NaNs at the end
Returns
-------
Categorical or None
See Also
--------
Categorical.sort
Series.sort_values
Examples
--------
>>> c = pd.Categorical([1, 2, 2, 1, 5])
>>> c
[1, 2, 2, 1, 5]
Categories (3, int64): [1, 2, 5]
>>> c.sort_values()
[1, 1, 2, 2, 5]
Categories (3, int64): [1, 2, 5]
>>> c.sort_values(ascending=False)
[5, 2, 2, 1, 1]
Categories (3, int64): [1, 2, 5]
Inplace sorting can be done as well:
>>> c.sort_values(inplace=True)
>>> c
[1, 1, 2, 2, 5]
Categories (3, int64): [1, 2, 5]
>>>
>>> c = pd.Categorical([1, 2, 2, 1, 5])
'sort_values' behaviour with NaNs. Note that 'na_position'
is independent of the 'ascending' parameter:
>>> c = pd.Categorical([np.nan, 2, 2, np.nan, 5])
>>> c
[NaN, 2.0, 2.0, NaN, 5.0]
Categories (2, int64): [2, 5]
>>> c.sort_values()
[2.0, 2.0, 5.0, NaN, NaN]
Categories (2, int64): [2, 5]
>>> c.sort_values(ascending=False)
[5.0, 2.0, 2.0, NaN, NaN]
Categories (2, int64): [2, 5]
>>> c.sort_values(na_position='first')
[NaN, NaN, 2.0, 2.0, 5.0]
Categories (2, int64): [2, 5]
>>> c.sort_values(ascending=False, na_position='first')
[NaN, NaN, 5.0, 2.0, 2.0]
Categories (2, int64): [2, 5]
"""
inplace = validate_bool_kwarg(inplace, 'inplace')
if na_position not in ['last', 'first']:
msg = 'invalid na_position: {na_position!r}'
raise ValueError(msg.format(na_position=na_position))
sorted_idx = nargsort(self,
ascending=ascending,
na_position=na_position)
if inplace:
self._codes = self._codes[sorted_idx]
else:
return self._constructor(values=self._codes[sorted_idx],
dtype=self.dtype,
fastpath=True)
|
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] |
Sort the Categorical by category value returning a new
Categorical by default.
While an ordering is applied to the category values, sorting in this
context refers more to organizing and grouping together based on
matching category values. Thus, this function can be called on an
unordered Categorical instance unlike the functions 'Categorical.min'
and 'Categorical.max'.
Parameters
----------
inplace : bool, default False
Do operation in place.
ascending : bool, default True
Order ascending. Passing False orders descending. The
ordering parameter provides the method by which the
category values are organized.
na_position : {'first', 'last'} (optional, default='last')
'first' puts NaNs at the beginning
'last' puts NaNs at the end
Returns
-------
Categorical or None
See Also
--------
Categorical.sort
Series.sort_values
Examples
--------
>>> c = pd.Categorical([1, 2, 2, 1, 5])
>>> c
[1, 2, 2, 1, 5]
Categories (3, int64): [1, 2, 5]
>>> c.sort_values()
[1, 1, 2, 2, 5]
Categories (3, int64): [1, 2, 5]
>>> c.sort_values(ascending=False)
[5, 2, 2, 1, 1]
Categories (3, int64): [1, 2, 5]
Inplace sorting can be done as well:
>>> c.sort_values(inplace=True)
>>> c
[1, 1, 2, 2, 5]
Categories (3, int64): [1, 2, 5]
>>>
>>> c = pd.Categorical([1, 2, 2, 1, 5])
'sort_values' behaviour with NaNs. Note that 'na_position'
is independent of the 'ascending' parameter:
>>> c = pd.Categorical([np.nan, 2, 2, np.nan, 5])
>>> c
[NaN, 2.0, 2.0, NaN, 5.0]
Categories (2, int64): [2, 5]
>>> c.sort_values()
[2.0, 2.0, 5.0, NaN, NaN]
Categories (2, int64): [2, 5]
>>> c.sort_values(ascending=False)
[5.0, 2.0, 2.0, NaN, NaN]
Categories (2, int64): [2, 5]
>>> c.sort_values(na_position='first')
[NaN, NaN, 2.0, 2.0, 5.0]
Categories (2, int64): [2, 5]
>>> c.sort_values(ascending=False, na_position='first')
[NaN, NaN, 5.0, 2.0, 2.0]
Categories (2, int64): [2, 5]
|
[
"Sort",
"the",
"Categorical",
"by",
"category",
"value",
"returning",
"a",
"new",
"Categorical",
"by",
"default",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/arrays/categorical.py#L1554-L1642
|
train
|
Sort the values of the Categorical by category value returning a new Categorical instance.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(2161 - 2113) + chr(111) + '\x31' + chr(0b110111) + chr(0b110111), 0o10), ehT0Px3KOsy9('\x30' + chr(238 - 127) + chr(0b110010) + chr(1837 - 1786) + chr(55), 6250 - 6242), ehT0Px3KOsy9(chr(0b110000) + chr(0b1000100 + 0o53) + '\063' + chr(55) + chr(0b110100), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + '\062' + chr(160 - 105) + chr(0b110000), 16608 - 16600), ehT0Px3KOsy9(chr(0b100 + 0o54) + chr(9395 - 9284) + chr(2081 - 2030) + '\x32' + '\x32', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b110110) + chr(0b110110), 28294 - 28286), ehT0Px3KOsy9('\060' + chr(4437 - 4326) + chr(50) + chr(0b100111 + 0o16) + '\064', 0b1000), ehT0Px3KOsy9(chr(2181 - 2133) + chr(0b1000010 + 0o55) + chr(0b110010 + 0o2) + chr(994 - 946), 0b1000), ehT0Px3KOsy9(chr(0b11010 + 0o26) + '\x6f' + '\061' + chr(0b10 + 0o61) + '\062', 0b1000), ehT0Px3KOsy9(chr(701 - 653) + '\x6f' + chr(0b100 + 0o57) + chr(0b110111) + chr(0b101111 + 0o5), 8), ehT0Px3KOsy9('\x30' + '\x6f' + '\061' + '\062' + chr(0b110100), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b11000 + 0o127) + '\066', 0b1000), ehT0Px3KOsy9(chr(0b100010 + 0o16) + '\x6f' + chr(50 - 0) + chr(0b101101 + 0o5) + '\064', 39322 - 39314), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b110010) + chr(49) + chr(0b1100 + 0o53), ord("\x08")), ehT0Px3KOsy9(chr(650 - 602) + '\157' + chr(0b110100), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(2265 - 2215) + chr(0b110101 + 0o1) + chr(0b101110 + 0o6), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(0b1011111 + 0o20) + '\x33' + chr(351 - 300) + chr(51), 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b11010 + 0o30) + chr(0b110010) + '\065', 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110110) + '\x31', 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b10111 + 0o33) + '\060' + chr(51), ord("\x08")), ehT0Px3KOsy9(chr(0b1101 + 0o43) + chr(0b1101111) + chr(0b10110 + 0o33) + '\063' + '\x30', 26266 - 26258), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x33', 10237 - 10229), ehT0Px3KOsy9(chr(1273 - 1225) + '\x6f' + chr(703 - 652) + chr(0b110011) + chr(1370 - 1317), 0o10), ehT0Px3KOsy9('\060' + '\157' + chr(0b11000 + 0o33) + chr(0b110101) + chr(54), 0o10), ehT0Px3KOsy9(chr(48) + chr(111) + chr(559 - 508) + '\064' + '\065', ord("\x08")), ehT0Px3KOsy9(chr(0b1110 + 0o42) + chr(5677 - 5566) + chr(51) + '\x30' + '\x35', 56511 - 56503), ehT0Px3KOsy9(chr(48) + chr(0b11 + 0o154) + chr(0b110011) + chr(0b110001) + '\065', 0o10), ehT0Px3KOsy9(chr(0b1001 + 0o47) + '\x6f' + chr(50) + '\066' + chr(0b110011), 12083 - 12075), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b11001 + 0o30) + chr(2193 - 2141) + chr(55), 0o10), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(49) + chr(452 - 404) + '\060', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\063' + chr(0b110101) + '\067', 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(1498 - 1448), 871 - 863), ehT0Px3KOsy9('\x30' + '\x6f' + chr(0b11101 + 0o25) + chr(0b10001 + 0o42) + '\x30', 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1100111 + 0o10) + chr(49) + chr(467 - 415) + chr(0b101100 + 0o10), 45829 - 45821), ehT0Px3KOsy9(chr(0b110000) + chr(11205 - 11094) + chr(0b110011) + chr(55) + chr(0b1011 + 0o45), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\067', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b110010 + 0o75) + '\061' + '\x33' + chr(0b11111 + 0o21), 8), ehT0Px3KOsy9(chr(1200 - 1152) + chr(6229 - 6118) + chr(0b110110) + chr(0b110101), 16309 - 16301), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x33' + '\x30' + chr(0b101111 + 0o2), 9148 - 9140), ehT0Px3KOsy9(chr(48) + chr(0b1101001 + 0o6) + chr(0b110011) + '\x37' + chr(55), 27845 - 27837)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + chr(10536 - 10425) + '\x35' + chr(0b110000), 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'Q'), '\144' + '\145' + '\x63' + chr(0b110111 + 0o70) + chr(0b11101 + 0o107) + chr(0b1100101))(chr(0b100001 + 0o124) + '\x74' + chr(0b100 + 0o142) + chr(0b101101) + chr(1915 - 1859)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def nKRyNs3qSeG2(oVre8I6UXc3b, KhzrMpzISODo=ehT0Px3KOsy9('\x30' + chr(111) + '\060', 0o10), OtwBK3ePE1cK=ehT0Px3KOsy9(chr(48) + chr(0b1000010 + 0o55) + '\061', ord("\x08")), JLtVil0zH4Au=xafqLlk3kkUe(SXOLrMavuUCe(b'\x13\xfe\x8f\xcc'), chr(0b1100100) + chr(0b1100101) + '\x63' + '\157' + chr(0b1100100) + chr(0b1001000 + 0o35))(chr(3567 - 3450) + '\x74' + '\146' + chr(45) + chr(0b111000))):
KhzrMpzISODo = LYHx5VlCvmk_(KhzrMpzISODo, xafqLlk3kkUe(SXOLrMavuUCe(b'\x16\xf1\x8c\xd4\xb3U\xc9'), chr(4701 - 4601) + '\x65' + chr(0b1100011) + chr(7447 - 7336) + chr(0b111000 + 0o54) + chr(101))('\x75' + chr(116) + chr(1193 - 1091) + chr(0b101101) + chr(0b100111 + 0o21)))
if JLtVil0zH4Au not in [xafqLlk3kkUe(SXOLrMavuUCe(b'\x13\xfe\x8f\xcc'), chr(100) + '\x65' + chr(0b1100011) + chr(5363 - 5252) + chr(0b1100100) + '\x65')(chr(0b1110101) + chr(116) + '\146' + '\055' + '\x38'), xafqLlk3kkUe(SXOLrMavuUCe(b'\x19\xf6\x8e\xcb\xa6'), '\x64' + chr(101) + chr(99) + '\157' + chr(100) + chr(6208 - 6107))(chr(4054 - 3937) + chr(116) + '\146' + chr(45) + chr(56))]:
jtbovtaIYjRB = xafqLlk3kkUe(SXOLrMavuUCe(b'\x16\xf1\x8a\xd9\xbe_\xc8\x004\x9d\x0bv\xfb\xfcm\xc0\xb2\xfa_\xb9xx\xb3\x8f\xba\xb5\xa2\xc0\x0e4\x86m\xf6E\x8az'), chr(5816 - 5716) + '\145' + chr(99) + chr(9557 - 9446) + chr(5648 - 5548) + '\145')('\165' + chr(0b1110100) + '\146' + '\055' + chr(0b111000))
raise q1QCh3W88sgk(xafqLlk3kkUe(jtbovtaIYjRB, xafqLlk3kkUe(SXOLrMavuUCe(b'\x19\xf0\x8e\xd5\xb3B'), chr(0b1100100) + chr(101) + '\143' + chr(0b1101111) + chr(0b0 + 0o144) + chr(0b11001 + 0o114))('\165' + chr(0b101001 + 0o113) + chr(10133 - 10031) + chr(0b101101) + chr(56)))(na_position=JLtVil0zH4Au))
sZLtNt0MRmdr = QMtV_7482tFG(oVre8I6UXc3b, ascending=OtwBK3ePE1cK, na_position=JLtVil0zH4Au)
if KhzrMpzISODo:
oVre8I6UXc3b.d5BDZJl_zDsu = oVre8I6UXc3b.d5BDZJl_zDsu[sZLtNt0MRmdr]
else:
return xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b' \xfc\x93\xd6\xa1B\xdeU9\x88;t'), chr(0b110001 + 0o63) + chr(0b1011000 + 0o15) + chr(0b1010101 + 0o16) + chr(0b1101111) + chr(100) + chr(101))('\x75' + chr(10805 - 10689) + chr(0b1100110) + '\055' + chr(0b111000)))(values=xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b"\x1b\xaa\xbe\xfc\x88|\xc0\x7f \xb8's"), '\x64' + '\x65' + chr(3831 - 3732) + '\157' + chr(0b111001 + 0o53) + '\x65')(chr(0b1110101) + '\164' + '\146' + chr(118 - 73) + '\x38'))[sZLtNt0MRmdr], dtype=xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\x1b\xeb\x85\xc8\xb7'), chr(100) + chr(0b1100101) + '\143' + '\x6f' + '\144' + '\x65')(chr(0b11011 + 0o132) + '\x74' + '\146' + '\055' + chr(2584 - 2528))), fastpath=ehT0Px3KOsy9(chr(48) + chr(0b1001001 + 0o46) + '\x31', 8))
|
pandas-dev/pandas
|
pandas/core/arrays/categorical.py
|
Categorical._values_for_rank
|
def _values_for_rank(self):
"""
For correctly ranking ordered categorical data. See GH#15420
Ordered categorical data should be ranked on the basis of
codes with -1 translated to NaN.
Returns
-------
numpy.array
"""
from pandas import Series
if self.ordered:
values = self.codes
mask = values == -1
if mask.any():
values = values.astype('float64')
values[mask] = np.nan
elif self.categories.is_numeric():
values = np.array(self)
else:
# reorder the categories (so rank can use the float codes)
# instead of passing an object array to rank
values = np.array(
self.rename_categories(Series(self.categories).rank().values)
)
return values
|
python
|
def _values_for_rank(self):
"""
For correctly ranking ordered categorical data. See GH#15420
Ordered categorical data should be ranked on the basis of
codes with -1 translated to NaN.
Returns
-------
numpy.array
"""
from pandas import Series
if self.ordered:
values = self.codes
mask = values == -1
if mask.any():
values = values.astype('float64')
values[mask] = np.nan
elif self.categories.is_numeric():
values = np.array(self)
else:
# reorder the categories (so rank can use the float codes)
# instead of passing an object array to rank
values = np.array(
self.rename_categories(Series(self.categories).rank().values)
)
return values
|
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"self",
".",
"categories",
")",
".",
"rank",
"(",
")",
".",
"values",
")",
")",
"return",
"values"
] |
For correctly ranking ordered categorical data. See GH#15420
Ordered categorical data should be ranked on the basis of
codes with -1 translated to NaN.
Returns
-------
numpy.array
|
[
"For",
"correctly",
"ranking",
"ordered",
"categorical",
"data",
".",
"See",
"GH#15420"
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/arrays/categorical.py#L1644-L1671
|
train
|
Returns a numpy array of the values for the rank of the items in the record.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b10 + 0o56) + chr(0b1101111) + chr(49) + chr(52) + chr(50), 0o10), ehT0Px3KOsy9('\060' + chr(0b10011 + 0o134) + chr(50) + chr(1746 - 1694) + chr(1947 - 1895), 0b1000), ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(0b1101111) + chr(0b111 + 0o53) + '\x37' + '\061', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(1653 - 1604) + '\060', ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + '\x34' + chr(0b100101 + 0o21), 0b1000), ehT0Px3KOsy9('\x30' + chr(0b100101 + 0o112) + '\063' + '\063' + '\x35', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(1167 - 1116) + chr(0b110 + 0o54) + chr(1401 - 1350), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + '\067' + '\x34', 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(50) + '\x32' + chr(0b11111 + 0o22), 0o10), ehT0Px3KOsy9('\x30' + chr(0b1101111) + '\x32' + chr(898 - 849) + chr(0b110000), 0b1000), ehT0Px3KOsy9(chr(0b11110 + 0o22) + chr(111) + '\x32' + '\066', 0b1000), ehT0Px3KOsy9(chr(48) + chr(8866 - 8755) + '\062' + chr(0b110100 + 0o2) + '\x34', 0o10), ehT0Px3KOsy9('\060' + chr(0b1100110 + 0o11) + '\063' + chr(0b110001) + '\060', 0b1000), ehT0Px3KOsy9('\x30' + chr(6033 - 5922) + chr(0b110101) + '\060', 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(0b10111 + 0o34) + '\x31' + '\062', 0o10), ehT0Px3KOsy9(chr(790 - 742) + '\x6f' + '\x32' + chr(2324 - 2273) + '\x32', 0o10), ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x33' + '\x30' + chr(1108 - 1054), ord("\x08")), ehT0Px3KOsy9(chr(72 - 24) + chr(0b1101111) + chr(50) + chr(0b1 + 0o65) + '\x37', 36855 - 36847), ehT0Px3KOsy9(chr(0b110000) + chr(5128 - 5017) + '\x32' + '\067' + '\062', 0b1000), ehT0Px3KOsy9(chr(1077 - 1029) + '\x6f' + chr(51) + '\063' + '\x34', 0b1000), ehT0Px3KOsy9(chr(486 - 438) + chr(7442 - 7331) + chr(280 - 230) + '\x34' + chr(49), 0o10), ehT0Px3KOsy9(chr(2207 - 2159) + chr(0b1101111) + chr(50) + '\065' + chr(0b110001), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(0b1010011 + 0o34) + chr(50) + chr(0b101100 + 0o11) + chr(50), 0b1000), ehT0Px3KOsy9(chr(48) + chr(8008 - 7897) + chr(0b110001) + chr(55), 45645 - 45637), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b101 + 0o56) + chr(0b10 + 0o62) + chr(2843 - 2788), ord("\x08")), ehT0Px3KOsy9(chr(0b100101 + 0o13) + chr(111) + chr(50) + '\x32' + '\065', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(0b11110 + 0o23) + '\x37' + chr(50), 0o10), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(1802 - 1751) + chr(52) + '\x30', 0b1000), ehT0Px3KOsy9(chr(0b101011 + 0o5) + chr(0b1100100 + 0o13) + chr(0b10000 + 0o42) + chr(0b1101 + 0o46) + '\x30', 30489 - 30481), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110010) + '\x33' + chr(53), ord("\x08")), ehT0Px3KOsy9(chr(494 - 446) + chr(111) + chr(2231 - 2180) + chr(0b1010 + 0o51) + chr(48), 20309 - 20301), ehT0Px3KOsy9('\060' + chr(0b111101 + 0o62) + chr(50) + chr(0b101001 + 0o12) + '\x33', ord("\x08")), ehT0Px3KOsy9(chr(550 - 502) + chr(0b1001010 + 0o45) + chr(1258 - 1208) + chr(55) + '\x34', 34662 - 34654), ehT0Px3KOsy9('\x30' + chr(111) + '\063' + chr(52) + '\x37', 8), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(51) + chr(52) + '\067', 8), ehT0Px3KOsy9(chr(48) + chr(0b110101 + 0o72) + chr(0b1100 + 0o45) + '\064' + chr(50), 8), ehT0Px3KOsy9('\060' + chr(7156 - 7045) + chr(49) + chr(61 - 6) + '\066', 0o10), ehT0Px3KOsy9('\x30' + chr(0b11001 + 0o126) + chr(51) + chr(50) + '\x34', 0o10), ehT0Px3KOsy9(chr(0b110 + 0o52) + chr(0b1 + 0o156) + '\062' + '\x32', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1011100 + 0o23) + chr(214 - 164) + chr(0b11111 + 0o22) + '\064', 23561 - 23553)][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + chr(0b111010 + 0o65) + chr(0b110101) + chr(0b110000 + 0o0), 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'L'), '\144' + chr(101) + chr(0b1100011) + chr(0b1101111) + chr(0b1100100) + chr(0b1100101))('\x75' + '\x74' + chr(102) + chr(0b10001 + 0o34) + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def O9jswikqFmIO(oVre8I6UXc3b):
(I9PbrFvU4NYI,) = (xafqLlk3kkUe(NPPHb59961Bv(xafqLlk3kkUe(SXOLrMavuUCe(b'\x12\xc5\xd7lG\xae'), '\144' + '\145' + '\143' + chr(0b11110 + 0o121) + chr(0b1100100) + '\x65')(chr(0b1101111 + 0o6) + chr(0b1110100) + chr(0b1100110) + chr(1636 - 1591) + '\x38'), xafqLlk3kkUe(SXOLrMavuUCe(b'1\xc1\xcbaC\xae'), chr(0b1100100) + '\x65' + '\x63' + chr(764 - 653) + chr(100) + chr(0b110 + 0o137))('\x75' + '\164' + chr(0b1000 + 0o136) + '\055' + '\070')), xafqLlk3kkUe(SXOLrMavuUCe(b'1\xc1\xcbaC\xae'), chr(0b1100100) + '\x65' + chr(0b1100011) + '\x6f' + '\x64' + '\145')(chr(9837 - 9720) + chr(116) + chr(102) + chr(0b101101) + '\070')),)
if xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\r\xd6\xddmT\xb8\xb7'), chr(100) + chr(0b1010 + 0o133) + chr(0b1100011) + chr(5325 - 5214) + chr(0b1100100) + '\145')(chr(0b110 + 0o157) + chr(0b1110100) + '\146' + '\x2d' + '\070')):
SPnCNu54H1db = oVre8I6UXc3b.codes
Iz1jSgUKZDvt = SPnCNu54H1db == -ehT0Px3KOsy9(chr(48) + chr(0b1010000 + 0o37) + chr(49), 0o10)
if xafqLlk3kkUe(Iz1jSgUKZDvt, xafqLlk3kkUe(SXOLrMavuUCe(b'7\xf2\xeaa\x12\x85\x84\x0b\xf4\xca_\xf9'), '\144' + chr(0b1100101) + chr(99) + '\x6f' + chr(1080 - 980) + chr(101))('\165' + '\164' + chr(0b11 + 0o143) + chr(0b101101) + chr(585 - 529)))():
SPnCNu54H1db = SPnCNu54H1db.astype(xafqLlk3kkUe(SXOLrMavuUCe(b'\x04\xc8\xd6iR\xeb\xe7'), chr(100) + '\x65' + '\x63' + '\157' + chr(0b1100100) + '\145')(chr(0b1100110 + 0o17) + chr(0b10111 + 0o135) + chr(102) + '\x2d' + '\070'))
SPnCNu54H1db[Iz1jSgUKZDvt] = WqUC3KWvYVup.nan
elif xafqLlk3kkUe(oVre8I6UXc3b.categories, xafqLlk3kkUe(SXOLrMavuUCe(b'\x0b\xd7\xe6fS\xb0\xb6N\xf8\xeb'), chr(0b1100001 + 0o3) + chr(0b1100010 + 0o3) + '\143' + '\157' + '\x64' + chr(1513 - 1412))(chr(117) + chr(0b1110100) + chr(102) + chr(0b101101) + chr(1592 - 1536)))():
SPnCNu54H1db = WqUC3KWvYVup.array(oVre8I6UXc3b)
else:
SPnCNu54H1db = WqUC3KWvYVup.array(oVre8I6UXc3b.rename_categories(I9PbrFvU4NYI(oVre8I6UXc3b.categories).rank().SPnCNu54H1db))
return SPnCNu54H1db
|
pandas-dev/pandas
|
pandas/core/arrays/categorical.py
|
Categorical.fillna
|
def fillna(self, value=None, method=None, limit=None):
"""
Fill NA/NaN values using the specified method.
Parameters
----------
value : scalar, dict, Series
If a scalar value is passed it is used to fill all missing values.
Alternatively, a Series or dict can be used to fill in different
values for each index. The value should not be a list. The
value(s) passed should either be in the categories or should be
NaN.
method : {'backfill', 'bfill', 'pad', 'ffill', None}, default None
Method to use for filling holes in reindexed Series
pad / ffill: propagate last valid observation forward to next valid
backfill / bfill: use NEXT valid observation to fill gap
limit : int, default None
(Not implemented yet for Categorical!)
If method is specified, this is the maximum number of consecutive
NaN values to forward/backward fill. In other words, if there is
a gap with more than this number of consecutive NaNs, it will only
be partially filled. If method is not specified, this is the
maximum number of entries along the entire axis where NaNs will be
filled.
Returns
-------
filled : Categorical with NA/NaN filled
"""
value, method = validate_fillna_kwargs(
value, method, validate_scalar_dict_value=False
)
if value is None:
value = np.nan
if limit is not None:
raise NotImplementedError("specifying a limit for fillna has not "
"been implemented yet")
codes = self._codes
# pad / bfill
if method is not None:
values = self.to_dense().reshape(-1, len(self))
values = interpolate_2d(values, method, 0, None,
value).astype(self.categories.dtype)[0]
codes = _get_codes_for_values(values, self.categories)
else:
# If value is a dict or a Series (a dict value has already
# been converted to a Series)
if isinstance(value, ABCSeries):
if not value[~value.isin(self.categories)].isna().all():
raise ValueError("fill value must be in categories")
values_codes = _get_codes_for_values(value, self.categories)
indexer = np.where(values_codes != -1)
codes[indexer] = values_codes[values_codes != -1]
# If value is not a dict or Series it should be a scalar
elif is_hashable(value):
if not isna(value) and value not in self.categories:
raise ValueError("fill value must be in categories")
mask = codes == -1
if mask.any():
codes = codes.copy()
if isna(value):
codes[mask] = -1
else:
codes[mask] = self.categories.get_loc(value)
else:
raise TypeError('"value" parameter must be a scalar, dict '
'or Series, but you passed a '
'"{0}"'.format(type(value).__name__))
return self._constructor(codes, dtype=self.dtype, fastpath=True)
|
python
|
def fillna(self, value=None, method=None, limit=None):
"""
Fill NA/NaN values using the specified method.
Parameters
----------
value : scalar, dict, Series
If a scalar value is passed it is used to fill all missing values.
Alternatively, a Series or dict can be used to fill in different
values for each index. The value should not be a list. The
value(s) passed should either be in the categories or should be
NaN.
method : {'backfill', 'bfill', 'pad', 'ffill', None}, default None
Method to use for filling holes in reindexed Series
pad / ffill: propagate last valid observation forward to next valid
backfill / bfill: use NEXT valid observation to fill gap
limit : int, default None
(Not implemented yet for Categorical!)
If method is specified, this is the maximum number of consecutive
NaN values to forward/backward fill. In other words, if there is
a gap with more than this number of consecutive NaNs, it will only
be partially filled. If method is not specified, this is the
maximum number of entries along the entire axis where NaNs will be
filled.
Returns
-------
filled : Categorical with NA/NaN filled
"""
value, method = validate_fillna_kwargs(
value, method, validate_scalar_dict_value=False
)
if value is None:
value = np.nan
if limit is not None:
raise NotImplementedError("specifying a limit for fillna has not "
"been implemented yet")
codes = self._codes
# pad / bfill
if method is not None:
values = self.to_dense().reshape(-1, len(self))
values = interpolate_2d(values, method, 0, None,
value).astype(self.categories.dtype)[0]
codes = _get_codes_for_values(values, self.categories)
else:
# If value is a dict or a Series (a dict value has already
# been converted to a Series)
if isinstance(value, ABCSeries):
if not value[~value.isin(self.categories)].isna().all():
raise ValueError("fill value must be in categories")
values_codes = _get_codes_for_values(value, self.categories)
indexer = np.where(values_codes != -1)
codes[indexer] = values_codes[values_codes != -1]
# If value is not a dict or Series it should be a scalar
elif is_hashable(value):
if not isna(value) and value not in self.categories:
raise ValueError("fill value must be in categories")
mask = codes == -1
if mask.any():
codes = codes.copy()
if isna(value):
codes[mask] = -1
else:
codes[mask] = self.categories.get_loc(value)
else:
raise TypeError('"value" parameter must be a scalar, dict '
'or Series, but you passed a '
'"{0}"'.format(type(value).__name__))
return self._constructor(codes, dtype=self.dtype, fastpath=True)
|
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] |
Fill NA/NaN values using the specified method.
Parameters
----------
value : scalar, dict, Series
If a scalar value is passed it is used to fill all missing values.
Alternatively, a Series or dict can be used to fill in different
values for each index. The value should not be a list. The
value(s) passed should either be in the categories or should be
NaN.
method : {'backfill', 'bfill', 'pad', 'ffill', None}, default None
Method to use for filling holes in reindexed Series
pad / ffill: propagate last valid observation forward to next valid
backfill / bfill: use NEXT valid observation to fill gap
limit : int, default None
(Not implemented yet for Categorical!)
If method is specified, this is the maximum number of consecutive
NaN values to forward/backward fill. In other words, if there is
a gap with more than this number of consecutive NaNs, it will only
be partially filled. If method is not specified, this is the
maximum number of entries along the entire axis where NaNs will be
filled.
Returns
-------
filled : Categorical with NA/NaN filled
|
[
"Fill",
"NA",
"/",
"NaN",
"values",
"using",
"the",
"specified",
"method",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/arrays/categorical.py#L1711-L1790
|
train
|
Fill missing values in the specified category with the specified value.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(821 - 772) + chr(55) + chr(52), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + '\062' + '\x30' + '\064', 0b1000), ehT0Px3KOsy9('\x30' + '\157' + chr(184 - 129) + chr(2011 - 1960), 10393 - 10385), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110001) + chr(0b110011) + chr(188 - 136), 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(0b11111 + 0o23) + chr(0b110001 + 0o2), 0o10), ehT0Px3KOsy9(chr(1616 - 1568) + '\x6f' + '\066' + '\064', 54317 - 54309), ehT0Px3KOsy9('\060' + chr(11499 - 11388) + chr(0b10111 + 0o32) + chr(0b110101) + '\x31', 0b1000), ehT0Px3KOsy9(chr(1558 - 1510) + '\157' + chr(53) + chr(49), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(576 - 525) + chr(1453 - 1398) + chr(0b110101), 22708 - 22700), ehT0Px3KOsy9(chr(48) + '\157' + '\061' + chr(0b111 + 0o57) + '\062', ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110111) + chr(507 - 456), 8), ehT0Px3KOsy9('\x30' + '\157' + chr(49) + chr(0b110111) + '\x33', 0b1000), ehT0Px3KOsy9('\060' + '\157' + '\x33' + chr(0b1110 + 0o43) + '\x33', 0b1000), ehT0Px3KOsy9('\x30' + '\x6f' + '\x31' + chr(0b10010 + 0o43) + chr(1771 - 1723), 53191 - 53183), ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(111) + '\065' + chr(0b110111), 0b1000), ehT0Px3KOsy9(chr(48) + chr(4392 - 4281) + chr(51) + '\x36', 0b1000), ehT0Px3KOsy9('\x30' + chr(9736 - 9625) + chr(0b1100 + 0o47) + '\066' + chr(0b110001 + 0o1), 5107 - 5099), ehT0Px3KOsy9('\x30' + chr(111) + chr(1961 - 1907), 57002 - 56994), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b110001) + '\060' + '\061', 58757 - 58749), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(0b110011) + '\x30' + chr(52), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b101100 + 0o7) + '\062' + chr(0b1111 + 0o45), 0b1000), ehT0Px3KOsy9(chr(141 - 93) + chr(0b1101111) + chr(0b10010 + 0o37) + chr(125 - 73) + chr(576 - 524), 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(51) + chr(55) + chr(0b110011), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(50) + chr(0b10 + 0o60) + '\065', 8696 - 8688), ehT0Px3KOsy9(chr(1974 - 1926) + '\x6f' + chr(51) + chr(0b100100 + 0o14), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b11111 + 0o120) + chr(2021 - 1968) + '\066', 0o10), ehT0Px3KOsy9('\x30' + chr(0b1010011 + 0o34) + chr(0b110001) + chr(52), 8246 - 8238), ehT0Px3KOsy9('\060' + chr(0b1001000 + 0o47) + chr(49) + chr(52) + chr(0b11010 + 0o30), 3577 - 3569), ehT0Px3KOsy9(chr(0b110000) + chr(5496 - 5385) + chr(0b11000 + 0o32) + chr(0b110110) + chr(0b1110 + 0o50), 27872 - 27864), ehT0Px3KOsy9('\x30' + '\157' + chr(2452 - 2402) + '\x36' + chr(54), 8), ehT0Px3KOsy9(chr(0b11 + 0o55) + '\x6f' + chr(51) + chr(2122 - 2074) + '\067', 23454 - 23446), ehT0Px3KOsy9(chr(0b100 + 0o54) + chr(0b1101111) + chr(0b100101 + 0o15) + chr(0b101001 + 0o13) + chr(0b101001 + 0o16), 0o10), ehT0Px3KOsy9(chr(1168 - 1120) + chr(0b100010 + 0o115) + chr(53) + '\061', 8), ehT0Px3KOsy9(chr(613 - 565) + chr(111) + chr(0b101011 + 0o10) + chr(2437 - 2387) + chr(0b110000), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(5412 - 5301) + chr(0b11101 + 0o25) + '\x36' + chr(0b110010), 0o10), ehT0Px3KOsy9(chr(0b11000 + 0o30) + chr(0b1101111) + chr(0b110011) + chr(53) + chr(0b11101 + 0o23), 1776 - 1768), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110010) + '\064' + '\064', 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(49) + chr(0b101001 + 0o10) + chr(54), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(51) + chr(0b110011) + chr(54), 11842 - 11834), ehT0Px3KOsy9(chr(1781 - 1733) + chr(377 - 266) + chr(1533 - 1483) + '\x32' + '\x32', 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9('\060' + chr(111) + chr(0b101001 + 0o14) + chr(48), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'R'), chr(100) + chr(101) + chr(6426 - 6327) + '\157' + '\x64' + chr(101))(chr(0b1011111 + 0o26) + '\x74' + chr(0b100000 + 0o106) + chr(0b101101) + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def WhVSCjZUYrOg(oVre8I6UXc3b, QmmgWUB13VCJ=None, CVRCXTcnOnH6=None, j8BaqiKmcR6w=None):
(QmmgWUB13VCJ, CVRCXTcnOnH6) = j80NLK81yWDZ(QmmgWUB13VCJ, CVRCXTcnOnH6, validate_scalar_dict_value=ehT0Px3KOsy9('\x30' + '\x6f' + chr(48), ord("\x08")))
if QmmgWUB13VCJ is None:
QmmgWUB13VCJ = WqUC3KWvYVup.nan
if j8BaqiKmcR6w is not None:
raise _zJ24Vce7wp0(xafqLlk3kkUe(SXOLrMavuUCe(b'\x0f\xf4^?zR\x10@\x93\x15\x1b\x1a\xeb\x04Fs\x9bra\xa2\xbb\x16\xdb\xf3qB`\x0c\xd7\x96\xaf\xc6Z\xf0\xdc\x87\xd0n\xbc\xf7\x19\xea\x1b5~D\x05L\x90\x17U\x0f\xae\x0c\x0fg\x97r'), chr(0b1110 + 0o126) + '\x65' + '\x63' + chr(0b1101111) + '\144' + chr(1545 - 1444))(chr(117) + chr(0b1010111 + 0o35) + chr(102) + '\055' + chr(2090 - 2034)))
AoWJEgIAbHh_ = oVre8I6UXc3b.d5BDZJl_zDsu
if CVRCXTcnOnH6 is not None:
SPnCNu54H1db = oVre8I6UXc3b.to_dense().reshape(-ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x31', 0b1000), c2A0yzQpDQB3(oVre8I6UXc3b))
SPnCNu54H1db = bDpz_vdV2az0(SPnCNu54H1db, CVRCXTcnOnH6, ehT0Px3KOsy9(chr(0b110000) + chr(6654 - 6543) + chr(0b110000), 8), None, QmmgWUB13VCJ).astype(oVre8I6UXc3b.categories.dtype)[ehT0Px3KOsy9(chr(2185 - 2137) + '\157' + '\x30', 8)]
AoWJEgIAbHh_ = SrdNuo8P440p(SPnCNu54H1db, oVre8I6UXc3b.mZZDAT49UzAb)
elif PlSM16l2KDPD(QmmgWUB13VCJ, essMXh4s9f1w):
if not xafqLlk3kkUe(QmmgWUB13VCJ[~QmmgWUB13VCJ.isin(oVre8I6UXc3b.categories)].isna(), xafqLlk3kkUe(SXOLrMavuUCe(b'8\xe8\x0fd}^X[\x9f\x1b\tH'), '\144' + chr(0b1100101) + chr(1217 - 1118) + chr(0b1101111) + chr(0b1000010 + 0o42) + chr(0b1100101))(chr(0b111101 + 0o70) + chr(0b1101000 + 0o14) + '\146' + chr(180 - 135) + chr(56)))():
raise q1QCh3W88sgk(xafqLlk3kkUe(SXOLrMavuUCe(b'\x1a\xedW03B\x08E\x88\x17\x1b\x16\xbe\x1b[>\x90ca\xad\xbaD\x98\xf4lKk\r\xc4\xdf\xa2\xd4'), '\144' + '\x65' + chr(0b1100011) + chr(0b110010 + 0o75) + chr(0b1100100) + chr(0b1100101 + 0o0))(chr(0b1110101) + chr(0b10001 + 0o143) + chr(0b1011000 + 0o16) + chr(45) + '\070'))
jcRPx5NtGtP0 = SrdNuo8P440p(QmmgWUB13VCJ, oVre8I6UXc3b.mZZDAT49UzAb)
BvJfssszZMhp = WqUC3KWvYVup.dRFAC59yQBm_(jcRPx5NtGtP0 != -ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\061', 8))
AoWJEgIAbHh_[BvJfssszZMhp] = jcRPx5NtGtP0[jcRPx5NtGtP0 != -ehT0Px3KOsy9(chr(1966 - 1918) + chr(0b1 + 0o156) + '\061', 8)]
elif ocRGWrk2KuZy(QmmgWUB13VCJ):
if not yBUx5qcFiTz6(QmmgWUB13VCJ) and QmmgWUB13VCJ not in xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\x11\xdea\x18R`]\x10\xa8\x08z\x19'), '\x64' + chr(101) + '\143' + chr(0b1101111) + chr(100) + '\x65')(chr(0b1110101) + chr(5597 - 5481) + chr(460 - 358) + '\x2d' + '\x38')):
raise q1QCh3W88sgk(xafqLlk3kkUe(SXOLrMavuUCe(b'\x1a\xedW03B\x08E\x88\x17\x1b\x16\xbe\x1b[>\x90ca\xad\xbaD\x98\xf4lKk\r\xc4\xdf\xa2\xd4'), chr(100) + '\x65' + chr(3781 - 3682) + '\x6f' + '\144' + chr(101))('\x75' + chr(5777 - 5661) + chr(102) + '\x2d' + chr(0b111000)))
Iz1jSgUKZDvt = AoWJEgIAbHh_ == -ehT0Px3KOsy9(chr(0b101010 + 0o6) + '\157' + chr(72 - 23), 8)
if xafqLlk3kkUe(Iz1jSgUKZDvt, xafqLlk3kkUe(SXOLrMavuUCe(b")\xd2h5'l>\x1e\x980r6"), chr(0b1000111 + 0o35) + chr(101) + '\x63' + chr(0b1011001 + 0o26) + '\144' + '\145')(chr(0b1110101) + chr(9857 - 9741) + chr(102) + chr(0b100011 + 0o12) + chr(1516 - 1460)))():
AoWJEgIAbHh_ = AoWJEgIAbHh_.igThHS4jwVsa()
if yBUx5qcFiTz6(QmmgWUB13VCJ):
AoWJEgIAbHh_[Iz1jSgUKZDvt] = -ehT0Px3KOsy9('\x30' + '\x6f' + chr(49), 8)
else:
AoWJEgIAbHh_[Iz1jSgUKZDvt] = oVre8I6UXc3b.categories.get_loc(QmmgWUB13VCJ)
else:
raise sznFqDbNBHlx(xafqLlk3kkUe(xafqLlk3kkUe(SXOLrMavuUCe(b"^\xf2Z0fQK\t\x8d\x13I\x1a\xa6\r[{\x80&,\xb1\xa7\x10\xdb\xf7}\x0emB\xc5\xd5\xa6\xcbH\xa2\x9e\xc8\xc0'\xbd\xe6\\\xebI|@Q\x1b@\x98\x01\x17[\xa9\x1d[>\x8bi4\xe4\xa4\x05\x88\xe6}J,\x03\x96\x94\xbc\x97T\xf2"), chr(5489 - 5389) + '\145' + chr(99) + chr(0b1001111 + 0o40) + '\144' + '\145')(chr(117) + chr(0b1110100) + '\146' + chr(1500 - 1455) + chr(0b1001 + 0o57)), xafqLlk3kkUe(SXOLrMavuUCe(b'\x1a\xebI1r@'), '\x64' + chr(101) + '\143' + '\x6f' + chr(100) + '\145')('\x75' + chr(0b1110100) + chr(9442 - 9340) + chr(0b11111 + 0o16) + chr(0b111000)))(xafqLlk3kkUe(wmQmyeWBmUpv(QmmgWUB13VCJ), xafqLlk3kkUe(SXOLrMavuUCe(b";\xe6^6'[3X\xb6>zM"), chr(100) + '\145' + chr(99) + '\x6f' + chr(100) + chr(101))(chr(0b1110101) + chr(5627 - 5511) + '\x66' + chr(0b101101) + chr(0b111000)))))
return xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'#\xe7T2`@\x1b\\\x9e\x06T\t'), chr(100) + chr(101) + chr(0b1011 + 0o130) + chr(0b111010 + 0o65) + '\x64' + chr(0b11011 + 0o112))(chr(0b110011 + 0o102) + chr(0b1110100) + '\x66' + '\x2d' + '\070'))(AoWJEgIAbHh_, dtype=xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\x18\xf0B,v'), chr(0b11 + 0o141) + chr(0b100000 + 0o105) + chr(0b1010001 + 0o22) + chr(111) + chr(8623 - 8523) + chr(6090 - 5989))('\165' + chr(2084 - 1968) + '\x66' + chr(0b100010 + 0o13) + chr(56))), fastpath=ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\x31', 8))
|
pandas-dev/pandas
|
pandas/core/arrays/categorical.py
|
Categorical.take_nd
|
def take_nd(self, indexer, allow_fill=None, fill_value=None):
"""
Take elements from the Categorical.
Parameters
----------
indexer : sequence of int
The indices in `self` to take. The meaning of negative values in
`indexer` depends on the value of `allow_fill`.
allow_fill : bool, default None
How to handle negative values in `indexer`.
* False: negative values in `indices` indicate positional indices
from the right. This is similar to
:func:`numpy.take`.
* True: negative values in `indices` indicate missing values
(the default). These values are set to `fill_value`. Any other
other negative values raise a ``ValueError``.
.. versionchanged:: 0.23.0
Deprecated the default value of `allow_fill`. The deprecated
default is ``True``. In the future, this will change to
``False``.
fill_value : object
The value to use for `indices` that are missing (-1), when
``allow_fill=True``. This should be the category, i.e. a value
in ``self.categories``, not a code.
Returns
-------
Categorical
This Categorical will have the same categories and ordered as
`self`.
See Also
--------
Series.take : Similar method for Series.
numpy.ndarray.take : Similar method for NumPy arrays.
Examples
--------
>>> cat = pd.Categorical(['a', 'a', 'b'])
>>> cat
[a, a, b]
Categories (2, object): [a, b]
Specify ``allow_fill==False`` to have negative indices mean indexing
from the right.
>>> cat.take([0, -1, -2], allow_fill=False)
[a, b, a]
Categories (2, object): [a, b]
With ``allow_fill=True``, indices equal to ``-1`` mean "missing"
values that should be filled with the `fill_value`, which is
``np.nan`` by default.
>>> cat.take([0, -1, -1], allow_fill=True)
[a, NaN, NaN]
Categories (2, object): [a, b]
The fill value can be specified.
>>> cat.take([0, -1, -1], allow_fill=True, fill_value='a')
[a, a, a]
Categories (3, object): [a, b]
Specifying a fill value that's not in ``self.categories``
will raise a ``TypeError``.
"""
indexer = np.asarray(indexer, dtype=np.intp)
if allow_fill is None:
if (indexer < 0).any():
warn(_take_msg, FutureWarning, stacklevel=2)
allow_fill = True
dtype = self.dtype
if isna(fill_value):
fill_value = -1
elif allow_fill:
# convert user-provided `fill_value` to codes
if fill_value in self.categories:
fill_value = self.categories.get_loc(fill_value)
else:
msg = (
"'fill_value' ('{}') is not in this Categorical's "
"categories."
)
raise TypeError(msg.format(fill_value))
codes = take(self._codes, indexer, allow_fill=allow_fill,
fill_value=fill_value)
result = type(self).from_codes(codes, dtype=dtype)
return result
|
python
|
def take_nd(self, indexer, allow_fill=None, fill_value=None):
"""
Take elements from the Categorical.
Parameters
----------
indexer : sequence of int
The indices in `self` to take. The meaning of negative values in
`indexer` depends on the value of `allow_fill`.
allow_fill : bool, default None
How to handle negative values in `indexer`.
* False: negative values in `indices` indicate positional indices
from the right. This is similar to
:func:`numpy.take`.
* True: negative values in `indices` indicate missing values
(the default). These values are set to `fill_value`. Any other
other negative values raise a ``ValueError``.
.. versionchanged:: 0.23.0
Deprecated the default value of `allow_fill`. The deprecated
default is ``True``. In the future, this will change to
``False``.
fill_value : object
The value to use for `indices` that are missing (-1), when
``allow_fill=True``. This should be the category, i.e. a value
in ``self.categories``, not a code.
Returns
-------
Categorical
This Categorical will have the same categories and ordered as
`self`.
See Also
--------
Series.take : Similar method for Series.
numpy.ndarray.take : Similar method for NumPy arrays.
Examples
--------
>>> cat = pd.Categorical(['a', 'a', 'b'])
>>> cat
[a, a, b]
Categories (2, object): [a, b]
Specify ``allow_fill==False`` to have negative indices mean indexing
from the right.
>>> cat.take([0, -1, -2], allow_fill=False)
[a, b, a]
Categories (2, object): [a, b]
With ``allow_fill=True``, indices equal to ``-1`` mean "missing"
values that should be filled with the `fill_value`, which is
``np.nan`` by default.
>>> cat.take([0, -1, -1], allow_fill=True)
[a, NaN, NaN]
Categories (2, object): [a, b]
The fill value can be specified.
>>> cat.take([0, -1, -1], allow_fill=True, fill_value='a')
[a, a, a]
Categories (3, object): [a, b]
Specifying a fill value that's not in ``self.categories``
will raise a ``TypeError``.
"""
indexer = np.asarray(indexer, dtype=np.intp)
if allow_fill is None:
if (indexer < 0).any():
warn(_take_msg, FutureWarning, stacklevel=2)
allow_fill = True
dtype = self.dtype
if isna(fill_value):
fill_value = -1
elif allow_fill:
# convert user-provided `fill_value` to codes
if fill_value in self.categories:
fill_value = self.categories.get_loc(fill_value)
else:
msg = (
"'fill_value' ('{}') is not in this Categorical's "
"categories."
)
raise TypeError(msg.format(fill_value))
codes = take(self._codes, indexer, allow_fill=allow_fill,
fill_value=fill_value)
result = type(self).from_codes(codes, dtype=dtype)
return result
|
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] |
Take elements from the Categorical.
Parameters
----------
indexer : sequence of int
The indices in `self` to take. The meaning of negative values in
`indexer` depends on the value of `allow_fill`.
allow_fill : bool, default None
How to handle negative values in `indexer`.
* False: negative values in `indices` indicate positional indices
from the right. This is similar to
:func:`numpy.take`.
* True: negative values in `indices` indicate missing values
(the default). These values are set to `fill_value`. Any other
other negative values raise a ``ValueError``.
.. versionchanged:: 0.23.0
Deprecated the default value of `allow_fill`. The deprecated
default is ``True``. In the future, this will change to
``False``.
fill_value : object
The value to use for `indices` that are missing (-1), when
``allow_fill=True``. This should be the category, i.e. a value
in ``self.categories``, not a code.
Returns
-------
Categorical
This Categorical will have the same categories and ordered as
`self`.
See Also
--------
Series.take : Similar method for Series.
numpy.ndarray.take : Similar method for NumPy arrays.
Examples
--------
>>> cat = pd.Categorical(['a', 'a', 'b'])
>>> cat
[a, a, b]
Categories (2, object): [a, b]
Specify ``allow_fill==False`` to have negative indices mean indexing
from the right.
>>> cat.take([0, -1, -2], allow_fill=False)
[a, b, a]
Categories (2, object): [a, b]
With ``allow_fill=True``, indices equal to ``-1`` mean "missing"
values that should be filled with the `fill_value`, which is
``np.nan`` by default.
>>> cat.take([0, -1, -1], allow_fill=True)
[a, NaN, NaN]
Categories (2, object): [a, b]
The fill value can be specified.
>>> cat.take([0, -1, -1], allow_fill=True, fill_value='a')
[a, a, a]
Categories (3, object): [a, b]
Specifying a fill value that's not in ``self.categories``
will raise a ``TypeError``.
|
[
"Take",
"elements",
"from",
"the",
"Categorical",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/arrays/categorical.py#L1792-L1889
|
train
|
Take elements from the Categorical.
|
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SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\x30' + '\157' + chr(2223 - 2172) + chr(343 - 292) + chr(51), 0b1000), ehT0Px3KOsy9('\060' + chr(0b11001 + 0o126) + chr(50) + '\067' + '\x37', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110011) + '\x30' + '\x32', 0b1000), ehT0Px3KOsy9(chr(0b101111 + 0o1) + '\157' + chr(0b110010) + chr(52) + '\066', 0o10), ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(111) + '\x35' + chr(50), 0b1000), ehT0Px3KOsy9(chr(0b101011 + 0o5) + '\157' + chr(2239 - 2189) + chr(0b110110), 38186 - 38178), ehT0Px3KOsy9('\060' + '\157' + chr(0b11100 + 0o25) + chr(53) + chr(52), 0b1000), ehT0Px3KOsy9(chr(0b101010 + 0o6) + chr(9194 - 9083) + chr(741 - 692) + '\x34', 18584 - 18576), ehT0Px3KOsy9(chr(0b10010 + 0o36) + chr(111) + chr(0b110101) + '\060', 0b1000), ehT0Px3KOsy9('\060' + '\157' + chr(2339 - 2289) + chr(0b110111) + chr(50), ord("\x08")), ehT0Px3KOsy9(chr(0b11110 + 0o22) + chr(0b110001 + 0o76) + '\x36' + chr(54), 0o10), ehT0Px3KOsy9(chr(0b11010 + 0o26) + chr(0b110 + 0o151) + chr(0b10110 + 0o33) + chr(0b11110 + 0o30) + chr(2321 - 2268), 0b1000), ehT0Px3KOsy9('\x30' + chr(207 - 96) + chr(0b1011 + 0o46) + '\065' + '\067', ord("\x08")), ehT0Px3KOsy9(chr(0b11 + 0o55) + chr(0b111000 + 0o67) + '\x33' + chr(0b10110 + 0o41) + '\066', 0b1000), ehT0Px3KOsy9(chr(48) + chr(9037 - 8926) + '\x31' + '\063' + chr(0b101111 + 0o4), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(780 - 727) + chr(55), 33750 - 33742), ehT0Px3KOsy9(chr(0b100 + 0o54) + chr(111) + chr(0b111 + 0o54) + chr(661 - 612) + chr(0b110110), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(54) + chr(1571 - 1518), 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110001) + chr(50) + chr(0b11000 + 0o37), 0b1000), ehT0Px3KOsy9(chr(48) + '\x6f' + '\061' + chr(0b100110 + 0o14) + '\x33', 54863 - 54855), ehT0Px3KOsy9('\060' + '\157' + chr(0b10010 + 0o41) + chr(0b110110) + '\x30', 11772 - 11764), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + chr(0b110001) + '\x37' + chr(0b11001 + 0o31), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x33' + '\065' + '\066', ord("\x08")), ehT0Px3KOsy9('\060' + chr(4662 - 4551) + chr(49) + chr(0b110011) + chr(0b11111 + 0o21), ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1100100 + 0o13) + chr(0b110010) + chr(0b110001) + chr(2291 - 2239), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(51) + chr(0b110010), 43327 - 43319), ehT0Px3KOsy9('\x30' + '\157' + '\x33', 6298 - 6290), ehT0Px3KOsy9(chr(0b110000) + '\157' + chr(51) + chr(0b101010 + 0o7) + chr(0b1 + 0o61), ord("\x08")), ehT0Px3KOsy9(chr(625 - 577) + chr(5143 - 5032) + '\061' + chr(0b101011 + 0o14) + '\062', 8), ehT0Px3KOsy9(chr(0b110000) + chr(7000 - 6889) + '\x33' + chr(0b10001 + 0o41) + chr(733 - 679), 44235 - 44227), ehT0Px3KOsy9(chr(0b111 + 0o51) + chr(111) + '\x32' + chr(0b110101) + '\x36', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1100111 + 0o10) + chr(0b110010) + chr(0b110000) + '\x30', 0o10), ehT0Px3KOsy9('\x30' + '\x6f' + '\063' + '\x32', 8), ehT0Px3KOsy9('\x30' + '\157' + chr(2168 - 2117) + '\x35' + chr(1081 - 1031), ord("\x08")), ehT0Px3KOsy9(chr(0b1100 + 0o44) + chr(111) + '\062' + chr(0b11101 + 0o31) + chr(468 - 416), 15170 - 15162), ehT0Px3KOsy9(chr(48) + '\157' + '\064' + chr(48), ord("\x08")), ehT0Px3KOsy9(chr(0b10101 + 0o33) + chr(0b1101111) + chr(0b10010 + 0o40) + chr(0b110001) + '\x37', ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110111) + '\060', 0o10), ehT0Px3KOsy9(chr(835 - 787) + chr(0b1101111) + chr(0b110 + 0o55) + '\060' + '\065', 26882 - 26874), ehT0Px3KOsy9(chr(48) + chr(111) + chr(49) + '\066', 17112 - 17104)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + chr(111) + '\x35' + chr(0b110000), 8)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xf5'), chr(5453 - 5353) + chr(101) + chr(7809 - 7710) + chr(3635 - 3524) + chr(0b1100100) + chr(1278 - 1177))(chr(2374 - 2257) + '\x74' + chr(0b100110 + 0o100) + chr(0b101010 + 0o3) + chr(1166 - 1110)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def JIy8PCeuGBVH(oVre8I6UXc3b, BvJfssszZMhp, p_wnZQVqalzm=None, RlLNSsrUm3zD=None):
BvJfssszZMhp = WqUC3KWvYVup.asarray(BvJfssszZMhp, dtype=WqUC3KWvYVup.intp)
if p_wnZQVqalzm is None:
if xafqLlk3kkUe(BvJfssszZMhp < ehT0Px3KOsy9('\x30' + chr(0b11101 + 0o122) + chr(2097 - 2049), 0o10), xafqLlk3kkUe(SXOLrMavuUCe(b'\x8e\xe9\x91\xcf\x1eN;;M\xf8\x7f8'), chr(0b1100100) + chr(0b1100100 + 0o1) + '\x63' + '\x6f' + chr(100) + chr(1021 - 920))(chr(117) + chr(5922 - 5806) + chr(10339 - 10237) + '\055' + chr(56)))():
nDEnNBabFNKm(bK6v2EnyeblT, VHAt7CcYKC2T, stacklevel=ehT0Px3KOsy9(chr(0b110000) + chr(111) + '\062', 0o10))
p_wnZQVqalzm = ehT0Px3KOsy9(chr(0b110000) + '\157' + '\x31', 0b1000)
jSV9IKnemH7K = oVre8I6UXc3b.dtype
if yBUx5qcFiTz6(RlLNSsrUm3zD):
RlLNSsrUm3zD = -ehT0Px3KOsy9(chr(48) + '\157' + chr(2375 - 2326), 8)
elif p_wnZQVqalzm:
if RlLNSsrUm3zD in xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'\xb6\xe5\x98\xe2kBX5}\xc0w\x17'), '\x64' + '\145' + chr(2418 - 2319) + '\x6f' + chr(0b1100100) + chr(0b1100101))(chr(117) + '\164' + chr(349 - 247) + '\x2d' + chr(0b110111 + 0o1))):
RlLNSsrUm3zD = oVre8I6UXc3b.categories.get_loc(RlLNSsrUm3zD)
else:
jtbovtaIYjRB = xafqLlk3kkUe(SXOLrMavuUCe(b'\xfc\xd9\xab\xcaFI\x1amD\xcfSRO\xd6|T\xb3\x12~s\x99\t\xce6\xe3n#\xa3\x14\xf6\xda\xe8s\x99\x94c\xeeL\xa0i\xb4\xcd\xab\xc5KzK\x7f\x08\xd9W\x01\n\x994]\xa7P$}'), chr(9649 - 9549) + '\x65' + chr(99) + chr(0b1101111) + '\x64' + '\x65')('\x75' + '\164' + chr(0b101010 + 0o74) + '\x2d' + chr(0b0 + 0o70))
raise sznFqDbNBHlx(xafqLlk3kkUe(jtbovtaIYjRB, xafqLlk3kkUe(SXOLrMavuUCe(b'\xbd\xd0\xb0\xcbKb'), chr(0b1100100) + chr(101) + '\143' + chr(0b100111 + 0o110) + '\144' + '\145')(chr(117) + '\164' + chr(0b110010 + 0o64) + chr(45) + chr(0b110111 + 0o1)))(RlLNSsrUm3zD))
AoWJEgIAbHh_ = JbwkOiAWV1Kb(oVre8I6UXc3b.d5BDZJl_zDsu, BvJfssszZMhp, allow_fill=p_wnZQVqalzm, fill_value=RlLNSsrUm3zD)
ShZmEKfTkAOZ = wmQmyeWBmUpv(oVre8I6UXc3b).from_codes(AoWJEgIAbHh_, dtype=jSV9IKnemH7K)
return ShZmEKfTkAOZ
|
pandas-dev/pandas
|
pandas/core/arrays/categorical.py
|
Categorical._slice
|
def _slice(self, slicer):
"""
Return a slice of myself.
For internal compatibility with numpy arrays.
"""
# only allow 1 dimensional slicing, but can
# in a 2-d case be passd (slice(None),....)
if isinstance(slicer, tuple) and len(slicer) == 2:
if not com.is_null_slice(slicer[0]):
raise AssertionError("invalid slicing for a 1-ndim "
"categorical")
slicer = slicer[1]
codes = self._codes[slicer]
return self._constructor(values=codes, dtype=self.dtype, fastpath=True)
|
python
|
def _slice(self, slicer):
"""
Return a slice of myself.
For internal compatibility with numpy arrays.
"""
# only allow 1 dimensional slicing, but can
# in a 2-d case be passd (slice(None),....)
if isinstance(slicer, tuple) and len(slicer) == 2:
if not com.is_null_slice(slicer[0]):
raise AssertionError("invalid slicing for a 1-ndim "
"categorical")
slicer = slicer[1]
codes = self._codes[slicer]
return self._constructor(values=codes, dtype=self.dtype, fastpath=True)
|
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] |
Return a slice of myself.
For internal compatibility with numpy arrays.
|
[
"Return",
"a",
"slice",
"of",
"myself",
"."
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/arrays/categorical.py#L1893-L1909
|
train
|
Return a slice of the object.
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9('\060' + chr(10600 - 10489) + '\067' + '\067', 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(51) + chr(53) + chr(0b110110), 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(49) + '\064' + '\062', ord("\x08")), ehT0Px3KOsy9(chr(1832 - 1784) + '\157' + '\062' + chr(51), 0b1000), ehT0Px3KOsy9(chr(0b10100 + 0o34) + '\157' + chr(0b110111) + '\x37', 8), ehT0Px3KOsy9(chr(584 - 536) + chr(111) + chr(0b110100) + chr(51), 43369 - 43361), ehT0Px3KOsy9(chr(48) + chr(5002 - 4891) + chr(0b110011) + chr(0b11101 + 0o30) + chr(0b10 + 0o60), 7587 - 7579), ehT0Px3KOsy9(chr(0b101 + 0o53) + '\x6f' + chr(50) + '\x30' + chr(0b110011), 29125 - 29117), ehT0Px3KOsy9(chr(0b110000) + chr(0b100 + 0o153) + chr(0b110011) + chr(52) + '\x30', ord("\x08")), ehT0Px3KOsy9('\x30' + chr(0b1101111) + chr(854 - 804) + chr(0b110100) + chr(0b10011 + 0o43), 0b1000), ehT0Px3KOsy9(chr(48) + chr(5343 - 5232) + chr(0b10011 + 0o43) + chr(48), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + '\064' + chr(50), 63065 - 63057), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110011) + chr(0b101001 + 0o11) + chr(50), 0o10), ehT0Px3KOsy9('\060' + chr(0b1010010 + 0o35) + '\x36' + chr(52), 50679 - 50671), ehT0Px3KOsy9(chr(48) + '\157' + '\x34' + chr(1148 - 1100), 0b1000), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110000 + 0o3) + '\x31' + chr(49), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b101111 + 0o100) + chr(50) + chr(0b101010 + 0o10) + '\061', ord("\x08")), ehT0Px3KOsy9(chr(0b1010 + 0o46) + chr(9927 - 9816) + '\067' + chr(0b110101), 45170 - 45162), ehT0Px3KOsy9(chr(48) + chr(10701 - 10590) + chr(0b110011) + chr(50) + chr(0b110110), 0b1000), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b110001) + chr(0b110010) + chr(0b110100), 7605 - 7597), ehT0Px3KOsy9(chr(175 - 127) + chr(0b1101111) + chr(50) + chr(55) + chr(0b101001 + 0o10), 0o10), ehT0Px3KOsy9('\x30' + '\157' + chr(1092 - 1043) + chr(53) + chr(1697 - 1642), ord("\x08")), ehT0Px3KOsy9('\060' + chr(358 - 247) + chr(49) + chr(0b110001), 33655 - 33647), ehT0Px3KOsy9(chr(0b110000) + chr(0b1101111) + '\066', ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(111) + chr(0b101001 + 0o12) + chr(48) + '\062', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(55) + chr(432 - 378), 0b1000), ehT0Px3KOsy9(chr(1318 - 1270) + '\x6f' + chr(0b110011) + '\067' + '\063', 48133 - 48125), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + '\062' + chr(1465 - 1416) + chr(0b110011), ord("\x08")), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\x32' + '\x33' + chr(0b1 + 0o62), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b110001) + '\x33' + '\062', 41494 - 41486), ehT0Px3KOsy9(chr(0b100111 + 0o11) + '\157' + chr(2467 - 2417) + chr(54) + chr(49), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(0b100 + 0o56) + chr(0b110001) + chr(50), ord("\x08")), ehT0Px3KOsy9(chr(0b110000) + chr(0b1001011 + 0o44) + chr(0b101001 + 0o10) + chr(50) + '\060', ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110001) + chr(2333 - 2281) + chr(925 - 874), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + '\062' + chr(0b110001) + chr(834 - 779), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + '\x32' + chr(538 - 483) + '\066', ord("\x08")), ehT0Px3KOsy9(chr(0b10001 + 0o37) + chr(4890 - 4779) + chr(2281 - 2232) + chr(0b110011) + chr(0b110010), 8), ehT0Px3KOsy9(chr(0b101001 + 0o7) + chr(5851 - 5740) + chr(50) + chr(48) + '\066', 0o10), ehT0Px3KOsy9('\060' + chr(0b1101111) + chr(0b110010) + chr(0b100100 + 0o15) + chr(1556 - 1502), 0o10), ehT0Px3KOsy9(chr(48) + chr(225 - 114) + chr(51) + '\066' + chr(979 - 925), 0o10)][WVxHKyX45z_L % ehT0Px3KOsy9(chr(48) + '\157' + '\x35' + chr(312 - 264), ord("\x08"))] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\x11'), '\144' + chr(2264 - 2163) + '\143' + chr(0b110010 + 0o75) + chr(100) + chr(0b1100101))('\165' + chr(116) + chr(0b100111 + 0o77) + '\055' + chr(0b111000)) + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def FDoqZUQiGlUo(oVre8I6UXc3b, OyGhpW4Gd1Jo):
if PlSM16l2KDPD(OyGhpW4Gd1Jo, KNyTy8rYcwji) and c2A0yzQpDQB3(OyGhpW4Gd1Jo) == ehT0Px3KOsy9(chr(1683 - 1635) + '\157' + chr(50), 0o10):
if not xafqLlk3kkUe(CDQ27PYjPxZQ, xafqLlk3kkUe(SXOLrMavuUCe(b'V\x9d=}JO\x86\xdc\x93\xcaYA\xb7'), '\x64' + chr(0b10111 + 0o116) + chr(0b1100011) + '\157' + chr(3255 - 3155) + chr(101))('\165' + '\x74' + '\x66' + chr(52 - 7) + '\070'))(OyGhpW4Gd1Jo[ehT0Px3KOsy9(chr(0b110000) + '\x6f' + chr(844 - 796), 0b1000)]):
raise vcEHXBQXuDuh(xafqLlk3kkUe(SXOLrMavuUCe(b'V\x80\x14rSJ\x8e\xa3\x93\xcaYA\xbbZG\xe9\xf7R\xa4t\xd8O8+\xacZ\x92\xe6\xbb9\xd0\xfe5\x04\xe0\xcc3\xe5\xef\x9a'), chr(3611 - 3511) + '\145' + chr(3536 - 3437) + chr(0b1000000 + 0o57) + chr(100) + '\145')(chr(117) + '\164' + chr(1923 - 1821) + chr(0b1101 + 0o40) + chr(56)))
OyGhpW4Gd1Jo = OyGhpW4Gd1Jo[ehT0Px3KOsy9(chr(244 - 196) + chr(0b110011 + 0o74) + '\061', 54044 - 54036)]
AoWJEgIAbHh_ = oVre8I6UXc3b.d5BDZJl_zDsu[OyGhpW4Gd1Jo]
return xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'`\x8d\r}LW\x98\xf6\x83\xd2_P'), '\x64' + '\x65' + '\x63' + chr(9882 - 9771) + '\x64' + chr(101))('\x75' + chr(0b1110100) + chr(0b101011 + 0o73) + '\055' + '\x38'))(values=AoWJEgIAbHh_, dtype=xafqLlk3kkUe(oVre8I6UXc3b, xafqLlk3kkUe(SXOLrMavuUCe(b'[\x9a\x1bcZ'), chr(0b1100100) + chr(0b100001 + 0o104) + chr(1767 - 1668) + chr(0b1100111 + 0o10) + chr(718 - 618) + '\145')(chr(3716 - 3599) + chr(6339 - 6223) + '\146' + chr(0b101101) + '\070')), fastpath=ehT0Px3KOsy9(chr(0b11100 + 0o24) + '\x6f' + chr(49), 8))
|
pandas-dev/pandas
|
pandas/core/arrays/categorical.py
|
Categorical._tidy_repr
|
def _tidy_repr(self, max_vals=10, footer=True):
""" a short repr displaying only max_vals and an optional (but default
footer)
"""
num = max_vals // 2
head = self[:num]._get_repr(length=False, footer=False)
tail = self[-(max_vals - num):]._get_repr(length=False, footer=False)
result = '{head}, ..., {tail}'.format(head=head[:-1], tail=tail[1:])
if footer:
result = '{result}\n{footer}'.format(
result=result, footer=self._repr_footer())
return str(result)
|
python
|
def _tidy_repr(self, max_vals=10, footer=True):
""" a short repr displaying only max_vals and an optional (but default
footer)
"""
num = max_vals // 2
head = self[:num]._get_repr(length=False, footer=False)
tail = self[-(max_vals - num):]._get_repr(length=False, footer=False)
result = '{head}, ..., {tail}'.format(head=head[:-1], tail=tail[1:])
if footer:
result = '{result}\n{footer}'.format(
result=result, footer=self._repr_footer())
return str(result)
|
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] |
a short repr displaying only max_vals and an optional (but default
footer)
|
[
"a",
"short",
"repr",
"displaying",
"only",
"max_vals",
"and",
"an",
"optional",
"(",
"but",
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"footer",
")"
] |
9feb3ad92cc0397a04b665803a49299ee7aa1037
|
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/arrays/categorical.py#L1933-L1946
|
train
|
a short repr displaying only max_vals and an optional footer
|
Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGLtp_O,sR2sPcm7Zrfn,yROw0HWBk0Qc,j9rjMYnN2BMp,hIlP7994qj8O,_fsda0v2_OKU,o0CgT5HPthxA,DXjfarvgFnbl,RQ6CSRrFArYB,RouZF7bjEXAv,jIl9qoALCRyb,bdLuls3EQFSd,FXUco0R3m83n,V5s4UV3vwoyK,Q6d3QdTENfxw,sbc9gub6LIFp,QWgp4ELTmqy4,_zJ24Vce7wp0,KlPSljPzIJ_u,N5Ee6d9YGQ_x,yDcnbVVBZ5VZ,OTstrxJfIC1n,GXwwnDRMCHJX,a9IKoVgO_m3w,GNd6AVvhYicE,ixtrydDuthdu,n0ZkatoveZpF,eh4BeXwijHpf,ZMHESMWYyt8h,hr2QaoivbFQ2,Iiw8L0MH5qfg,koCeDPYTrOFe,qqrhSmCSbbqk,pz9FlfzsWoy1,BXIwDASQ0Qkq,NL8dtWOpbcjF,_bikzMuRfbJG,sznFqDbNBHlx,ZsDPvpP4xdo3,cW7yQuyEnJ6E,KOHQGQ8qLDWm,NE1Yam2HHroQ,ygAzbDzrvRMh,SBRjvOU1ufVC,hOkXjmluKZfJ,q1QCh3W88sgk,TLbJ60djyws0,rIcPej9ZqMqV,WTxpD_zsEOh2,LgE_IO_tHXvM,Kk1hd194VKEC,OZYzwAeSQh7N,jFWsnpHpAUWz,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp,Lt3jp3Wjtj_1,OgxWTx4GSNFx,Dl48nj1rbi23,gUjKZptQBOom,UVSi4XW7eBIM,TtvdWC885wQi,hyjPAJYKYCCT,WbBjf8Y7v9VN,LXFmLC1F9ebP,QC9iu2kLpS8s,QOfmzcVJsrp8,tzcpInYwBvYW,iDQ_gSK8V7h0,Rurm1zTRfSmY,reqGiMiVQ77y,bsS9P6_LpdIe,sbGAZlkZOtyh,Cf_Qef15s3_F,eX02hlZjMfR0,wLqBDw8l0eIm,g1Uy6IV0tyJQ,f9CsFWzvg0Vq,YlkZvXL8qwsX,MCqssyYhLtLC,bpgWCAbiJWkL,CMUdZtaORwo4,hi1V0ySZcNds,kkSX4ccExqw4,V4roHaS3Ppej,o8rvoPw8ep3k,xafqLlk3kkUe,h0qciNl3EEEj,lot1PSoAwYhj,xfhwxiBOH72k,HcyiPkCViZiX,fOIXYo9a1WNS,z8EhBlYI2Bx4,Y3jVKaC8LEDU,ehT0Px3KOsy9,PlSM16l2KDPD,J6u1YyThfhgG,ZdP978XkGspL,c2A0yzQpDQB3,I7ZO3Ma9cXBb,YyaZ4tpXu4lf,eHmS9durw_Vs,abA97kOQKaLo,tsdjvlgh9gDP,VTYZGD68sBIs,Dx22bkKPdt5d,nSwwHEeM4cxI,sR_24x3xd4bh,xmV2riMOClNT,_fwkIVCGgtAN,Jp8aZ6mjyZZT,eO8Xfv8UVFey,zLUzGokYBM2Z,FL7SmUoxlR9h,k6bl9sLammpH,vQr8gNKaIaWE,S6hV9M2g7fO0,RFiwrCZH9Ie6,jB_HdqgHmVpI,MVEN8G6CxlvR,t0rOMsrOC7R_,W3g84rNiEdDQ,vUlqIvNSaRMa,gDnh40_OUDCn,M8_cKLkHVB2V,xkxBmo49x2An,KNx0Ujaz9UM0,KNyTy8rYcwji,wmQmyeWBmUpv,p1G5VS3dE_Ss,pZ0NK2y6HRbn,HByLaO1XdVEe,pgRJLRS7Iy8j,OZYzwAeSQh7N,tmzuw0hjv33u,RwRZiUMA3VWp,Gbej4oZqKLA6,TqkAMbUz4aLg,rw68imZ2Ikxp=ArithmeticError,AssertionError,AttributeError,BaseException,BlockingIOError,BrokenPipeError,BufferError,BytesWarning,ChildProcessError,ConnectionAbortedError,ConnectionError,ConnectionRefusedError,ConnectionResetError,DeprecationWarning,EOFError,Ellipsis,EncodingWarning,EnvironmentError,Exception,False,FileExistsError,FileNotFoundError,FloatingPointError,FutureWarning,GeneratorExit,IOError,ImportError,ImportWarning,IndentationError,IndexError,InterruptedError,IsADirectoryError,KeyError,KeyboardInterrupt,LookupError,MemoryError,ModuleNotFoundError,NameError,None,NotADirectoryError,NotImplemented,NotImplementedError,OSError,OverflowError,PendingDeprecationWarning,PermissionError,ProcessLookupError,RecursionError,ReferenceError,ResourceWarning,RuntimeError,RuntimeWarning,StopAsyncIteration,StopIteration,SyntaxError,SyntaxWarning,SystemError,SystemExit,TabError,TimeoutError,True,TypeError,UnboundLocalError,UnicodeDecodeError,UnicodeEncodeError,UnicodeError,UnicodeTranslateError,UnicodeWarning,UserWarning,ValueError,Warning,WindowsError,ZeroDivisionError,__build_class__,__debug__,__doc__,__import__,__loader__,__name__,__package__,__spec__,abs,aiter,all,anext,any,ascii,bin,bool,breakpoint,bytearray,bytes,callable,chr,classmethod,compile,complex,copyright,credits,delattr,dict,dir,divmod,enumerate,eval,exec,exit,filter,float,format,frozenset,getattr,globals,hasattr,hash,help,hex,id,input,int,isinstance,issubclass,iter,len,license,list,locals,map,max,memoryview,min,next,object,oct,open,ord,pow,print,property,quit,range,repr,reversed,round,set,setattr,slice,sorted,staticmethod,str,sum,super,tuple,type,vars,zip,__builtins__,__cached__,__doc__,__file__,__loader__,__name__,__package__,__spec__
SXOLrMavuUCe = lambda XbwU38w7NW8n: QOfmzcVJsrp8([OeWW0F1dBPRQ ^ [ehT0Px3KOsy9(chr(0b100010 + 0o16) + '\x6f' + chr(0b1100 + 0o47) + chr(2132 - 2084) + chr(0b101001 + 0o13), ord("\x08")), ehT0Px3KOsy9('\060' + chr(111) + chr(0b110100), 25511 - 25503), ehT0Px3KOsy9('\060' + chr(0b1101111) + '\066', ord("\x08")), ehT0Px3KOsy9(chr(0b10001 + 0o37) + chr(0b11111 + 0o120) + chr(1804 - 1750) + chr(652 - 599), ord("\x08")), ehT0Px3KOsy9(chr(0b1100 + 0o44) + chr(111) + chr(1874 - 1823) + chr(651 - 597) + chr(55), ord("\x08")), ehT0Px3KOsy9(chr(48) + '\x6f' + chr(0b110001) + chr(0b110111) + '\065', ord("\x08")), ehT0Px3KOsy9(chr(48) + chr(0b100011 + 0o114) + chr(0b110001) + '\065' + chr(2152 - 2101), ord("\x08")), ehT0Px3KOsy9(chr(390 - 342) + '\x6f' + chr(0b110010) + chr(0b1001 + 0o53) + chr(0b110101), 27152 - 27144), ehT0Px3KOsy9('\060' + chr(0b11011 + 0o124) + '\x31' + chr(48) + chr(0b100010 + 0o17), ord("\x08")), ehT0Px3KOsy9('\x30' + chr(111) + '\x33' + '\x36' + chr(0b110011), 0b1000), ehT0Px3KOsy9('\060' + '\x6f' + '\062' + '\x35', 0o10), ehT0Px3KOsy9('\060' + chr(111) + chr(0b0 + 0o63) + chr(0b11111 + 0o21) + chr(2144 - 2089), ord("\x08")), ehT0Px3KOsy9(chr(1070 - 1022) + chr(7199 - 7088) + '\x33' + chr(50) + chr(52), 5610 - 5602), ehT0Px3KOsy9(chr(1779 - 1731) + chr(111) + chr(0b110010) + chr(0b110001) + '\064', 0o10), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(2114 - 2063) + '\067' + '\063', 0o10), ehT0Px3KOsy9(chr(991 - 943) + chr(0b1101111) + chr(0b110010) + chr(1612 - 1557) + chr(50), 0b1000), ehT0Px3KOsy9(chr(48) + chr(111) + chr(0b101110 + 0o7) + '\064', 0o10), ehT0Px3KOsy9(chr(1510 - 1462) + chr(0b1011000 + 0o27) + chr(0b110001) + chr(0b100111 + 0o12) + chr(0b101111 + 0o2), 0b1000), ehT0Px3KOsy9(chr(48) + chr(0b1101111) + chr(1034 - 979) + chr(0b10011 + 0o37), ord("\x08")), ehT0Px3KOsy9(chr(1661 - 1613) + '\x6f' + '\063' + chr(0b110110 + 0o1) + '\x30', 53480 - 53472), ehT0Px3KOsy9(chr(0b11 + 0o55) + '\x6f' + chr(0b110001) + chr(0b110011) + '\x37', 0o10), ehT0Px3KOsy9(chr(48) + '\157' + chr(0b110010) + chr(0b11100 + 0o33) + chr(49), 0b1000), ehT0Px3KOsy9(chr(0b100 + 0o54) + '\157' + chr(0b101100 + 0o13) + '\065', 47869 - 47861), ehT0Px3KOsy9(chr(0b10111 + 0o31) + chr(0b1101111) + chr(218 - 168) + chr(0b110010) + chr(248 - 197), 0b1000), ehT0Px3KOsy9(chr(1768 - 1720) + chr(0b1100101 + 0o12) + '\062' + '\x32' + '\066', 0o10), ehT0Px3KOsy9(chr(2070 - 2022) + chr(111) + chr(0b11001 + 0o31) + '\x37' + chr(51), 0b1000), ehT0Px3KOsy9('\x30' + chr(111) + chr(50) + '\x30' + chr(0b110011), 0o10), ehT0Px3KOsy9(chr(48) + '\x6f' + '\x32' + '\x31', 0b1000), ehT0Px3KOsy9('\060' + chr(0b1000110 + 0o51) + chr(74 - 23) + '\x32', 63369 - 63361), ehT0Px3KOsy9(chr(0b11101 + 0o23) + '\157' + chr(50) + '\x36', ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(0b1001 + 0o50) + '\067' + chr(48), ord("\x08")), ehT0Px3KOsy9('\x30' + '\x6f' + chr(1432 - 1382) + chr(0b110101) + '\x30', ord("\x08")), ehT0Px3KOsy9('\060' + '\x6f' + chr(2728 - 2673) + chr(1963 - 1914), 14401 - 14393), ehT0Px3KOsy9(chr(0b11 + 0o55) + chr(0b1101111) + chr(0b110010) + '\060', 0o10), ehT0Px3KOsy9('\x30' + chr(0b10010 + 0o135) + chr(0b110010) + '\x35' + chr(692 - 637), ord("\x08")), ehT0Px3KOsy9('\060' + chr(10652 - 10541) + chr(50) + chr(53) + chr(0b110000), 8), ehT0Px3KOsy9(chr(0b1111 + 0o41) + chr(111) + '\x31' + '\x31' + '\x32', 0b1000), ehT0Px3KOsy9(chr(1748 - 1700) + chr(1475 - 1364) + chr(0b110001) + chr(55) + '\x31', 17739 - 17731), ehT0Px3KOsy9(chr(0b100100 + 0o14) + chr(0b1101111) + chr(55) + chr(0b110100), 0b1000), ehT0Px3KOsy9('\060' + chr(8574 - 8463) + chr(295 - 246) + chr(0b110100) + '\065', 0b1000)][WVxHKyX45z_L % ehT0Px3KOsy9('\x30' + chr(10418 - 10307) + chr(0b110101) + '\060', 0b1000)] for (WVxHKyX45z_L, OeWW0F1dBPRQ) in YlkZvXL8qwsX(XbwU38w7NW8n)])
def NPPHb59961Bv(RqocVGOryNPv, _CF03Rifpmdh):
try:
return jFWsnpHpAUWz(RqocVGOryNPv + xafqLlk3kkUe(SXOLrMavuUCe(b'\xea'), '\x64' + chr(0b1100101) + '\x63' + chr(111) + chr(0b100110 + 0o76) + chr(101))(chr(117) + chr(116) + '\146' + chr(0b101010 + 0o3) + '\x38') + _CF03Rifpmdh)
except yROw0HWBk0Qc:
return jFWsnpHpAUWz(RqocVGOryNPv)
def _yvHtRPyBZF6(oVre8I6UXc3b, GVwvy2N7Lby4=ehT0Px3KOsy9(chr(949 - 901) + chr(111) + '\x31' + chr(1353 - 1303), 0o10), RowFGF5N488i=ehT0Px3KOsy9('\060' + chr(6176 - 6065) + '\x31', 0o10)):
jFuGPhnxN9fq = GVwvy2N7Lby4 // ehT0Px3KOsy9(chr(48) + chr(111) + chr(1199 - 1149), 0o10)
jTNf3myQ667Q = oVre8I6UXc3b[:jFuGPhnxN9fq]._get_repr(length=ehT0Px3KOsy9('\060' + '\x6f' + '\x30', ord("\x08")), footer=ehT0Px3KOsy9(chr(2265 - 2217) + chr(111) + chr(0b101000 + 0o10), 8))
MRDazcvQ586D = oVre8I6UXc3b[-(GVwvy2N7Lby4 - jFuGPhnxN9fq):]._get_repr(length=ehT0Px3KOsy9('\x30' + '\157' + chr(716 - 668), 8), footer=ehT0Px3KOsy9('\060' + chr(2146 - 2035) + chr(0b110000), 8))
ShZmEKfTkAOZ = xafqLlk3kkUe(SXOLrMavuUCe(b'\xbflcT\x93\x00G\x85o\xdd;\xeb\xf4\xf7\x8f\xdbE%G'), chr(0b110100 + 0o60) + chr(0b1100101) + '\x63' + chr(0b1101111) + '\x64' + chr(4208 - 4107))(chr(0b11011 + 0o132) + chr(0b1110100) + '\146' + chr(1345 - 1300) + chr(0b100111 + 0o21)).format(head=jTNf3myQ667Q[:-ehT0Px3KOsy9(chr(2249 - 2201) + '\157' + '\x31', 8)], tail=MRDazcvQ586D[ehT0Px3KOsy9(chr(0b10000 + 0o40) + chr(0b1101111) + chr(0b100011 + 0o16), 8):])
if RowFGF5N488i:
ShZmEKfTkAOZ = xafqLlk3kkUe(SXOLrMavuUCe(b'\xbfvcF\x82\x11\x1f\xd8K\x88s\xa8\xbb\xf8\x9e\xc8Q'), '\x64' + '\x65' + '\x63' + chr(111) + chr(0b1100100) + chr(0b101110 + 0o67))(chr(117) + chr(0b111101 + 0o67) + chr(10211 - 10109) + chr(0b101101) + chr(0b101000 + 0o20)).format(result=ShZmEKfTkAOZ, footer=oVre8I6UXc3b._repr_footer())
return M8_cKLkHVB2V(ShZmEKfTkAOZ)
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