partition stringclasses 3
values | func_name stringlengths 1 134 | docstring stringlengths 1 46.9k | path stringlengths 4 223 | original_string stringlengths 75 104k | code stringlengths 75 104k | docstring_tokens listlengths 1 1.97k | repo stringlengths 7 55 | language stringclasses 1
value | url stringlengths 87 315 | code_tokens listlengths 19 28.4k | sha stringlengths 40 40 |
|---|---|---|---|---|---|---|---|---|---|---|---|
train | NDFrame.get | Get item from object for given key (DataFrame column, Panel slice,
etc.). Returns default value if not found.
Parameters
----------
key : object
Returns
-------
value : same type as items contained in object | pandas/core/generic.py | def get(self, key, default=None):
"""
Get item from object for given key (DataFrame column, Panel slice,
etc.). Returns default value if not found.
Parameters
----------
key : object
Returns
-------
value : same type as items contained in object
... | def get(self, key, default=None):
"""
Get item from object for given key (DataFrame column, Panel slice,
etc.). Returns default value if not found.
Parameters
----------
key : object
Returns
-------
value : same type as items contained in object
... | [
"Get",
"item",
"from",
"object",
"for",
"given",
"key",
"(",
"DataFrame",
"column",
"Panel",
"slice",
"etc",
".",
")",
".",
"Returns",
"default",
"value",
"if",
"not",
"found",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L3065-L3081 | [
"def",
"get",
"(",
"self",
",",
"key",
",",
"default",
"=",
"None",
")",
":",
"try",
":",
"return",
"self",
"[",
"key",
"]",
"except",
"(",
"KeyError",
",",
"ValueError",
",",
"IndexError",
")",
":",
"return",
"default"
] | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame._get_item_cache | Return the cached item, item represents a label indexer. | pandas/core/generic.py | def _get_item_cache(self, item):
"""Return the cached item, item represents a label indexer."""
cache = self._item_cache
res = cache.get(item)
if res is None:
values = self._data.get(item)
res = self._box_item_values(item, values)
cache[item] = res
... | def _get_item_cache(self, item):
"""Return the cached item, item represents a label indexer."""
cache = self._item_cache
res = cache.get(item)
if res is None:
values = self._data.get(item)
res = self._box_item_values(item, values)
cache[item] = res
... | [
"Return",
"the",
"cached",
"item",
"item",
"represents",
"a",
"label",
"indexer",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L3086-L3098 | [
"def",
"_get_item_cache",
"(",
"self",
",",
"item",
")",
":",
"cache",
"=",
"self",
".",
"_item_cache",
"res",
"=",
"cache",
".",
"get",
"(",
"item",
")",
"if",
"res",
"is",
"None",
":",
"values",
"=",
"self",
".",
"_data",
".",
"get",
"(",
"item",... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame._set_as_cached | Set the _cacher attribute on the calling object with a weakref to
cacher. | pandas/core/generic.py | def _set_as_cached(self, item, cacher):
"""Set the _cacher attribute on the calling object with a weakref to
cacher.
"""
self._cacher = (item, weakref.ref(cacher)) | def _set_as_cached(self, item, cacher):
"""Set the _cacher attribute on the calling object with a weakref to
cacher.
"""
self._cacher = (item, weakref.ref(cacher)) | [
"Set",
"the",
"_cacher",
"attribute",
"on",
"the",
"calling",
"object",
"with",
"a",
"weakref",
"to",
"cacher",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L3100-L3104 | [
"def",
"_set_as_cached",
"(",
"self",
",",
"item",
",",
"cacher",
")",
":",
"self",
".",
"_cacher",
"=",
"(",
"item",
",",
"weakref",
".",
"ref",
"(",
"cacher",
")",
")"
] | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame._iget_item_cache | Return the cached item, item represents a positional indexer. | pandas/core/generic.py | def _iget_item_cache(self, item):
"""Return the cached item, item represents a positional indexer."""
ax = self._info_axis
if ax.is_unique:
lower = self._get_item_cache(ax[item])
else:
lower = self._take(item, axis=self._info_axis_number)
return lower | def _iget_item_cache(self, item):
"""Return the cached item, item represents a positional indexer."""
ax = self._info_axis
if ax.is_unique:
lower = self._get_item_cache(ax[item])
else:
lower = self._take(item, axis=self._info_axis_number)
return lower | [
"Return",
"the",
"cached",
"item",
"item",
"represents",
"a",
"positional",
"indexer",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L3111-L3118 | [
"def",
"_iget_item_cache",
"(",
"self",
",",
"item",
")",
":",
"ax",
"=",
"self",
".",
"_info_axis",
"if",
"ax",
".",
"is_unique",
":",
"lower",
"=",
"self",
".",
"_get_item_cache",
"(",
"ax",
"[",
"item",
"]",
")",
"else",
":",
"lower",
"=",
"self",... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame._maybe_update_cacher | See if we need to update our parent cacher if clear, then clear our
cache.
Parameters
----------
clear : boolean, default False
clear the item cache
verify_is_copy : boolean, default True
provide is_copy checks | pandas/core/generic.py | def _maybe_update_cacher(self, clear=False, verify_is_copy=True):
"""
See if we need to update our parent cacher if clear, then clear our
cache.
Parameters
----------
clear : boolean, default False
clear the item cache
verify_is_copy : boolean, defaul... | def _maybe_update_cacher(self, clear=False, verify_is_copy=True):
"""
See if we need to update our parent cacher if clear, then clear our
cache.
Parameters
----------
clear : boolean, default False
clear the item cache
verify_is_copy : boolean, defaul... | [
"See",
"if",
"we",
"need",
"to",
"update",
"our",
"parent",
"cacher",
"if",
"clear",
"then",
"clear",
"our",
"cache",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L3145-L3177 | [
"def",
"_maybe_update_cacher",
"(",
"self",
",",
"clear",
"=",
"False",
",",
"verify_is_copy",
"=",
"True",
")",
":",
"cacher",
"=",
"getattr",
"(",
"self",
",",
"'_cacher'",
",",
"None",
")",
"if",
"cacher",
"is",
"not",
"None",
":",
"ref",
"=",
"cach... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame._slice | Construct a slice of this container.
kind parameter is maintained for compatibility with Series slicing. | pandas/core/generic.py | def _slice(self, slobj, axis=0, kind=None):
"""
Construct a slice of this container.
kind parameter is maintained for compatibility with Series slicing.
"""
axis = self._get_block_manager_axis(axis)
result = self._constructor(self._data.get_slice(slobj, axis=axis))
... | def _slice(self, slobj, axis=0, kind=None):
"""
Construct a slice of this container.
kind parameter is maintained for compatibility with Series slicing.
"""
axis = self._get_block_manager_axis(axis)
result = self._constructor(self._data.get_slice(slobj, axis=axis))
... | [
"Construct",
"a",
"slice",
"of",
"this",
"container",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L3185-L3199 | [
"def",
"_slice",
"(",
"self",
",",
"slobj",
",",
"axis",
"=",
"0",
",",
"kind",
"=",
"None",
")",
":",
"axis",
"=",
"self",
".",
"_get_block_manager_axis",
"(",
"axis",
")",
"result",
"=",
"self",
".",
"_constructor",
"(",
"self",
".",
"_data",
".",
... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame._check_is_chained_assignment_possible | Check if we are a view, have a cacher, and are of mixed type.
If so, then force a setitem_copy check.
Should be called just near setting a value
Will return a boolean if it we are a view and are cached, but a
single-dtype meaning that the cacher should be updated following
sett... | pandas/core/generic.py | def _check_is_chained_assignment_possible(self):
"""
Check if we are a view, have a cacher, and are of mixed type.
If so, then force a setitem_copy check.
Should be called just near setting a value
Will return a boolean if it we are a view and are cached, but a
single-d... | def _check_is_chained_assignment_possible(self):
"""
Check if we are a view, have a cacher, and are of mixed type.
If so, then force a setitem_copy check.
Should be called just near setting a value
Will return a boolean if it we are a view and are cached, but a
single-d... | [
"Check",
"if",
"we",
"are",
"a",
"view",
"have",
"a",
"cacher",
"and",
"are",
"of",
"mixed",
"type",
".",
"If",
"so",
"then",
"force",
"a",
"setitem_copy",
"check",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L3214-L3233 | [
"def",
"_check_is_chained_assignment_possible",
"(",
"self",
")",
":",
"if",
"self",
".",
"_is_view",
"and",
"self",
".",
"_is_cached",
":",
"ref",
"=",
"self",
".",
"_get_cacher",
"(",
")",
"if",
"ref",
"is",
"not",
"None",
"and",
"ref",
".",
"_is_mixed_t... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame._take | Return the elements in the given *positional* indices along an axis.
This means that we are not indexing according to actual values in
the index attribute of the object. We are indexing according to the
actual position of the element in the object.
This is the internal version of ``.ta... | pandas/core/generic.py | def _take(self, indices, axis=0, is_copy=True):
"""
Return the elements in the given *positional* indices along an axis.
This means that we are not indexing according to actual values in
the index attribute of the object. We are indexing according to the
actual position of the e... | def _take(self, indices, axis=0, is_copy=True):
"""
Return the elements in the given *positional* indices along an axis.
This means that we are not indexing according to actual values in
the index attribute of the object. We are indexing according to the
actual position of the e... | [
"Return",
"the",
"elements",
"in",
"the",
"given",
"*",
"positional",
"*",
"indices",
"along",
"an",
"axis",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L3353-L3397 | [
"def",
"_take",
"(",
"self",
",",
"indices",
",",
"axis",
"=",
"0",
",",
"is_copy",
"=",
"True",
")",
":",
"self",
".",
"_consolidate_inplace",
"(",
")",
"new_data",
"=",
"self",
".",
"_data",
".",
"take",
"(",
"indices",
",",
"axis",
"=",
"self",
... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.take | Return the elements in the given *positional* indices along an axis.
This means that we are not indexing according to actual values in
the index attribute of the object. We are indexing according to the
actual position of the element in the object.
Parameters
----------
... | pandas/core/generic.py | def take(self, indices, axis=0, convert=None, is_copy=True, **kwargs):
"""
Return the elements in the given *positional* indices along an axis.
This means that we are not indexing according to actual values in
the index attribute of the object. We are indexing according to the
a... | def take(self, indices, axis=0, convert=None, is_copy=True, **kwargs):
"""
Return the elements in the given *positional* indices along an axis.
This means that we are not indexing according to actual values in
the index attribute of the object. We are indexing according to the
a... | [
"Return",
"the",
"elements",
"in",
"the",
"given",
"*",
"positional",
"*",
"indices",
"along",
"an",
"axis",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L3399-L3489 | [
"def",
"take",
"(",
"self",
",",
"indices",
",",
"axis",
"=",
"0",
",",
"convert",
"=",
"None",
",",
"is_copy",
"=",
"True",
",",
"*",
"*",
"kwargs",
")",
":",
"if",
"convert",
"is",
"not",
"None",
":",
"msg",
"=",
"(",
"\"The 'convert' parameter is ... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.xs | Return cross-section from the Series/DataFrame.
This method takes a `key` argument to select data at a particular
level of a MultiIndex.
Parameters
----------
key : label or tuple of label
Label contained in the index, or partially in a MultiIndex.
axis : {0... | pandas/core/generic.py | def xs(self, key, axis=0, level=None, drop_level=True):
"""
Return cross-section from the Series/DataFrame.
This method takes a `key` argument to select data at a particular
level of a MultiIndex.
Parameters
----------
key : label or tuple of label
L... | def xs(self, key, axis=0, level=None, drop_level=True):
"""
Return cross-section from the Series/DataFrame.
This method takes a `key` argument to select data at a particular
level of a MultiIndex.
Parameters
----------
key : label or tuple of label
L... | [
"Return",
"cross",
"-",
"section",
"from",
"the",
"Series",
"/",
"DataFrame",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L3491-L3649 | [
"def",
"xs",
"(",
"self",
",",
"key",
",",
"axis",
"=",
"0",
",",
"level",
"=",
"None",
",",
"drop_level",
"=",
"True",
")",
":",
"axis",
"=",
"self",
".",
"_get_axis_number",
"(",
"axis",
")",
"labels",
"=",
"self",
".",
"_get_axis",
"(",
"axis",
... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.select | Return data corresponding to axis labels matching criteria.
.. deprecated:: 0.21.0
Use df.loc[df.index.map(crit)] to select via labels
Parameters
----------
crit : function
To be called on each index (label). Should return True or False
axis : int
... | pandas/core/generic.py | def select(self, crit, axis=0):
"""
Return data corresponding to axis labels matching criteria.
.. deprecated:: 0.21.0
Use df.loc[df.index.map(crit)] to select via labels
Parameters
----------
crit : function
To be called on each index (label). S... | def select(self, crit, axis=0):
"""
Return data corresponding to axis labels matching criteria.
.. deprecated:: 0.21.0
Use df.loc[df.index.map(crit)] to select via labels
Parameters
----------
crit : function
To be called on each index (label). S... | [
"Return",
"data",
"corresponding",
"to",
"axis",
"labels",
"matching",
"criteria",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L3653-L3685 | [
"def",
"select",
"(",
"self",
",",
"crit",
",",
"axis",
"=",
"0",
")",
":",
"warnings",
".",
"warn",
"(",
"\"'select' is deprecated and will be removed in a \"",
"\"future release. You can use \"",
"\".loc[labels.map(crit)] as a replacement\"",
",",
"FutureWarning",
",",
... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.reindex_like | Return an object with matching indices as other object.
Conform the object to the same index on all axes. Optional
filling logic, placing NaN in locations having no value
in the previous index. A new object is produced unless the
new index is equivalent to the current one and copy=False... | pandas/core/generic.py | def reindex_like(self, other, method=None, copy=True, limit=None,
tolerance=None):
"""
Return an object with matching indices as other object.
Conform the object to the same index on all axes. Optional
filling logic, placing NaN in locations having no value
... | def reindex_like(self, other, method=None, copy=True, limit=None,
tolerance=None):
"""
Return an object with matching indices as other object.
Conform the object to the same index on all axes. Optional
filling logic, placing NaN in locations having no value
... | [
"Return",
"an",
"object",
"with",
"matching",
"indices",
"as",
"other",
"object",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L3687-L3787 | [
"def",
"reindex_like",
"(",
"self",
",",
"other",
",",
"method",
"=",
"None",
",",
"copy",
"=",
"True",
",",
"limit",
"=",
"None",
",",
"tolerance",
"=",
"None",
")",
":",
"d",
"=",
"other",
".",
"_construct_axes_dict",
"(",
"axes",
"=",
"self",
".",... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame._drop_axis | Drop labels from specified axis. Used in the ``drop`` method
internally.
Parameters
----------
labels : single label or list-like
axis : int or axis name
level : int or level name, default None
For MultiIndex
errors : {'ignore', 'raise'}, default 'rai... | pandas/core/generic.py | def _drop_axis(self, labels, axis, level=None, errors='raise'):
"""
Drop labels from specified axis. Used in the ``drop`` method
internally.
Parameters
----------
labels : single label or list-like
axis : int or axis name
level : int or level name, defaul... | def _drop_axis(self, labels, axis, level=None, errors='raise'):
"""
Drop labels from specified axis. Used in the ``drop`` method
internally.
Parameters
----------
labels : single label or list-like
axis : int or axis name
level : int or level name, defaul... | [
"Drop",
"labels",
"from",
"specified",
"axis",
".",
"Used",
"in",
"the",
"drop",
"method",
"internally",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L3817-L3868 | [
"def",
"_drop_axis",
"(",
"self",
",",
"labels",
",",
"axis",
",",
"level",
"=",
"None",
",",
"errors",
"=",
"'raise'",
")",
":",
"axis",
"=",
"self",
".",
"_get_axis_number",
"(",
"axis",
")",
"axis_name",
"=",
"self",
".",
"_get_axis_name",
"(",
"axi... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame._update_inplace | Replace self internals with result.
Parameters
----------
verify_is_copy : boolean, default True
provide is_copy checks | pandas/core/generic.py | def _update_inplace(self, result, verify_is_copy=True):
"""
Replace self internals with result.
Parameters
----------
verify_is_copy : boolean, default True
provide is_copy checks
"""
# NOTE: This does *not* call __finalize__ and that's an explicit
... | def _update_inplace(self, result, verify_is_copy=True):
"""
Replace self internals with result.
Parameters
----------
verify_is_copy : boolean, default True
provide is_copy checks
"""
# NOTE: This does *not* call __finalize__ and that's an explicit
... | [
"Replace",
"self",
"internals",
"with",
"result",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L3870-L3886 | [
"def",
"_update_inplace",
"(",
"self",
",",
"result",
",",
"verify_is_copy",
"=",
"True",
")",
":",
"# NOTE: This does *not* call __finalize__ and that's an explicit",
"# decision that we may revisit in the future.",
"self",
".",
"_reset_cache",
"(",
")",
"self",
".",
"_cle... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.add_prefix | Prefix labels with string `prefix`.
For Series, the row labels are prefixed.
For DataFrame, the column labels are prefixed.
Parameters
----------
prefix : str
The string to add before each label.
Returns
-------
Series or DataFrame
... | pandas/core/generic.py | def add_prefix(self, prefix):
"""
Prefix labels with string `prefix`.
For Series, the row labels are prefixed.
For DataFrame, the column labels are prefixed.
Parameters
----------
prefix : str
The string to add before each label.
Returns
... | def add_prefix(self, prefix):
"""
Prefix labels with string `prefix`.
For Series, the row labels are prefixed.
For DataFrame, the column labels are prefixed.
Parameters
----------
prefix : str
The string to add before each label.
Returns
... | [
"Prefix",
"labels",
"with",
"string",
"prefix",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L3888-L3945 | [
"def",
"add_prefix",
"(",
"self",
",",
"prefix",
")",
":",
"f",
"=",
"functools",
".",
"partial",
"(",
"'{prefix}{}'",
".",
"format",
",",
"prefix",
"=",
"prefix",
")",
"mapper",
"=",
"{",
"self",
".",
"_info_axis_name",
":",
"f",
"}",
"return",
"self"... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.add_suffix | Suffix labels with string `suffix`.
For Series, the row labels are suffixed.
For DataFrame, the column labels are suffixed.
Parameters
----------
suffix : str
The string to add after each label.
Returns
-------
Series or DataFrame
... | pandas/core/generic.py | def add_suffix(self, suffix):
"""
Suffix labels with string `suffix`.
For Series, the row labels are suffixed.
For DataFrame, the column labels are suffixed.
Parameters
----------
suffix : str
The string to add after each label.
Returns
... | def add_suffix(self, suffix):
"""
Suffix labels with string `suffix`.
For Series, the row labels are suffixed.
For DataFrame, the column labels are suffixed.
Parameters
----------
suffix : str
The string to add after each label.
Returns
... | [
"Suffix",
"labels",
"with",
"string",
"suffix",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L3947-L4004 | [
"def",
"add_suffix",
"(",
"self",
",",
"suffix",
")",
":",
"f",
"=",
"functools",
".",
"partial",
"(",
"'{}{suffix}'",
".",
"format",
",",
"suffix",
"=",
"suffix",
")",
"mapper",
"=",
"{",
"self",
".",
"_info_axis_name",
":",
"f",
"}",
"return",
"self"... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.sort_values | Sort by the values along either axis.
Parameters
----------%(optional_by)s
axis : %(axes_single_arg)s, default 0
Axis to be sorted.
ascending : bool or list of bool, default True
Sort ascending vs. descending. Specify list for multiple sort
orders.... | pandas/core/generic.py | def sort_values(self, by=None, axis=0, ascending=True, inplace=False,
kind='quicksort', na_position='last'):
"""
Sort by the values along either axis.
Parameters
----------%(optional_by)s
axis : %(axes_single_arg)s, default 0
Axis to be sorted.
... | def sort_values(self, by=None, axis=0, ascending=True, inplace=False,
kind='quicksort', na_position='last'):
"""
Sort by the values along either axis.
Parameters
----------%(optional_by)s
axis : %(axes_single_arg)s, default 0
Axis to be sorted.
... | [
"Sort",
"by",
"the",
"values",
"along",
"either",
"axis",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L4006-L4096 | [
"def",
"sort_values",
"(",
"self",
",",
"by",
"=",
"None",
",",
"axis",
"=",
"0",
",",
"ascending",
"=",
"True",
",",
"inplace",
"=",
"False",
",",
"kind",
"=",
"'quicksort'",
",",
"na_position",
"=",
"'last'",
")",
":",
"raise",
"NotImplementedError",
... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.sort_index | Sort object by labels (along an axis).
Parameters
----------
axis : {0 or 'index', 1 or 'columns'}, default 0
The axis along which to sort. The value 0 identifies the rows,
and 1 identifies the columns.
level : int or level name or list of ints or list of level ... | pandas/core/generic.py | def sort_index(self, axis=0, level=None, ascending=True, inplace=False,
kind='quicksort', na_position='last', sort_remaining=True):
"""
Sort object by labels (along an axis).
Parameters
----------
axis : {0 or 'index', 1 or 'columns'}, default 0
Th... | def sort_index(self, axis=0, level=None, ascending=True, inplace=False,
kind='quicksort', na_position='last', sort_remaining=True):
"""
Sort object by labels (along an axis).
Parameters
----------
axis : {0 or 'index', 1 or 'columns'}, default 0
Th... | [
"Sort",
"object",
"by",
"labels",
"(",
"along",
"an",
"axis",
")",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L4098-L4146 | [
"def",
"sort_index",
"(",
"self",
",",
"axis",
"=",
"0",
",",
"level",
"=",
"None",
",",
"ascending",
"=",
"True",
",",
"inplace",
"=",
"False",
",",
"kind",
"=",
"'quicksort'",
",",
"na_position",
"=",
"'last'",
",",
"sort_remaining",
"=",
"True",
")"... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.reindex | Conform %(klass)s to new index with optional filling logic, placing
NA/NaN in locations having no value in the previous index. A new object
is produced unless the new index is equivalent to the current one and
``copy=False``.
Parameters
----------
%(optional_labels)s
... | pandas/core/generic.py | def reindex(self, *args, **kwargs):
"""
Conform %(klass)s to new index with optional filling logic, placing
NA/NaN in locations having no value in the previous index. A new object
is produced unless the new index is equivalent to the current one and
``copy=False``.
Param... | def reindex(self, *args, **kwargs):
"""
Conform %(klass)s to new index with optional filling logic, placing
NA/NaN in locations having no value in the previous index. A new object
is produced unless the new index is equivalent to the current one and
``copy=False``.
Param... | [
"Conform",
"%",
"(",
"klass",
")",
"s",
"to",
"new",
"index",
"with",
"optional",
"filling",
"logic",
"placing",
"NA",
"/",
"NaN",
"in",
"locations",
"having",
"no",
"value",
"in",
"the",
"previous",
"index",
".",
"A",
"new",
"object",
"is",
"produced",
... | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L4148-L4391 | [
"def",
"reindex",
"(",
"self",
",",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"# TODO: Decide if we care about having different examples for different",
"# kinds",
"# construct the args",
"axes",
",",
"kwargs",
"=",
"self",
".",
"_construct_axes_from_arguments",
"... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame._reindex_axes | Perform the reindex for all the axes. | pandas/core/generic.py | def _reindex_axes(self, axes, level, limit, tolerance, method, fill_value,
copy):
"""Perform the reindex for all the axes."""
obj = self
for a in self._AXIS_ORDERS:
labels = axes[a]
if labels is None:
continue
ax = self._... | def _reindex_axes(self, axes, level, limit, tolerance, method, fill_value,
copy):
"""Perform the reindex for all the axes."""
obj = self
for a in self._AXIS_ORDERS:
labels = axes[a]
if labels is None:
continue
ax = self._... | [
"Perform",
"the",
"reindex",
"for",
"all",
"the",
"axes",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L4393-L4411 | [
"def",
"_reindex_axes",
"(",
"self",
",",
"axes",
",",
"level",
",",
"limit",
",",
"tolerance",
",",
"method",
",",
"fill_value",
",",
"copy",
")",
":",
"obj",
"=",
"self",
"for",
"a",
"in",
"self",
".",
"_AXIS_ORDERS",
":",
"labels",
"=",
"axes",
"[... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame._needs_reindex_multi | Check if we do need a multi reindex. | pandas/core/generic.py | def _needs_reindex_multi(self, axes, method, level):
"""Check if we do need a multi reindex."""
return ((com.count_not_none(*axes.values()) == self._AXIS_LEN) and
method is None and level is None and not self._is_mixed_type) | def _needs_reindex_multi(self, axes, method, level):
"""Check if we do need a multi reindex."""
return ((com.count_not_none(*axes.values()) == self._AXIS_LEN) and
method is None and level is None and not self._is_mixed_type) | [
"Check",
"if",
"we",
"do",
"need",
"a",
"multi",
"reindex",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L4413-L4416 | [
"def",
"_needs_reindex_multi",
"(",
"self",
",",
"axes",
",",
"method",
",",
"level",
")",
":",
"return",
"(",
"(",
"com",
".",
"count_not_none",
"(",
"*",
"axes",
".",
"values",
"(",
")",
")",
"==",
"self",
".",
"_AXIS_LEN",
")",
"and",
"method",
"i... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame._reindex_with_indexers | allow_dups indicates an internal call here | pandas/core/generic.py | def _reindex_with_indexers(self, reindexers, fill_value=None, copy=False,
allow_dups=False):
"""allow_dups indicates an internal call here """
# reindex doing multiple operations on different axes if indicated
new_data = self._data
for axis in sorted(reind... | def _reindex_with_indexers(self, reindexers, fill_value=None, copy=False,
allow_dups=False):
"""allow_dups indicates an internal call here """
# reindex doing multiple operations on different axes if indicated
new_data = self._data
for axis in sorted(reind... | [
"allow_dups",
"indicates",
"an",
"internal",
"call",
"here"
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L4504-L4530 | [
"def",
"_reindex_with_indexers",
"(",
"self",
",",
"reindexers",
",",
"fill_value",
"=",
"None",
",",
"copy",
"=",
"False",
",",
"allow_dups",
"=",
"False",
")",
":",
"# reindex doing multiple operations on different axes if indicated",
"new_data",
"=",
"self",
".",
... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.filter | Subset rows or columns of dataframe according to labels in
the specified index.
Note that this routine does not filter a dataframe on its
contents. The filter is applied to the labels of the index.
Parameters
----------
items : list-like
Keep labels from axi... | pandas/core/generic.py | def filter(self, items=None, like=None, regex=None, axis=None):
"""
Subset rows or columns of dataframe according to labels in
the specified index.
Note that this routine does not filter a dataframe on its
contents. The filter is applied to the labels of the index.
Para... | def filter(self, items=None, like=None, regex=None, axis=None):
"""
Subset rows or columns of dataframe according to labels in
the specified index.
Note that this routine does not filter a dataframe on its
contents. The filter is applied to the labels of the index.
Para... | [
"Subset",
"rows",
"or",
"columns",
"of",
"dataframe",
"according",
"to",
"labels",
"in",
"the",
"specified",
"index",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L4532-L4618 | [
"def",
"filter",
"(",
"self",
",",
"items",
"=",
"None",
",",
"like",
"=",
"None",
",",
"regex",
"=",
"None",
",",
"axis",
"=",
"None",
")",
":",
"import",
"re",
"nkw",
"=",
"com",
".",
"count_not_none",
"(",
"items",
",",
"like",
",",
"regex",
"... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.sample | Return a random sample of items from an axis of object.
You can use `random_state` for reproducibility.
Parameters
----------
n : int, optional
Number of items from axis to return. Cannot be used with `frac`.
Default = 1 if `frac` = None.
frac : float, o... | pandas/core/generic.py | def sample(self, n=None, frac=None, replace=False, weights=None,
random_state=None, axis=None):
"""
Return a random sample of items from an axis of object.
You can use `random_state` for reproducibility.
Parameters
----------
n : int, optional
... | def sample(self, n=None, frac=None, replace=False, weights=None,
random_state=None, axis=None):
"""
Return a random sample of items from an axis of object.
You can use `random_state` for reproducibility.
Parameters
----------
n : int, optional
... | [
"Return",
"a",
"random",
"sample",
"of",
"items",
"from",
"an",
"axis",
"of",
"object",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L4740-L4901 | [
"def",
"sample",
"(",
"self",
",",
"n",
"=",
"None",
",",
"frac",
"=",
"None",
",",
"replace",
"=",
"False",
",",
"weights",
"=",
"None",
",",
"random_state",
"=",
"None",
",",
"axis",
"=",
"None",
")",
":",
"if",
"axis",
"is",
"None",
":",
"axis... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame._dir_additions | add the string-like attributes from the info_axis.
If info_axis is a MultiIndex, it's first level values are used. | pandas/core/generic.py | def _dir_additions(self):
""" add the string-like attributes from the info_axis.
If info_axis is a MultiIndex, it's first level values are used.
"""
additions = {c for c in self._info_axis.unique(level=0)[:100]
if isinstance(c, str) and c.isidentifier()}
retu... | def _dir_additions(self):
""" add the string-like attributes from the info_axis.
If info_axis is a MultiIndex, it's first level values are used.
"""
additions = {c for c in self._info_axis.unique(level=0)[:100]
if isinstance(c, str) and c.isidentifier()}
retu... | [
"add",
"the",
"string",
"-",
"like",
"attributes",
"from",
"the",
"info_axis",
".",
"If",
"info_axis",
"is",
"a",
"MultiIndex",
"it",
"s",
"first",
"level",
"values",
"are",
"used",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L5141-L5147 | [
"def",
"_dir_additions",
"(",
"self",
")",
":",
"additions",
"=",
"{",
"c",
"for",
"c",
"in",
"self",
".",
"_info_axis",
".",
"unique",
"(",
"level",
"=",
"0",
")",
"[",
":",
"100",
"]",
"if",
"isinstance",
"(",
"c",
",",
"str",
")",
"and",
"c",
... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame._protect_consolidate | Consolidate _data -- if the blocks have changed, then clear the
cache | pandas/core/generic.py | def _protect_consolidate(self, f):
"""Consolidate _data -- if the blocks have changed, then clear the
cache
"""
blocks_before = len(self._data.blocks)
result = f()
if len(self._data.blocks) != blocks_before:
self._clear_item_cache()
return result | def _protect_consolidate(self, f):
"""Consolidate _data -- if the blocks have changed, then clear the
cache
"""
blocks_before = len(self._data.blocks)
result = f()
if len(self._data.blocks) != blocks_before:
self._clear_item_cache()
return result | [
"Consolidate",
"_data",
"--",
"if",
"the",
"blocks",
"have",
"changed",
"then",
"clear",
"the",
"cache"
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L5155-L5163 | [
"def",
"_protect_consolidate",
"(",
"self",
",",
"f",
")",
":",
"blocks_before",
"=",
"len",
"(",
"self",
".",
"_data",
".",
"blocks",
")",
"result",
"=",
"f",
"(",
")",
"if",
"len",
"(",
"self",
".",
"_data",
".",
"blocks",
")",
"!=",
"blocks_before... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame._consolidate_inplace | Consolidate data in place and return None | pandas/core/generic.py | def _consolidate_inplace(self):
"""Consolidate data in place and return None"""
def f():
self._data = self._data.consolidate()
self._protect_consolidate(f) | def _consolidate_inplace(self):
"""Consolidate data in place and return None"""
def f():
self._data = self._data.consolidate()
self._protect_consolidate(f) | [
"Consolidate",
"data",
"in",
"place",
"and",
"return",
"None"
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L5165-L5171 | [
"def",
"_consolidate_inplace",
"(",
"self",
")",
":",
"def",
"f",
"(",
")",
":",
"self",
".",
"_data",
"=",
"self",
".",
"_data",
".",
"consolidate",
"(",
")",
"self",
".",
"_protect_consolidate",
"(",
"f",
")"
] | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame._consolidate | Compute NDFrame with "consolidated" internals (data of each dtype
grouped together in a single ndarray).
Parameters
----------
inplace : boolean, default False
If False return new object, otherwise modify existing object
Returns
-------
consolidated ... | pandas/core/generic.py | def _consolidate(self, inplace=False):
"""
Compute NDFrame with "consolidated" internals (data of each dtype
grouped together in a single ndarray).
Parameters
----------
inplace : boolean, default False
If False return new object, otherwise modify existing ob... | def _consolidate(self, inplace=False):
"""
Compute NDFrame with "consolidated" internals (data of each dtype
grouped together in a single ndarray).
Parameters
----------
inplace : boolean, default False
If False return new object, otherwise modify existing ob... | [
"Compute",
"NDFrame",
"with",
"consolidated",
"internals",
"(",
"data",
"of",
"each",
"dtype",
"grouped",
"together",
"in",
"a",
"single",
"ndarray",
")",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L5173-L5193 | [
"def",
"_consolidate",
"(",
"self",
",",
"inplace",
"=",
"False",
")",
":",
"inplace",
"=",
"validate_bool_kwarg",
"(",
"inplace",
",",
"'inplace'",
")",
"if",
"inplace",
":",
"self",
".",
"_consolidate_inplace",
"(",
")",
"else",
":",
"f",
"=",
"lambda",
... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame._check_inplace_setting | check whether we allow in-place setting with this type of value | pandas/core/generic.py | def _check_inplace_setting(self, value):
""" check whether we allow in-place setting with this type of value """
if self._is_mixed_type:
if not self._is_numeric_mixed_type:
# allow an actual np.nan thru
try:
if np.isnan(value):
... | def _check_inplace_setting(self, value):
""" check whether we allow in-place setting with this type of value """
if self._is_mixed_type:
if not self._is_numeric_mixed_type:
# allow an actual np.nan thru
try:
if np.isnan(value):
... | [
"check",
"whether",
"we",
"allow",
"in",
"-",
"place",
"setting",
"with",
"this",
"type",
"of",
"value"
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L5210-L5226 | [
"def",
"_check_inplace_setting",
"(",
"self",
",",
"value",
")",
":",
"if",
"self",
".",
"_is_mixed_type",
":",
"if",
"not",
"self",
".",
"_is_numeric_mixed_type",
":",
"# allow an actual np.nan thru",
"try",
":",
"if",
"np",
".",
"isnan",
"(",
"value",
")",
... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.as_matrix | Convert the frame to its Numpy-array representation.
.. deprecated:: 0.23.0
Use :meth:`DataFrame.values` instead.
Parameters
----------
columns : list, optional, default:None
If None, return all columns, otherwise, returns specified columns.
Returns
... | pandas/core/generic.py | def as_matrix(self, columns=None):
"""
Convert the frame to its Numpy-array representation.
.. deprecated:: 0.23.0
Use :meth:`DataFrame.values` instead.
Parameters
----------
columns : list, optional, default:None
If None, return all columns, oth... | def as_matrix(self, columns=None):
"""
Convert the frame to its Numpy-array representation.
.. deprecated:: 0.23.0
Use :meth:`DataFrame.values` instead.
Parameters
----------
columns : list, optional, default:None
If None, return all columns, oth... | [
"Convert",
"the",
"frame",
"to",
"its",
"Numpy",
"-",
"array",
"representation",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L5238-L5281 | [
"def",
"as_matrix",
"(",
"self",
",",
"columns",
"=",
"None",
")",
":",
"warnings",
".",
"warn",
"(",
"\"Method .as_matrix will be removed in a future version. \"",
"\"Use .values instead.\"",
",",
"FutureWarning",
",",
"stacklevel",
"=",
"2",
")",
"self",
".",
"_co... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.values | Return a Numpy representation of the DataFrame.
.. warning::
We recommend using :meth:`DataFrame.to_numpy` instead.
Only the values in the DataFrame will be returned, the axes labels
will be removed.
Returns
-------
numpy.ndarray
The values of t... | pandas/core/generic.py | def values(self):
"""
Return a Numpy representation of the DataFrame.
.. warning::
We recommend using :meth:`DataFrame.to_numpy` instead.
Only the values in the DataFrame will be returned, the axes labels
will be removed.
Returns
-------
num... | def values(self):
"""
Return a Numpy representation of the DataFrame.
.. warning::
We recommend using :meth:`DataFrame.to_numpy` instead.
Only the values in the DataFrame will be returned, the axes labels
will be removed.
Returns
-------
num... | [
"Return",
"a",
"Numpy",
"representation",
"of",
"the",
"DataFrame",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L5284-L5358 | [
"def",
"values",
"(",
"self",
")",
":",
"self",
".",
"_consolidate_inplace",
"(",
")",
"return",
"self",
".",
"_data",
".",
"as_array",
"(",
"transpose",
"=",
"self",
".",
"_AXIS_REVERSED",
")"
] | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.get_ftype_counts | Return counts of unique ftypes in this object.
.. deprecated:: 0.23.0
This is useful for SparseDataFrame or for DataFrames containing
sparse arrays.
Returns
-------
dtype : Series
Series with the count of columns with each type and
sparsity (den... | pandas/core/generic.py | def get_ftype_counts(self):
"""
Return counts of unique ftypes in this object.
.. deprecated:: 0.23.0
This is useful for SparseDataFrame or for DataFrames containing
sparse arrays.
Returns
-------
dtype : Series
Series with the count of colu... | def get_ftype_counts(self):
"""
Return counts of unique ftypes in this object.
.. deprecated:: 0.23.0
This is useful for SparseDataFrame or for DataFrames containing
sparse arrays.
Returns
-------
dtype : Series
Series with the count of colu... | [
"Return",
"counts",
"of",
"unique",
"ftypes",
"in",
"this",
"object",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L5447-L5488 | [
"def",
"get_ftype_counts",
"(",
"self",
")",
":",
"warnings",
".",
"warn",
"(",
"\"get_ftype_counts is deprecated and will \"",
"\"be removed in a future version\"",
",",
"FutureWarning",
",",
"stacklevel",
"=",
"2",
")",
"from",
"pandas",
"import",
"Series",
"return",
... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.dtypes | Return the dtypes in the DataFrame.
This returns a Series with the data type of each column.
The result's index is the original DataFrame's columns. Columns
with mixed types are stored with the ``object`` dtype. See
:ref:`the User Guide <basics.dtypes>` for more.
Returns
... | pandas/core/generic.py | def dtypes(self):
"""
Return the dtypes in the DataFrame.
This returns a Series with the data type of each column.
The result's index is the original DataFrame's columns. Columns
with mixed types are stored with the ``object`` dtype. See
:ref:`the User Guide <basics.dtyp... | def dtypes(self):
"""
Return the dtypes in the DataFrame.
This returns a Series with the data type of each column.
The result's index is the original DataFrame's columns. Columns
with mixed types are stored with the ``object`` dtype. See
:ref:`the User Guide <basics.dtyp... | [
"Return",
"the",
"dtypes",
"in",
"the",
"DataFrame",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L5491-L5524 | [
"def",
"dtypes",
"(",
"self",
")",
":",
"from",
"pandas",
"import",
"Series",
"return",
"Series",
"(",
"self",
".",
"_data",
".",
"get_dtypes",
"(",
")",
",",
"index",
"=",
"self",
".",
"_info_axis",
",",
"dtype",
"=",
"np",
".",
"object_",
")"
] | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.ftypes | Return the ftypes (indication of sparse/dense and dtype) in DataFrame.
This returns a Series with the data type of each column.
The result's index is the original DataFrame's columns. Columns
with mixed types are stored with the ``object`` dtype. See
:ref:`the User Guide <basics.dtypes... | pandas/core/generic.py | def ftypes(self):
"""
Return the ftypes (indication of sparse/dense and dtype) in DataFrame.
This returns a Series with the data type of each column.
The result's index is the original DataFrame's columns. Columns
with mixed types are stored with the ``object`` dtype. See
... | def ftypes(self):
"""
Return the ftypes (indication of sparse/dense and dtype) in DataFrame.
This returns a Series with the data type of each column.
The result's index is the original DataFrame's columns. Columns
with mixed types are stored with the ``object`` dtype. See
... | [
"Return",
"the",
"ftypes",
"(",
"indication",
"of",
"sparse",
"/",
"dense",
"and",
"dtype",
")",
"in",
"DataFrame",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L5527-L5570 | [
"def",
"ftypes",
"(",
"self",
")",
":",
"from",
"pandas",
"import",
"Series",
"return",
"Series",
"(",
"self",
".",
"_data",
".",
"get_ftypes",
"(",
")",
",",
"index",
"=",
"self",
".",
"_info_axis",
",",
"dtype",
"=",
"np",
".",
"object_",
")"
] | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.as_blocks | Convert the frame to a dict of dtype -> Constructor Types that each has
a homogeneous dtype.
.. deprecated:: 0.21.0
NOTE: the dtypes of the blocks WILL BE PRESERVED HERE (unlike in
as_matrix)
Parameters
----------
copy : boolean, default True
Ret... | pandas/core/generic.py | def as_blocks(self, copy=True):
"""
Convert the frame to a dict of dtype -> Constructor Types that each has
a homogeneous dtype.
.. deprecated:: 0.21.0
NOTE: the dtypes of the blocks WILL BE PRESERVED HERE (unlike in
as_matrix)
Parameters
--------... | def as_blocks(self, copy=True):
"""
Convert the frame to a dict of dtype -> Constructor Types that each has
a homogeneous dtype.
.. deprecated:: 0.21.0
NOTE: the dtypes of the blocks WILL BE PRESERVED HERE (unlike in
as_matrix)
Parameters
--------... | [
"Convert",
"the",
"frame",
"to",
"a",
"dict",
"of",
"dtype",
"-",
">",
"Constructor",
"Types",
"that",
"each",
"has",
"a",
"homogeneous",
"dtype",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L5572-L5593 | [
"def",
"as_blocks",
"(",
"self",
",",
"copy",
"=",
"True",
")",
":",
"warnings",
".",
"warn",
"(",
"\"as_blocks is deprecated and will \"",
"\"be removed in a future version\"",
",",
"FutureWarning",
",",
"stacklevel",
"=",
"2",
")",
"return",
"self",
".",
"_to_di... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame._to_dict_of_blocks | Return a dict of dtype -> Constructor Types that
each is a homogeneous dtype.
Internal ONLY | pandas/core/generic.py | def _to_dict_of_blocks(self, copy=True):
"""
Return a dict of dtype -> Constructor Types that
each is a homogeneous dtype.
Internal ONLY
"""
return {k: self._constructor(v).__finalize__(self)
for k, v, in self._data.to_dict(copy=copy).items()} | def _to_dict_of_blocks(self, copy=True):
"""
Return a dict of dtype -> Constructor Types that
each is a homogeneous dtype.
Internal ONLY
"""
return {k: self._constructor(v).__finalize__(self)
for k, v, in self._data.to_dict(copy=copy).items()} | [
"Return",
"a",
"dict",
"of",
"dtype",
"-",
">",
"Constructor",
"Types",
"that",
"each",
"is",
"a",
"homogeneous",
"dtype",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L5604-L5612 | [
"def",
"_to_dict_of_blocks",
"(",
"self",
",",
"copy",
"=",
"True",
")",
":",
"return",
"{",
"k",
":",
"self",
".",
"_constructor",
"(",
"v",
")",
".",
"__finalize__",
"(",
"self",
")",
"for",
"k",
",",
"v",
",",
"in",
"self",
".",
"_data",
".",
... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.astype | Cast a pandas object to a specified dtype ``dtype``.
Parameters
----------
dtype : data type, or dict of column name -> data type
Use a numpy.dtype or Python type to cast entire pandas object to
the same type. Alternatively, use {col: dtype, ...}, where col is a
... | pandas/core/generic.py | def astype(self, dtype, copy=True, errors='raise', **kwargs):
"""
Cast a pandas object to a specified dtype ``dtype``.
Parameters
----------
dtype : data type, or dict of column name -> data type
Use a numpy.dtype or Python type to cast entire pandas object to
... | def astype(self, dtype, copy=True, errors='raise', **kwargs):
"""
Cast a pandas object to a specified dtype ``dtype``.
Parameters
----------
dtype : data type, or dict of column name -> data type
Use a numpy.dtype or Python type to cast entire pandas object to
... | [
"Cast",
"a",
"pandas",
"object",
"to",
"a",
"specified",
"dtype",
"dtype",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L5614-L5731 | [
"def",
"astype",
"(",
"self",
",",
"dtype",
",",
"copy",
"=",
"True",
",",
"errors",
"=",
"'raise'",
",",
"*",
"*",
"kwargs",
")",
":",
"if",
"is_dict_like",
"(",
"dtype",
")",
":",
"if",
"self",
".",
"ndim",
"==",
"1",
":",
"# i.e. Series",
"if",
... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.copy | Make a copy of this object's indices and data.
When ``deep=True`` (default), a new object will be created with a
copy of the calling object's data and indices. Modifications to
the data or indices of the copy will not be reflected in the
original object (see notes below).
When ... | pandas/core/generic.py | def copy(self, deep=True):
"""
Make a copy of this object's indices and data.
When ``deep=True`` (default), a new object will be created with a
copy of the calling object's data and indices. Modifications to
the data or indices of the copy will not be reflected in the
or... | def copy(self, deep=True):
"""
Make a copy of this object's indices and data.
When ``deep=True`` (default), a new object will be created with a
copy of the calling object's data and indices. Modifications to
the data or indices of the copy will not be reflected in the
or... | [
"Make",
"a",
"copy",
"of",
"this",
"object",
"s",
"indices",
"and",
"data",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L5733-L5839 | [
"def",
"copy",
"(",
"self",
",",
"deep",
"=",
"True",
")",
":",
"data",
"=",
"self",
".",
"_data",
".",
"copy",
"(",
"deep",
"=",
"deep",
")",
"return",
"self",
".",
"_constructor",
"(",
"data",
")",
".",
"__finalize__",
"(",
"self",
")"
] | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame._convert | Attempt to infer better dtype for object columns
Parameters
----------
datetime : boolean, default False
If True, convert to date where possible.
numeric : boolean, default False
If True, attempt to convert to numbers (including strings), with
unconve... | pandas/core/generic.py | def _convert(self, datetime=False, numeric=False, timedelta=False,
coerce=False, copy=True):
"""
Attempt to infer better dtype for object columns
Parameters
----------
datetime : boolean, default False
If True, convert to date where possible.
... | def _convert(self, datetime=False, numeric=False, timedelta=False,
coerce=False, copy=True):
"""
Attempt to infer better dtype for object columns
Parameters
----------
datetime : boolean, default False
If True, convert to date where possible.
... | [
"Attempt",
"to",
"infer",
"better",
"dtype",
"for",
"object",
"columns"
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L5855-L5884 | [
"def",
"_convert",
"(",
"self",
",",
"datetime",
"=",
"False",
",",
"numeric",
"=",
"False",
",",
"timedelta",
"=",
"False",
",",
"coerce",
"=",
"False",
",",
"copy",
"=",
"True",
")",
":",
"return",
"self",
".",
"_constructor",
"(",
"self",
".",
"_d... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.convert_objects | Attempt to infer better dtype for object columns.
.. deprecated:: 0.21.0
Parameters
----------
convert_dates : boolean, default True
If True, convert to date where possible. If 'coerce', force
conversion, with unconvertible values becoming NaT.
convert_n... | pandas/core/generic.py | def convert_objects(self, convert_dates=True, convert_numeric=False,
convert_timedeltas=True, copy=True):
"""
Attempt to infer better dtype for object columns.
.. deprecated:: 0.21.0
Parameters
----------
convert_dates : boolean, default True
... | def convert_objects(self, convert_dates=True, convert_numeric=False,
convert_timedeltas=True, copy=True):
"""
Attempt to infer better dtype for object columns.
.. deprecated:: 0.21.0
Parameters
----------
convert_dates : boolean, default True
... | [
"Attempt",
"to",
"infer",
"better",
"dtype",
"for",
"object",
"columns",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L5886-L5930 | [
"def",
"convert_objects",
"(",
"self",
",",
"convert_dates",
"=",
"True",
",",
"convert_numeric",
"=",
"False",
",",
"convert_timedeltas",
"=",
"True",
",",
"copy",
"=",
"True",
")",
":",
"msg",
"=",
"(",
"\"convert_objects is deprecated. To re-infer data dtypes fo... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.infer_objects | Attempt to infer better dtypes for object columns.
Attempts soft conversion of object-dtyped
columns, leaving non-object and unconvertible
columns unchanged. The inference rules are the
same as during normal Series/DataFrame construction.
.. versionadded:: 0.21.0
Retur... | pandas/core/generic.py | def infer_objects(self):
"""
Attempt to infer better dtypes for object columns.
Attempts soft conversion of object-dtyped
columns, leaving non-object and unconvertible
columns unchanged. The inference rules are the
same as during normal Series/DataFrame construction.
... | def infer_objects(self):
"""
Attempt to infer better dtypes for object columns.
Attempts soft conversion of object-dtyped
columns, leaving non-object and unconvertible
columns unchanged. The inference rules are the
same as during normal Series/DataFrame construction.
... | [
"Attempt",
"to",
"infer",
"better",
"dtypes",
"for",
"object",
"columns",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L5932-L5977 | [
"def",
"infer_objects",
"(",
"self",
")",
":",
"# numeric=False necessary to only soft convert;",
"# python objects will still be converted to",
"# native numpy numeric types",
"return",
"self",
".",
"_constructor",
"(",
"self",
".",
"_data",
".",
"convert",
"(",
"datetime",
... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.fillna | Fill NA/NaN values using the specified method.
Parameters
----------
value : scalar, dict, Series, or DataFrame
Value to use to fill holes (e.g. 0), alternately a
dict/Series/DataFrame of values specifying which value to use for
each index (for a Series) or c... | pandas/core/generic.py | def fillna(self, value=None, method=None, axis=None, inplace=False,
limit=None, downcast=None):
"""
Fill NA/NaN values using the specified method.
Parameters
----------
value : scalar, dict, Series, or DataFrame
Value to use to fill holes (e.g. 0), alt... | def fillna(self, value=None, method=None, axis=None, inplace=False,
limit=None, downcast=None):
"""
Fill NA/NaN values using the specified method.
Parameters
----------
value : scalar, dict, Series, or DataFrame
Value to use to fill holes (e.g. 0), alt... | [
"Fill",
"NA",
"/",
"NaN",
"values",
"using",
"the",
"specified",
"method",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L5982-L6169 | [
"def",
"fillna",
"(",
"self",
",",
"value",
"=",
"None",
",",
"method",
"=",
"None",
",",
"axis",
"=",
"None",
",",
"inplace",
"=",
"False",
",",
"limit",
"=",
"None",
",",
"downcast",
"=",
"None",
")",
":",
"inplace",
"=",
"validate_bool_kwarg",
"("... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.interpolate | Interpolate values according to different methods. | pandas/core/generic.py | def interpolate(self, method='linear', axis=0, limit=None, inplace=False,
limit_direction='forward', limit_area=None,
downcast=None, **kwargs):
"""
Interpolate values according to different methods.
"""
inplace = validate_bool_kwarg(inplace, 'inpla... | def interpolate(self, method='linear', axis=0, limit=None, inplace=False,
limit_direction='forward', limit_area=None,
downcast=None, **kwargs):
"""
Interpolate values according to different methods.
"""
inplace = validate_bool_kwarg(inplace, 'inpla... | [
"Interpolate",
"values",
"according",
"to",
"different",
"methods",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L6817-L6894 | [
"def",
"interpolate",
"(",
"self",
",",
"method",
"=",
"'linear'",
",",
"axis",
"=",
"0",
",",
"limit",
"=",
"None",
",",
"inplace",
"=",
"False",
",",
"limit_direction",
"=",
"'forward'",
",",
"limit_area",
"=",
"None",
",",
"downcast",
"=",
"None",
"... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.asof | Return the last row(s) without any NaNs before `where`.
The last row (for each element in `where`, if list) without any
NaN is taken.
In case of a :class:`~pandas.DataFrame`, the last row without NaN
considering only the subset of columns (if not `None`)
.. versionadded:: 0.19.... | pandas/core/generic.py | def asof(self, where, subset=None):
"""
Return the last row(s) without any NaNs before `where`.
The last row (for each element in `where`, if list) without any
NaN is taken.
In case of a :class:`~pandas.DataFrame`, the last row without NaN
considering only the subset of ... | def asof(self, where, subset=None):
"""
Return the last row(s) without any NaNs before `where`.
The last row (for each element in `where`, if list) without any
NaN is taken.
In case of a :class:`~pandas.DataFrame`, the last row without NaN
considering only the subset of ... | [
"Return",
"the",
"last",
"row",
"(",
"s",
")",
"without",
"any",
"NaNs",
"before",
"where",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L6899-L7067 | [
"def",
"asof",
"(",
"self",
",",
"where",
",",
"subset",
"=",
"None",
")",
":",
"if",
"isinstance",
"(",
"where",
",",
"str",
")",
":",
"from",
"pandas",
"import",
"to_datetime",
"where",
"=",
"to_datetime",
"(",
"where",
")",
"if",
"not",
"self",
".... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.clip | Trim values at input threshold(s).
Assigns values outside boundary to boundary values. Thresholds
can be singular values or array like, and in the latter case
the clipping is performed element-wise in the specified axis.
Parameters
----------
lower : float or array_like... | pandas/core/generic.py | def clip(self, lower=None, upper=None, axis=None, inplace=False,
*args, **kwargs):
"""
Trim values at input threshold(s).
Assigns values outside boundary to boundary values. Thresholds
can be singular values or array like, and in the latter case
the clipping is perf... | def clip(self, lower=None, upper=None, axis=None, inplace=False,
*args, **kwargs):
"""
Trim values at input threshold(s).
Assigns values outside boundary to boundary values. Thresholds
can be singular values or array like, and in the latter case
the clipping is perf... | [
"Trim",
"values",
"at",
"input",
"threshold",
"(",
"s",
")",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L7256-L7369 | [
"def",
"clip",
"(",
"self",
",",
"lower",
"=",
"None",
",",
"upper",
"=",
"None",
",",
"axis",
"=",
"None",
",",
"inplace",
"=",
"False",
",",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"if",
"isinstance",
"(",
"self",
",",
"ABCPanel",
")",
... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.clip_upper | Trim values above a given threshold.
.. deprecated:: 0.24.0
Use clip(upper=threshold) instead.
Elements above the `threshold` will be changed to match the
`threshold` value(s). Threshold can be a single value or an array,
in the latter case it performs the truncation elemen... | pandas/core/generic.py | def clip_upper(self, threshold, axis=None, inplace=False):
"""
Trim values above a given threshold.
.. deprecated:: 0.24.0
Use clip(upper=threshold) instead.
Elements above the `threshold` will be changed to match the
`threshold` value(s). Threshold can be a single ... | def clip_upper(self, threshold, axis=None, inplace=False):
"""
Trim values above a given threshold.
.. deprecated:: 0.24.0
Use clip(upper=threshold) instead.
Elements above the `threshold` will be changed to match the
`threshold` value(s). Threshold can be a single ... | [
"Trim",
"values",
"above",
"a",
"given",
"threshold",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L7371-L7449 | [
"def",
"clip_upper",
"(",
"self",
",",
"threshold",
",",
"axis",
"=",
"None",
",",
"inplace",
"=",
"False",
")",
":",
"warnings",
".",
"warn",
"(",
"'clip_upper(threshold) is deprecated, '",
"'use clip(upper=threshold) instead'",
",",
"FutureWarning",
",",
"stacklev... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.clip_lower | Trim values below a given threshold.
.. deprecated:: 0.24.0
Use clip(lower=threshold) instead.
Elements below the `threshold` will be changed to match the
`threshold` value(s). Threshold can be a single value or an array,
in the latter case it performs the truncation elemen... | pandas/core/generic.py | def clip_lower(self, threshold, axis=None, inplace=False):
"""
Trim values below a given threshold.
.. deprecated:: 0.24.0
Use clip(lower=threshold) instead.
Elements below the `threshold` will be changed to match the
`threshold` value(s). Threshold can be a single ... | def clip_lower(self, threshold, axis=None, inplace=False):
"""
Trim values below a given threshold.
.. deprecated:: 0.24.0
Use clip(lower=threshold) instead.
Elements below the `threshold` will be changed to match the
`threshold` value(s). Threshold can be a single ... | [
"Trim",
"values",
"below",
"a",
"given",
"threshold",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L7451-L7565 | [
"def",
"clip_lower",
"(",
"self",
",",
"threshold",
",",
"axis",
"=",
"None",
",",
"inplace",
"=",
"False",
")",
":",
"warnings",
".",
"warn",
"(",
"'clip_lower(threshold) is deprecated, '",
"'use clip(lower=threshold) instead'",
",",
"FutureWarning",
",",
"stacklev... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.groupby | Group DataFrame or Series using a mapper or by a Series of columns.
A groupby operation involves some combination of splitting the
object, applying a function, and combining the results. This can be
used to group large amounts of data and compute operations on these
groups.
Par... | pandas/core/generic.py | def groupby(self, by=None, axis=0, level=None, as_index=True, sort=True,
group_keys=True, squeeze=False, observed=False, **kwargs):
"""
Group DataFrame or Series using a mapper or by a Series of columns.
A groupby operation involves some combination of splitting the
obje... | def groupby(self, by=None, axis=0, level=None, as_index=True, sort=True,
group_keys=True, squeeze=False, observed=False, **kwargs):
"""
Group DataFrame or Series using a mapper or by a Series of columns.
A groupby operation involves some combination of splitting the
obje... | [
"Group",
"DataFrame",
"or",
"Series",
"using",
"a",
"mapper",
"or",
"by",
"a",
"Series",
"of",
"columns",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L7567-L7685 | [
"def",
"groupby",
"(",
"self",
",",
"by",
"=",
"None",
",",
"axis",
"=",
"0",
",",
"level",
"=",
"None",
",",
"as_index",
"=",
"True",
",",
"sort",
"=",
"True",
",",
"group_keys",
"=",
"True",
",",
"squeeze",
"=",
"False",
",",
"observed",
"=",
"... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.asfreq | Convert TimeSeries to specified frequency.
Optionally provide filling method to pad/backfill missing values.
Returns the original data conformed to a new index with the specified
frequency. ``resample`` is more appropriate if an operation, such as
summarization, is necessary to represe... | pandas/core/generic.py | def asfreq(self, freq, method=None, how=None, normalize=False,
fill_value=None):
"""
Convert TimeSeries to specified frequency.
Optionally provide filling method to pad/backfill missing values.
Returns the original data conformed to a new index with the specified
... | def asfreq(self, freq, method=None, how=None, normalize=False,
fill_value=None):
"""
Convert TimeSeries to specified frequency.
Optionally provide filling method to pad/backfill missing values.
Returns the original data conformed to a new index with the specified
... | [
"Convert",
"TimeSeries",
"to",
"specified",
"frequency",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L7687-L7784 | [
"def",
"asfreq",
"(",
"self",
",",
"freq",
",",
"method",
"=",
"None",
",",
"how",
"=",
"None",
",",
"normalize",
"=",
"False",
",",
"fill_value",
"=",
"None",
")",
":",
"from",
"pandas",
".",
"core",
".",
"resample",
"import",
"asfreq",
"return",
"a... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.at_time | Select values at particular time of day (e.g. 9:30AM).
Parameters
----------
time : datetime.time or str
axis : {0 or 'index', 1 or 'columns'}, default 0
.. versionadded:: 0.24.0
Returns
-------
Series or DataFrame
Raises
------
... | pandas/core/generic.py | def at_time(self, time, asof=False, axis=None):
"""
Select values at particular time of day (e.g. 9:30AM).
Parameters
----------
time : datetime.time or str
axis : {0 or 'index', 1 or 'columns'}, default 0
.. versionadded:: 0.24.0
Returns
--... | def at_time(self, time, asof=False, axis=None):
"""
Select values at particular time of day (e.g. 9:30AM).
Parameters
----------
time : datetime.time or str
axis : {0 or 'index', 1 or 'columns'}, default 0
.. versionadded:: 0.24.0
Returns
--... | [
"Select",
"values",
"at",
"particular",
"time",
"of",
"day",
"(",
"e",
".",
"g",
".",
"9",
":",
"30AM",
")",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L7786-L7840 | [
"def",
"at_time",
"(",
"self",
",",
"time",
",",
"asof",
"=",
"False",
",",
"axis",
"=",
"None",
")",
":",
"if",
"axis",
"is",
"None",
":",
"axis",
"=",
"self",
".",
"_stat_axis_number",
"axis",
"=",
"self",
".",
"_get_axis_number",
"(",
"axis",
")",... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.between_time | Select values between particular times of the day (e.g., 9:00-9:30 AM).
By setting ``start_time`` to be later than ``end_time``,
you can get the times that are *not* between the two times.
Parameters
----------
start_time : datetime.time or str
end_time : datetime.time ... | pandas/core/generic.py | def between_time(self, start_time, end_time, include_start=True,
include_end=True, axis=None):
"""
Select values between particular times of the day (e.g., 9:00-9:30 AM).
By setting ``start_time`` to be later than ``end_time``,
you can get the times that are *not* b... | def between_time(self, start_time, end_time, include_start=True,
include_end=True, axis=None):
"""
Select values between particular times of the day (e.g., 9:00-9:30 AM).
By setting ``start_time`` to be later than ``end_time``,
you can get the times that are *not* b... | [
"Select",
"values",
"between",
"particular",
"times",
"of",
"the",
"day",
"(",
"e",
".",
"g",
".",
"9",
":",
"00",
"-",
"9",
":",
"30",
"AM",
")",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L7842-L7913 | [
"def",
"between_time",
"(",
"self",
",",
"start_time",
",",
"end_time",
",",
"include_start",
"=",
"True",
",",
"include_end",
"=",
"True",
",",
"axis",
"=",
"None",
")",
":",
"if",
"axis",
"is",
"None",
":",
"axis",
"=",
"self",
".",
"_stat_axis_number"... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.resample | Resample time-series data.
Convenience method for frequency conversion and resampling of time
series. Object must have a datetime-like index (`DatetimeIndex`,
`PeriodIndex`, or `TimedeltaIndex`), or pass datetime-like values
to the `on` or `level` keyword.
Parameters
--... | pandas/core/generic.py | def resample(self, rule, how=None, axis=0, fill_method=None, closed=None,
label=None, convention='start', kind=None, loffset=None,
limit=None, base=0, on=None, level=None):
"""
Resample time-series data.
Convenience method for frequency conversion and resamplin... | def resample(self, rule, how=None, axis=0, fill_method=None, closed=None,
label=None, convention='start', kind=None, loffset=None,
limit=None, base=0, on=None, level=None):
"""
Resample time-series data.
Convenience method for frequency conversion and resamplin... | [
"Resample",
"time",
"-",
"series",
"data",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L7915-L8212 | [
"def",
"resample",
"(",
"self",
",",
"rule",
",",
"how",
"=",
"None",
",",
"axis",
"=",
"0",
",",
"fill_method",
"=",
"None",
",",
"closed",
"=",
"None",
",",
"label",
"=",
"None",
",",
"convention",
"=",
"'start'",
",",
"kind",
"=",
"None",
",",
... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.first | Convenience method for subsetting initial periods of time series data
based on a date offset.
Parameters
----------
offset : string, DateOffset, dateutil.relativedelta
Returns
-------
subset : same type as caller
Raises
------
TypeError
... | pandas/core/generic.py | def first(self, offset):
"""
Convenience method for subsetting initial periods of time series data
based on a date offset.
Parameters
----------
offset : string, DateOffset, dateutil.relativedelta
Returns
-------
subset : same type as caller
... | def first(self, offset):
"""
Convenience method for subsetting initial periods of time series data
based on a date offset.
Parameters
----------
offset : string, DateOffset, dateutil.relativedelta
Returns
-------
subset : same type as caller
... | [
"Convenience",
"method",
"for",
"subsetting",
"initial",
"periods",
"of",
"time",
"series",
"data",
"based",
"on",
"a",
"date",
"offset",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L8214-L8275 | [
"def",
"first",
"(",
"self",
",",
"offset",
")",
":",
"if",
"not",
"isinstance",
"(",
"self",
".",
"index",
",",
"DatetimeIndex",
")",
":",
"raise",
"TypeError",
"(",
"\"'first' only supports a DatetimeIndex index\"",
")",
"if",
"len",
"(",
"self",
".",
"ind... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.last | Convenience method for subsetting final periods of time series data
based on a date offset.
Parameters
----------
offset : string, DateOffset, dateutil.relativedelta
Returns
-------
subset : same type as caller
Raises
------
TypeError
... | pandas/core/generic.py | def last(self, offset):
"""
Convenience method for subsetting final periods of time series data
based on a date offset.
Parameters
----------
offset : string, DateOffset, dateutil.relativedelta
Returns
-------
subset : same type as caller
... | def last(self, offset):
"""
Convenience method for subsetting final periods of time series data
based on a date offset.
Parameters
----------
offset : string, DateOffset, dateutil.relativedelta
Returns
-------
subset : same type as caller
... | [
"Convenience",
"method",
"for",
"subsetting",
"final",
"periods",
"of",
"time",
"series",
"data",
"based",
"on",
"a",
"date",
"offset",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L8277-L8333 | [
"def",
"last",
"(",
"self",
",",
"offset",
")",
":",
"if",
"not",
"isinstance",
"(",
"self",
".",
"index",
",",
"DatetimeIndex",
")",
":",
"raise",
"TypeError",
"(",
"\"'last' only supports a DatetimeIndex index\"",
")",
"if",
"len",
"(",
"self",
".",
"index... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.rank | Compute numerical data ranks (1 through n) along axis. Equal values are
assigned a rank that is the average of the ranks of those values.
Parameters
----------
axis : {0 or 'index', 1 or 'columns'}, default 0
index to direct ranking
method : {'average', 'min', 'max',... | pandas/core/generic.py | def rank(self, axis=0, method='average', numeric_only=None,
na_option='keep', ascending=True, pct=False):
"""
Compute numerical data ranks (1 through n) along axis. Equal values are
assigned a rank that is the average of the ranks of those values.
Parameters
-------... | def rank(self, axis=0, method='average', numeric_only=None,
na_option='keep', ascending=True, pct=False):
"""
Compute numerical data ranks (1 through n) along axis. Equal values are
assigned a rank that is the average of the ranks of those values.
Parameters
-------... | [
"Compute",
"numerical",
"data",
"ranks",
"(",
"1",
"through",
"n",
")",
"along",
"axis",
".",
"Equal",
"values",
"are",
"assigned",
"a",
"rank",
"that",
"is",
"the",
"average",
"of",
"the",
"ranks",
"of",
"those",
"values",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L8335-L8397 | [
"def",
"rank",
"(",
"self",
",",
"axis",
"=",
"0",
",",
"method",
"=",
"'average'",
",",
"numeric_only",
"=",
"None",
",",
"na_option",
"=",
"'keep'",
",",
"ascending",
"=",
"True",
",",
"pct",
"=",
"False",
")",
":",
"axis",
"=",
"self",
".",
"_ge... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame._where | Equivalent to public method `where`, except that `other` is not
applied as a function even if callable. Used in __setitem__. | pandas/core/generic.py | def _where(self, cond, other=np.nan, inplace=False, axis=None, level=None,
errors='raise', try_cast=False):
"""
Equivalent to public method `where`, except that `other` is not
applied as a function even if callable. Used in __setitem__.
"""
inplace = validate_bool_... | def _where(self, cond, other=np.nan, inplace=False, axis=None, level=None,
errors='raise', try_cast=False):
"""
Equivalent to public method `where`, except that `other` is not
applied as a function even if callable. Used in __setitem__.
"""
inplace = validate_bool_... | [
"Equivalent",
"to",
"public",
"method",
"where",
"except",
"that",
"other",
"is",
"not",
"applied",
"as",
"a",
"function",
"even",
"if",
"callable",
".",
"Used",
"in",
"__setitem__",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L8609-L8743 | [
"def",
"_where",
"(",
"self",
",",
"cond",
",",
"other",
"=",
"np",
".",
"nan",
",",
"inplace",
"=",
"False",
",",
"axis",
"=",
"None",
",",
"level",
"=",
"None",
",",
"errors",
"=",
"'raise'",
",",
"try_cast",
"=",
"False",
")",
":",
"inplace",
... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.slice_shift | Equivalent to `shift` without copying data. The shifted data will
not include the dropped periods and the shifted axis will be smaller
than the original.
Parameters
----------
periods : int
Number of periods to move, can be positive or negative
Returns
... | pandas/core/generic.py | def slice_shift(self, periods=1, axis=0):
"""
Equivalent to `shift` without copying data. The shifted data will
not include the dropped periods and the shifted axis will be smaller
than the original.
Parameters
----------
periods : int
Number of perio... | def slice_shift(self, periods=1, axis=0):
"""
Equivalent to `shift` without copying data. The shifted data will
not include the dropped periods and the shifted axis will be smaller
than the original.
Parameters
----------
periods : int
Number of perio... | [
"Equivalent",
"to",
"shift",
"without",
"copying",
"data",
".",
"The",
"shifted",
"data",
"will",
"not",
"include",
"the",
"dropped",
"periods",
"and",
"the",
"shifted",
"axis",
"will",
"be",
"smaller",
"than",
"the",
"original",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L9010-L9044 | [
"def",
"slice_shift",
"(",
"self",
",",
"periods",
"=",
"1",
",",
"axis",
"=",
"0",
")",
":",
"if",
"periods",
"==",
"0",
":",
"return",
"self",
"if",
"periods",
">",
"0",
":",
"vslicer",
"=",
"slice",
"(",
"None",
",",
"-",
"periods",
")",
"isli... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.tshift | Shift the time index, using the index's frequency if available.
Parameters
----------
periods : int
Number of periods to move, can be positive or negative
freq : DateOffset, timedelta, or time rule string, default None
Increment to use from the tseries module or ... | pandas/core/generic.py | def tshift(self, periods=1, freq=None, axis=0):
"""
Shift the time index, using the index's frequency if available.
Parameters
----------
periods : int
Number of periods to move, can be positive or negative
freq : DateOffset, timedelta, or time rule string, d... | def tshift(self, periods=1, freq=None, axis=0):
"""
Shift the time index, using the index's frequency if available.
Parameters
----------
periods : int
Number of periods to move, can be positive or negative
freq : DateOffset, timedelta, or time rule string, d... | [
"Shift",
"the",
"time",
"index",
"using",
"the",
"index",
"s",
"frequency",
"if",
"available",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L9046-L9101 | [
"def",
"tshift",
"(",
"self",
",",
"periods",
"=",
"1",
",",
"freq",
"=",
"None",
",",
"axis",
"=",
"0",
")",
":",
"index",
"=",
"self",
".",
"_get_axis",
"(",
"axis",
")",
"if",
"freq",
"is",
"None",
":",
"freq",
"=",
"getattr",
"(",
"index",
... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.truncate | Truncate a Series or DataFrame before and after some index value.
This is a useful shorthand for boolean indexing based on index
values above or below certain thresholds.
Parameters
----------
before : date, string, int
Truncate all rows before this index value.
... | pandas/core/generic.py | def truncate(self, before=None, after=None, axis=None, copy=True):
"""
Truncate a Series or DataFrame before and after some index value.
This is a useful shorthand for boolean indexing based on index
values above or below certain thresholds.
Parameters
----------
... | def truncate(self, before=None, after=None, axis=None, copy=True):
"""
Truncate a Series or DataFrame before and after some index value.
This is a useful shorthand for boolean indexing based on index
values above or below certain thresholds.
Parameters
----------
... | [
"Truncate",
"a",
"Series",
"or",
"DataFrame",
"before",
"and",
"after",
"some",
"index",
"value",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L9103-L9255 | [
"def",
"truncate",
"(",
"self",
",",
"before",
"=",
"None",
",",
"after",
"=",
"None",
",",
"axis",
"=",
"None",
",",
"copy",
"=",
"True",
")",
":",
"if",
"axis",
"is",
"None",
":",
"axis",
"=",
"self",
".",
"_stat_axis_number",
"axis",
"=",
"self"... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.tz_convert | Convert tz-aware axis to target time zone.
Parameters
----------
tz : string or pytz.timezone object
axis : the axis to convert
level : int, str, default None
If axis ia a MultiIndex, convert a specific level. Otherwise
must be None
copy : boolean... | pandas/core/generic.py | def tz_convert(self, tz, axis=0, level=None, copy=True):
"""
Convert tz-aware axis to target time zone.
Parameters
----------
tz : string or pytz.timezone object
axis : the axis to convert
level : int, str, default None
If axis ia a MultiIndex, conver... | def tz_convert(self, tz, axis=0, level=None, copy=True):
"""
Convert tz-aware axis to target time zone.
Parameters
----------
tz : string or pytz.timezone object
axis : the axis to convert
level : int, str, default None
If axis ia a MultiIndex, conver... | [
"Convert",
"tz",
"-",
"aware",
"axis",
"to",
"target",
"time",
"zone",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L9257-L9307 | [
"def",
"tz_convert",
"(",
"self",
",",
"tz",
",",
"axis",
"=",
"0",
",",
"level",
"=",
"None",
",",
"copy",
"=",
"True",
")",
":",
"axis",
"=",
"self",
".",
"_get_axis_number",
"(",
"axis",
")",
"ax",
"=",
"self",
".",
"_get_axis",
"(",
"axis",
"... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.tz_localize | Localize tz-naive index of a Series or DataFrame to target time zone.
This operation localizes the Index. To localize the values in a
timezone-naive Series, use :meth:`Series.dt.tz_localize`.
Parameters
----------
tz : string or pytz.timezone object
axis : the axis to l... | pandas/core/generic.py | def tz_localize(self, tz, axis=0, level=None, copy=True,
ambiguous='raise', nonexistent='raise'):
"""
Localize tz-naive index of a Series or DataFrame to target time zone.
This operation localizes the Index. To localize the values in a
timezone-naive Series, use :met... | def tz_localize(self, tz, axis=0, level=None, copy=True,
ambiguous='raise', nonexistent='raise'):
"""
Localize tz-naive index of a Series or DataFrame to target time zone.
This operation localizes the Index. To localize the values in a
timezone-naive Series, use :met... | [
"Localize",
"tz",
"-",
"naive",
"index",
"of",
"a",
"Series",
"or",
"DataFrame",
"to",
"target",
"time",
"zone",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L9309-L9471 | [
"def",
"tz_localize",
"(",
"self",
",",
"tz",
",",
"axis",
"=",
"0",
",",
"level",
"=",
"None",
",",
"copy",
"=",
"True",
",",
"ambiguous",
"=",
"'raise'",
",",
"nonexistent",
"=",
"'raise'",
")",
":",
"nonexistent_options",
"=",
"(",
"'raise'",
",",
... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame.describe | Generate descriptive statistics that summarize the central tendency,
dispersion and shape of a dataset's distribution, excluding
``NaN`` values.
Analyzes both numeric and object series, as well
as ``DataFrame`` column sets of mixed data types. The output
will vary depending on w... | pandas/core/generic.py | def describe(self, percentiles=None, include=None, exclude=None):
"""
Generate descriptive statistics that summarize the central tendency,
dispersion and shape of a dataset's distribution, excluding
``NaN`` values.
Analyzes both numeric and object series, as well
as ``Da... | def describe(self, percentiles=None, include=None, exclude=None):
"""
Generate descriptive statistics that summarize the central tendency,
dispersion and shape of a dataset's distribution, excluding
``NaN`` values.
Analyzes both numeric and object series, as well
as ``Da... | [
"Generate",
"descriptive",
"statistics",
"that",
"summarize",
"the",
"central",
"tendency",
"dispersion",
"and",
"shape",
"of",
"a",
"dataset",
"s",
"distribution",
"excluding",
"NaN",
"values",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L9544-L9875 | [
"def",
"describe",
"(",
"self",
",",
"percentiles",
"=",
"None",
",",
"include",
"=",
"None",
",",
"exclude",
"=",
"None",
")",
":",
"if",
"self",
".",
"ndim",
">=",
"3",
":",
"msg",
"=",
"\"describe is not implemented on Panel objects.\"",
"raise",
"NotImpl... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame._check_percentile | Validate percentiles (used by describe and quantile). | pandas/core/generic.py | def _check_percentile(self, q):
"""
Validate percentiles (used by describe and quantile).
"""
msg = ("percentiles should all be in the interval [0, 1]. "
"Try {0} instead.")
q = np.asarray(q)
if q.ndim == 0:
if not 0 <= q <= 1:
... | def _check_percentile(self, q):
"""
Validate percentiles (used by describe and quantile).
"""
msg = ("percentiles should all be in the interval [0, 1]. "
"Try {0} instead.")
q = np.asarray(q)
if q.ndim == 0:
if not 0 <= q <= 1:
... | [
"Validate",
"percentiles",
"(",
"used",
"by",
"describe",
"and",
"quantile",
")",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L9877-L9891 | [
"def",
"_check_percentile",
"(",
"self",
",",
"q",
")",
":",
"msg",
"=",
"(",
"\"percentiles should all be in the interval [0, 1]. \"",
"\"Try {0} instead.\"",
")",
"q",
"=",
"np",
".",
"asarray",
"(",
"q",
")",
"if",
"q",
".",
"ndim",
"==",
"0",
":",
"if",
... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame._add_numeric_operations | Add the operations to the cls; evaluate the doc strings again | pandas/core/generic.py | def _add_numeric_operations(cls):
"""
Add the operations to the cls; evaluate the doc strings again
"""
axis_descr, name, name2 = _doc_parms(cls)
cls.any = _make_logical_function(
cls, 'any', name, name2, axis_descr, _any_desc, nanops.nanany,
_any_see_al... | def _add_numeric_operations(cls):
"""
Add the operations to the cls; evaluate the doc strings again
"""
axis_descr, name, name2 = _doc_parms(cls)
cls.any = _make_logical_function(
cls, 'any', name, name2, axis_descr, _any_desc, nanops.nanany,
_any_see_al... | [
"Add",
"the",
"operations",
"to",
"the",
"cls",
";",
"evaluate",
"the",
"doc",
"strings",
"again"
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L10038-L10162 | [
"def",
"_add_numeric_operations",
"(",
"cls",
")",
":",
"axis_descr",
",",
"name",
",",
"name2",
"=",
"_doc_parms",
"(",
"cls",
")",
"cls",
".",
"any",
"=",
"_make_logical_function",
"(",
"cls",
",",
"'any'",
",",
"name",
",",
"name2",
",",
"axis_descr",
... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame._add_series_only_operations | Add the series only operations to the cls; evaluate the doc
strings again. | pandas/core/generic.py | def _add_series_only_operations(cls):
"""
Add the series only operations to the cls; evaluate the doc
strings again.
"""
axis_descr, name, name2 = _doc_parms(cls)
def nanptp(values, axis=0, skipna=True):
nmax = nanops.nanmax(values, axis, skipna)
... | def _add_series_only_operations(cls):
"""
Add the series only operations to the cls; evaluate the doc
strings again.
"""
axis_descr, name, name2 = _doc_parms(cls)
def nanptp(values, axis=0, skipna=True):
nmax = nanops.nanmax(values, axis, skipna)
... | [
"Add",
"the",
"series",
"only",
"operations",
"to",
"the",
"cls",
";",
"evaluate",
"the",
"doc",
"strings",
"again",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L10165-L10187 | [
"def",
"_add_series_only_operations",
"(",
"cls",
")",
":",
"axis_descr",
",",
"name",
",",
"name2",
"=",
"_doc_parms",
"(",
"cls",
")",
"def",
"nanptp",
"(",
"values",
",",
"axis",
"=",
"0",
",",
"skipna",
"=",
"True",
")",
":",
"nmax",
"=",
"nanops",... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame._add_series_or_dataframe_operations | Add the series or dataframe only operations to the cls; evaluate
the doc strings again. | pandas/core/generic.py | def _add_series_or_dataframe_operations(cls):
"""
Add the series or dataframe only operations to the cls; evaluate
the doc strings again.
"""
from pandas.core import window as rwindow
@Appender(rwindow.rolling.__doc__)
def rolling(self, window, min_periods=None,... | def _add_series_or_dataframe_operations(cls):
"""
Add the series or dataframe only operations to the cls; evaluate
the doc strings again.
"""
from pandas.core import window as rwindow
@Appender(rwindow.rolling.__doc__)
def rolling(self, window, min_periods=None,... | [
"Add",
"the",
"series",
"or",
"dataframe",
"only",
"operations",
"to",
"the",
"cls",
";",
"evaluate",
"the",
"doc",
"strings",
"again",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L10190-L10226 | [
"def",
"_add_series_or_dataframe_operations",
"(",
"cls",
")",
":",
"from",
"pandas",
".",
"core",
"import",
"window",
"as",
"rwindow",
"@",
"Appender",
"(",
"rwindow",
".",
"rolling",
".",
"__doc__",
")",
"def",
"rolling",
"(",
"self",
",",
"window",
",",
... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | NDFrame._find_valid_index | Retrieves the index of the first valid value.
Parameters
----------
how : {'first', 'last'}
Use this parameter to change between the first or last valid index.
Returns
-------
idx_first_valid : type of index | pandas/core/generic.py | def _find_valid_index(self, how):
"""
Retrieves the index of the first valid value.
Parameters
----------
how : {'first', 'last'}
Use this parameter to change between the first or last valid index.
Returns
-------
idx_first_valid : type of in... | def _find_valid_index(self, how):
"""
Retrieves the index of the first valid value.
Parameters
----------
how : {'first', 'last'}
Use this parameter to change between the first or last valid index.
Returns
-------
idx_first_valid : type of in... | [
"Retrieves",
"the",
"index",
"of",
"the",
"first",
"valid",
"value",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/generic.py#L10253-L10286 | [
"def",
"_find_valid_index",
"(",
"self",
",",
"how",
")",
":",
"assert",
"how",
"in",
"[",
"'first'",
",",
"'last'",
"]",
"if",
"len",
"(",
"self",
")",
"==",
"0",
":",
"# early stop",
"return",
"None",
"is_valid",
"=",
"~",
"self",
".",
"isna",
"(",... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | PandasObject._reset_cache | Reset cached properties. If ``key`` is passed, only clears that key. | pandas/core/base.py | def _reset_cache(self, key=None):
"""
Reset cached properties. If ``key`` is passed, only clears that key.
"""
if getattr(self, '_cache', None) is None:
return
if key is None:
self._cache.clear()
else:
self._cache.pop(key, None) | def _reset_cache(self, key=None):
"""
Reset cached properties. If ``key`` is passed, only clears that key.
"""
if getattr(self, '_cache', None) is None:
return
if key is None:
self._cache.clear()
else:
self._cache.pop(key, None) | [
"Reset",
"cached",
"properties",
".",
"If",
"key",
"is",
"passed",
"only",
"clears",
"that",
"key",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/base.py#L86-L95 | [
"def",
"_reset_cache",
"(",
"self",
",",
"key",
"=",
"None",
")",
":",
"if",
"getattr",
"(",
"self",
",",
"'_cache'",
",",
"None",
")",
"is",
"None",
":",
"return",
"if",
"key",
"is",
"None",
":",
"self",
".",
"_cache",
".",
"clear",
"(",
")",
"e... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | SelectionMixin._try_aggregate_string_function | if arg is a string, then try to operate on it:
- try to find a function (or attribute) on ourselves
- try to find a numpy function
- raise | pandas/core/base.py | def _try_aggregate_string_function(self, arg, *args, **kwargs):
"""
if arg is a string, then try to operate on it:
- try to find a function (or attribute) on ourselves
- try to find a numpy function
- raise
"""
assert isinstance(arg, str)
f = getattr(sel... | def _try_aggregate_string_function(self, arg, *args, **kwargs):
"""
if arg is a string, then try to operate on it:
- try to find a function (or attribute) on ourselves
- try to find a numpy function
- raise
"""
assert isinstance(arg, str)
f = getattr(sel... | [
"if",
"arg",
"is",
"a",
"string",
"then",
"try",
"to",
"operate",
"on",
"it",
":",
"-",
"try",
"to",
"find",
"a",
"function",
"(",
"or",
"attribute",
")",
"on",
"ourselves",
"-",
"try",
"to",
"find",
"a",
"numpy",
"function",
"-",
"raise"
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/base.py#L285-L311 | [
"def",
"_try_aggregate_string_function",
"(",
"self",
",",
"arg",
",",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"assert",
"isinstance",
"(",
"arg",
",",
"str",
")",
"f",
"=",
"getattr",
"(",
"self",
",",
"arg",
",",
"None",
")",
"if",
"f",
"... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | SelectionMixin._aggregate | provide an implementation for the aggregators
Parameters
----------
arg : string, dict, function
*args : args to pass on to the function
**kwargs : kwargs to pass on to the function
Returns
-------
tuple of result, how
Notes
-----
... | pandas/core/base.py | def _aggregate(self, arg, *args, **kwargs):
"""
provide an implementation for the aggregators
Parameters
----------
arg : string, dict, function
*args : args to pass on to the function
**kwargs : kwargs to pass on to the function
Returns
-------
... | def _aggregate(self, arg, *args, **kwargs):
"""
provide an implementation for the aggregators
Parameters
----------
arg : string, dict, function
*args : args to pass on to the function
**kwargs : kwargs to pass on to the function
Returns
-------
... | [
"provide",
"an",
"implementation",
"for",
"the",
"aggregators"
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/base.py#L313-L553 | [
"def",
"_aggregate",
"(",
"self",
",",
"arg",
",",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"is_aggregator",
"=",
"lambda",
"x",
":",
"isinstance",
"(",
"x",
",",
"(",
"list",
",",
"tuple",
",",
"dict",
")",
")",
"is_nested_renamer",
"=",
"F... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | SelectionMixin._shallow_copy | return a new object with the replacement attributes | pandas/core/base.py | def _shallow_copy(self, obj=None, obj_type=None, **kwargs):
"""
return a new object with the replacement attributes
"""
if obj is None:
obj = self._selected_obj.copy()
if obj_type is None:
obj_type = self._constructor
if isinstance(obj, obj_type):
... | def _shallow_copy(self, obj=None, obj_type=None, **kwargs):
"""
return a new object with the replacement attributes
"""
if obj is None:
obj = self._selected_obj.copy()
if obj_type is None:
obj_type = self._constructor
if isinstance(obj, obj_type):
... | [
"return",
"a",
"new",
"object",
"with",
"the",
"replacement",
"attributes"
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/base.py#L619-L632 | [
"def",
"_shallow_copy",
"(",
"self",
",",
"obj",
"=",
"None",
",",
"obj_type",
"=",
"None",
",",
"*",
"*",
"kwargs",
")",
":",
"if",
"obj",
"is",
"None",
":",
"obj",
"=",
"self",
".",
"_selected_obj",
".",
"copy",
"(",
")",
"if",
"obj_type",
"is",
... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | IndexOpsMixin.itemsize | Return the size of the dtype of the item of the underlying data.
.. deprecated:: 0.23.0 | pandas/core/base.py | def itemsize(self):
"""
Return the size of the dtype of the item of the underlying data.
.. deprecated:: 0.23.0
"""
warnings.warn("{obj}.itemsize is deprecated and will be removed "
"in a future version".format(obj=type(self).__name__),
... | def itemsize(self):
"""
Return the size of the dtype of the item of the underlying data.
.. deprecated:: 0.23.0
"""
warnings.warn("{obj}.itemsize is deprecated and will be removed "
"in a future version".format(obj=type(self).__name__),
... | [
"Return",
"the",
"size",
"of",
"the",
"dtype",
"of",
"the",
"item",
"of",
"the",
"underlying",
"data",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/base.py#L715-L724 | [
"def",
"itemsize",
"(",
"self",
")",
":",
"warnings",
".",
"warn",
"(",
"\"{obj}.itemsize is deprecated and will be removed \"",
"\"in a future version\"",
".",
"format",
"(",
"obj",
"=",
"type",
"(",
"self",
")",
".",
"__name__",
")",
",",
"FutureWarning",
",",
... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | IndexOpsMixin.base | Return the base object if the memory of the underlying data is shared.
.. deprecated:: 0.23.0 | pandas/core/base.py | def base(self):
"""
Return the base object if the memory of the underlying data is shared.
.. deprecated:: 0.23.0
"""
warnings.warn("{obj}.base is deprecated and will be removed "
"in a future version".format(obj=type(self).__name__),
... | def base(self):
"""
Return the base object if the memory of the underlying data is shared.
.. deprecated:: 0.23.0
"""
warnings.warn("{obj}.base is deprecated and will be removed "
"in a future version".format(obj=type(self).__name__),
... | [
"Return",
"the",
"base",
"object",
"if",
"the",
"memory",
"of",
"the",
"underlying",
"data",
"is",
"shared",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/base.py#L765-L774 | [
"def",
"base",
"(",
"self",
")",
":",
"warnings",
".",
"warn",
"(",
"\"{obj}.base is deprecated and will be removed \"",
"\"in a future version\"",
".",
"format",
"(",
"obj",
"=",
"type",
"(",
"self",
")",
".",
"__name__",
")",
",",
"FutureWarning",
",",
"stackl... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | IndexOpsMixin.array | The ExtensionArray of the data backing this Series or Index.
.. versionadded:: 0.24.0
Returns
-------
ExtensionArray
An ExtensionArray of the values stored within. For extension
types, this is the actual array. For NumPy native types, this
is a thin ... | pandas/core/base.py | def array(self) -> ExtensionArray:
"""
The ExtensionArray of the data backing this Series or Index.
.. versionadded:: 0.24.0
Returns
-------
ExtensionArray
An ExtensionArray of the values stored within. For extension
types, this is the actual arr... | def array(self) -> ExtensionArray:
"""
The ExtensionArray of the data backing this Series or Index.
.. versionadded:: 0.24.0
Returns
-------
ExtensionArray
An ExtensionArray of the values stored within. For extension
types, this is the actual arr... | [
"The",
"ExtensionArray",
"of",
"the",
"data",
"backing",
"this",
"Series",
"or",
"Index",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/base.py#L777-L853 | [
"def",
"array",
"(",
"self",
")",
"->",
"ExtensionArray",
":",
"result",
"=",
"self",
".",
"_values",
"if",
"is_datetime64_ns_dtype",
"(",
"result",
".",
"dtype",
")",
":",
"from",
"pandas",
".",
"arrays",
"import",
"DatetimeArray",
"result",
"=",
"DatetimeA... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | IndexOpsMixin.to_numpy | A NumPy ndarray representing the values in this Series or Index.
.. versionadded:: 0.24.0
Parameters
----------
dtype : str or numpy.dtype, optional
The dtype to pass to :meth:`numpy.asarray`
copy : bool, default False
Whether to ensure that the returned... | pandas/core/base.py | def to_numpy(self, dtype=None, copy=False):
"""
A NumPy ndarray representing the values in this Series or Index.
.. versionadded:: 0.24.0
Parameters
----------
dtype : str or numpy.dtype, optional
The dtype to pass to :meth:`numpy.asarray`
copy : boo... | def to_numpy(self, dtype=None, copy=False):
"""
A NumPy ndarray representing the values in this Series or Index.
.. versionadded:: 0.24.0
Parameters
----------
dtype : str or numpy.dtype, optional
The dtype to pass to :meth:`numpy.asarray`
copy : boo... | [
"A",
"NumPy",
"ndarray",
"representing",
"the",
"values",
"in",
"this",
"Series",
"or",
"Index",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/base.py#L855-L949 | [
"def",
"to_numpy",
"(",
"self",
",",
"dtype",
"=",
"None",
",",
"copy",
"=",
"False",
")",
":",
"if",
"is_datetime64tz_dtype",
"(",
"self",
".",
"dtype",
")",
"and",
"dtype",
"is",
"None",
":",
"# note: this is going to change very soon.",
"# I have a WIP PR mak... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | IndexOpsMixin._ndarray_values | The data as an ndarray, possibly losing information.
The expectation is that this is cheap to compute, and is primarily
used for interacting with our indexers.
- categorical -> codes | pandas/core/base.py | def _ndarray_values(self) -> np.ndarray:
"""
The data as an ndarray, possibly losing information.
The expectation is that this is cheap to compute, and is primarily
used for interacting with our indexers.
- categorical -> codes
"""
if is_extension_array_dtype(se... | def _ndarray_values(self) -> np.ndarray:
"""
The data as an ndarray, possibly losing information.
The expectation is that this is cheap to compute, and is primarily
used for interacting with our indexers.
- categorical -> codes
"""
if is_extension_array_dtype(se... | [
"The",
"data",
"as",
"an",
"ndarray",
"possibly",
"losing",
"information",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/base.py#L952-L963 | [
"def",
"_ndarray_values",
"(",
"self",
")",
"->",
"np",
".",
"ndarray",
":",
"if",
"is_extension_array_dtype",
"(",
"self",
")",
":",
"return",
"self",
".",
"array",
".",
"_ndarray_values",
"return",
"self",
".",
"values"
] | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | IndexOpsMixin.max | Return the maximum value of the Index.
Parameters
----------
axis : int, optional
For compatibility with NumPy. Only 0 or None are allowed.
skipna : bool, default True
Returns
-------
scalar
Maximum value.
See Also
------... | pandas/core/base.py | def max(self, axis=None, skipna=True):
"""
Return the maximum value of the Index.
Parameters
----------
axis : int, optional
For compatibility with NumPy. Only 0 or None are allowed.
skipna : bool, default True
Returns
-------
scalar
... | def max(self, axis=None, skipna=True):
"""
Return the maximum value of the Index.
Parameters
----------
axis : int, optional
For compatibility with NumPy. Only 0 or None are allowed.
skipna : bool, default True
Returns
-------
scalar
... | [
"Return",
"the",
"maximum",
"value",
"of",
"the",
"Index",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/base.py#L969-L1007 | [
"def",
"max",
"(",
"self",
",",
"axis",
"=",
"None",
",",
"skipna",
"=",
"True",
")",
":",
"nv",
".",
"validate_minmax_axis",
"(",
"axis",
")",
"return",
"nanops",
".",
"nanmax",
"(",
"self",
".",
"_values",
",",
"skipna",
"=",
"skipna",
")"
] | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | IndexOpsMixin.argmax | Return an ndarray of the maximum argument indexer.
Parameters
----------
axis : {None}
Dummy argument for consistency with Series
skipna : bool, default True
See Also
--------
numpy.ndarray.argmax | pandas/core/base.py | def argmax(self, axis=None, skipna=True):
"""
Return an ndarray of the maximum argument indexer.
Parameters
----------
axis : {None}
Dummy argument for consistency with Series
skipna : bool, default True
See Also
--------
numpy.ndarra... | def argmax(self, axis=None, skipna=True):
"""
Return an ndarray of the maximum argument indexer.
Parameters
----------
axis : {None}
Dummy argument for consistency with Series
skipna : bool, default True
See Also
--------
numpy.ndarra... | [
"Return",
"an",
"ndarray",
"of",
"the",
"maximum",
"argument",
"indexer",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/base.py#L1009-L1024 | [
"def",
"argmax",
"(",
"self",
",",
"axis",
"=",
"None",
",",
"skipna",
"=",
"True",
")",
":",
"nv",
".",
"validate_minmax_axis",
"(",
"axis",
")",
"return",
"nanops",
".",
"nanargmax",
"(",
"self",
".",
"_values",
",",
"skipna",
"=",
"skipna",
")"
] | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | IndexOpsMixin.min | Return the minimum value of the Index.
Parameters
----------
axis : {None}
Dummy argument for consistency with Series
skipna : bool, default True
Returns
-------
scalar
Minimum value.
See Also
--------
Index.max :... | pandas/core/base.py | def min(self, axis=None, skipna=True):
"""
Return the minimum value of the Index.
Parameters
----------
axis : {None}
Dummy argument for consistency with Series
skipna : bool, default True
Returns
-------
scalar
Minimum va... | def min(self, axis=None, skipna=True):
"""
Return the minimum value of the Index.
Parameters
----------
axis : {None}
Dummy argument for consistency with Series
skipna : bool, default True
Returns
-------
scalar
Minimum va... | [
"Return",
"the",
"minimum",
"value",
"of",
"the",
"Index",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/base.py#L1026-L1064 | [
"def",
"min",
"(",
"self",
",",
"axis",
"=",
"None",
",",
"skipna",
"=",
"True",
")",
":",
"nv",
".",
"validate_minmax_axis",
"(",
"axis",
")",
"return",
"nanops",
".",
"nanmin",
"(",
"self",
".",
"_values",
",",
"skipna",
"=",
"skipna",
")"
] | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | IndexOpsMixin.argmin | Return a ndarray of the minimum argument indexer.
Parameters
----------
axis : {None}
Dummy argument for consistency with Series
skipna : bool, default True
Returns
-------
numpy.ndarray
See Also
--------
numpy.ndarray.argmin | pandas/core/base.py | def argmin(self, axis=None, skipna=True):
"""
Return a ndarray of the minimum argument indexer.
Parameters
----------
axis : {None}
Dummy argument for consistency with Series
skipna : bool, default True
Returns
-------
numpy.ndarray
... | def argmin(self, axis=None, skipna=True):
"""
Return a ndarray of the minimum argument indexer.
Parameters
----------
axis : {None}
Dummy argument for consistency with Series
skipna : bool, default True
Returns
-------
numpy.ndarray
... | [
"Return",
"a",
"ndarray",
"of",
"the",
"minimum",
"argument",
"indexer",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/base.py#L1066-L1085 | [
"def",
"argmin",
"(",
"self",
",",
"axis",
"=",
"None",
",",
"skipna",
"=",
"True",
")",
":",
"nv",
".",
"validate_minmax_axis",
"(",
"axis",
")",
"return",
"nanops",
".",
"nanargmin",
"(",
"self",
".",
"_values",
",",
"skipna",
"=",
"skipna",
")"
] | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | IndexOpsMixin.tolist | Return a list of the values.
These are each a scalar type, which is a Python scalar
(for str, int, float) or a pandas scalar
(for Timestamp/Timedelta/Interval/Period)
Returns
-------
list
See Also
--------
numpy.ndarray.tolist | pandas/core/base.py | def tolist(self):
"""
Return a list of the values.
These are each a scalar type, which is a Python scalar
(for str, int, float) or a pandas scalar
(for Timestamp/Timedelta/Interval/Period)
Returns
-------
list
See Also
--------
n... | def tolist(self):
"""
Return a list of the values.
These are each a scalar type, which is a Python scalar
(for str, int, float) or a pandas scalar
(for Timestamp/Timedelta/Interval/Period)
Returns
-------
list
See Also
--------
n... | [
"Return",
"a",
"list",
"of",
"the",
"values",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/base.py#L1087-L1108 | [
"def",
"tolist",
"(",
"self",
")",
":",
"if",
"is_datetimelike",
"(",
"self",
".",
"_values",
")",
":",
"return",
"[",
"com",
".",
"maybe_box_datetimelike",
"(",
"x",
")",
"for",
"x",
"in",
"self",
".",
"_values",
"]",
"elif",
"is_extension_array_dtype",
... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | IndexOpsMixin._reduce | perform the reduction type operation if we can | pandas/core/base.py | def _reduce(self, op, name, axis=0, skipna=True, numeric_only=None,
filter_type=None, **kwds):
""" perform the reduction type operation if we can """
func = getattr(self, name, None)
if func is None:
raise TypeError("{klass} cannot perform the operation {op}".format(
... | def _reduce(self, op, name, axis=0, skipna=True, numeric_only=None,
filter_type=None, **kwds):
""" perform the reduction type operation if we can """
func = getattr(self, name, None)
if func is None:
raise TypeError("{klass} cannot perform the operation {op}".format(
... | [
"perform",
"the",
"reduction",
"type",
"operation",
"if",
"we",
"can"
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/base.py#L1135-L1142 | [
"def",
"_reduce",
"(",
"self",
",",
"op",
",",
"name",
",",
"axis",
"=",
"0",
",",
"skipna",
"=",
"True",
",",
"numeric_only",
"=",
"None",
",",
"filter_type",
"=",
"None",
",",
"*",
"*",
"kwds",
")",
":",
"func",
"=",
"getattr",
"(",
"self",
","... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | IndexOpsMixin._map_values | An internal function that maps values using the input
correspondence (which can be a dict, Series, or function).
Parameters
----------
mapper : function, dict, or Series
The input correspondence object
na_action : {None, 'ignore'}
If 'ignore', propagate N... | pandas/core/base.py | def _map_values(self, mapper, na_action=None):
"""
An internal function that maps values using the input
correspondence (which can be a dict, Series, or function).
Parameters
----------
mapper : function, dict, or Series
The input correspondence object
... | def _map_values(self, mapper, na_action=None):
"""
An internal function that maps values using the input
correspondence (which can be a dict, Series, or function).
Parameters
----------
mapper : function, dict, or Series
The input correspondence object
... | [
"An",
"internal",
"function",
"that",
"maps",
"values",
"using",
"the",
"input",
"correspondence",
"(",
"which",
"can",
"be",
"a",
"dict",
"Series",
"or",
"function",
")",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/base.py#L1144-L1215 | [
"def",
"_map_values",
"(",
"self",
",",
"mapper",
",",
"na_action",
"=",
"None",
")",
":",
"# we can fastpath dict/Series to an efficient map",
"# as we know that we are not going to have to yield",
"# python types",
"if",
"isinstance",
"(",
"mapper",
",",
"dict",
")",
":... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | IndexOpsMixin.value_counts | Return a Series containing counts of unique values.
The resulting object will be in descending order so that the
first element is the most frequently-occurring element.
Excludes NA values by default.
Parameters
----------
normalize : boolean, default False
I... | pandas/core/base.py | def value_counts(self, normalize=False, sort=True, ascending=False,
bins=None, dropna=True):
"""
Return a Series containing counts of unique values.
The resulting object will be in descending order so that the
first element is the most frequently-occurring element.
... | def value_counts(self, normalize=False, sort=True, ascending=False,
bins=None, dropna=True):
"""
Return a Series containing counts of unique values.
The resulting object will be in descending order so that the
first element is the most frequently-occurring element.
... | [
"Return",
"a",
"Series",
"containing",
"counts",
"of",
"unique",
"values",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/base.py#L1217-L1299 | [
"def",
"value_counts",
"(",
"self",
",",
"normalize",
"=",
"False",
",",
"sort",
"=",
"True",
",",
"ascending",
"=",
"False",
",",
"bins",
"=",
"None",
",",
"dropna",
"=",
"True",
")",
":",
"from",
"pandas",
".",
"core",
".",
"algorithms",
"import",
... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | IndexOpsMixin.nunique | Return number of unique elements in the object.
Excludes NA values by default.
Parameters
----------
dropna : bool, default True
Don't include NaN in the count.
Returns
-------
int
See Also
--------
DataFrame.nunique: Method... | pandas/core/base.py | def nunique(self, dropna=True):
"""
Return number of unique elements in the object.
Excludes NA values by default.
Parameters
----------
dropna : bool, default True
Don't include NaN in the count.
Returns
-------
int
See Als... | def nunique(self, dropna=True):
"""
Return number of unique elements in the object.
Excludes NA values by default.
Parameters
----------
dropna : bool, default True
Don't include NaN in the count.
Returns
-------
int
See Als... | [
"Return",
"number",
"of",
"unique",
"elements",
"in",
"the",
"object",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/base.py#L1313-L1351 | [
"def",
"nunique",
"(",
"self",
",",
"dropna",
"=",
"True",
")",
":",
"uniqs",
"=",
"self",
".",
"unique",
"(",
")",
"n",
"=",
"len",
"(",
"uniqs",
")",
"if",
"dropna",
"and",
"isna",
"(",
"uniqs",
")",
".",
"any",
"(",
")",
":",
"n",
"-=",
"1... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | IndexOpsMixin.memory_usage | Memory usage of the values
Parameters
----------
deep : bool
Introspect the data deeply, interrogate
`object` dtypes for system-level memory consumption
Returns
-------
bytes used
See Also
--------
numpy.ndarray.nbytes
... | pandas/core/base.py | def memory_usage(self, deep=False):
"""
Memory usage of the values
Parameters
----------
deep : bool
Introspect the data deeply, interrogate
`object` dtypes for system-level memory consumption
Returns
-------
bytes used
S... | def memory_usage(self, deep=False):
"""
Memory usage of the values
Parameters
----------
deep : bool
Introspect the data deeply, interrogate
`object` dtypes for system-level memory consumption
Returns
-------
bytes used
S... | [
"Memory",
"usage",
"of",
"the",
"values"
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/base.py#L1396-L1425 | [
"def",
"memory_usage",
"(",
"self",
",",
"deep",
"=",
"False",
")",
":",
"if",
"hasattr",
"(",
"self",
".",
"array",
",",
"'memory_usage'",
")",
":",
"return",
"self",
".",
"array",
".",
"memory_usage",
"(",
"deep",
"=",
"deep",
")",
"v",
"=",
"self"... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | _expand_user | Return the argument with an initial component of ~ or ~user
replaced by that user's home directory.
Parameters
----------
filepath_or_buffer : object to be converted if possible
Returns
-------
expanded_filepath_or_buffer : an expanded filepath or the
i... | pandas/io/common.py | def _expand_user(filepath_or_buffer):
"""Return the argument with an initial component of ~ or ~user
replaced by that user's home directory.
Parameters
----------
filepath_or_buffer : object to be converted if possible
Returns
-------
expanded_filepath_or_buffer : an expanded filepa... | def _expand_user(filepath_or_buffer):
"""Return the argument with an initial component of ~ or ~user
replaced by that user's home directory.
Parameters
----------
filepath_or_buffer : object to be converted if possible
Returns
-------
expanded_filepath_or_buffer : an expanded filepa... | [
"Return",
"the",
"argument",
"with",
"an",
"initial",
"component",
"of",
"~",
"or",
"~user",
"replaced",
"by",
"that",
"user",
"s",
"home",
"directory",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/io/common.py#L70-L85 | [
"def",
"_expand_user",
"(",
"filepath_or_buffer",
")",
":",
"if",
"isinstance",
"(",
"filepath_or_buffer",
",",
"str",
")",
":",
"return",
"os",
".",
"path",
".",
"expanduser",
"(",
"filepath_or_buffer",
")",
"return",
"filepath_or_buffer"
] | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | _stringify_path | Attempt to convert a path-like object to a string.
Parameters
----------
filepath_or_buffer : object to be converted
Returns
-------
str_filepath_or_buffer : maybe a string version of the object
Notes
-----
Objects supporting the fspath protocol (python 3.6+) are coerced
accor... | pandas/io/common.py | def _stringify_path(filepath_or_buffer):
"""Attempt to convert a path-like object to a string.
Parameters
----------
filepath_or_buffer : object to be converted
Returns
-------
str_filepath_or_buffer : maybe a string version of the object
Notes
-----
Objects supporting the fsp... | def _stringify_path(filepath_or_buffer):
"""Attempt to convert a path-like object to a string.
Parameters
----------
filepath_or_buffer : object to be converted
Returns
-------
str_filepath_or_buffer : maybe a string version of the object
Notes
-----
Objects supporting the fsp... | [
"Attempt",
"to",
"convert",
"a",
"path",
"-",
"like",
"object",
"to",
"a",
"string",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/io/common.py#L96-L136 | [
"def",
"_stringify_path",
"(",
"filepath_or_buffer",
")",
":",
"try",
":",
"import",
"pathlib",
"_PATHLIB_INSTALLED",
"=",
"True",
"except",
"ImportError",
":",
"_PATHLIB_INSTALLED",
"=",
"False",
"try",
":",
"from",
"py",
".",
"path",
"import",
"local",
"as",
... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | get_filepath_or_buffer | If the filepath_or_buffer is a url, translate and return the buffer.
Otherwise passthrough.
Parameters
----------
filepath_or_buffer : a url, filepath (str, py.path.local or pathlib.Path),
or buffer
compression : {{'gzip', 'bz2', 'zip', 'xz', None}}, optional
encoding :... | pandas/io/common.py | def get_filepath_or_buffer(filepath_or_buffer, encoding=None,
compression=None, mode=None):
"""
If the filepath_or_buffer is a url, translate and return the buffer.
Otherwise passthrough.
Parameters
----------
filepath_or_buffer : a url, filepath (str, py.path.local o... | def get_filepath_or_buffer(filepath_or_buffer, encoding=None,
compression=None, mode=None):
"""
If the filepath_or_buffer is a url, translate and return the buffer.
Otherwise passthrough.
Parameters
----------
filepath_or_buffer : a url, filepath (str, py.path.local o... | [
"If",
"the",
"filepath_or_buffer",
"is",
"a",
"url",
"translate",
"and",
"return",
"the",
"buffer",
".",
"Otherwise",
"passthrough",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/io/common.py#L155-L209 | [
"def",
"get_filepath_or_buffer",
"(",
"filepath_or_buffer",
",",
"encoding",
"=",
"None",
",",
"compression",
"=",
"None",
",",
"mode",
"=",
"None",
")",
":",
"filepath_or_buffer",
"=",
"_stringify_path",
"(",
"filepath_or_buffer",
")",
"if",
"_is_url",
"(",
"fi... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | _infer_compression | Get the compression method for filepath_or_buffer. If compression='infer',
the inferred compression method is returned. Otherwise, the input
compression method is returned unchanged, unless it's invalid, in which
case an error is raised.
Parameters
----------
filepath_or_buffer :
a path... | pandas/io/common.py | def _infer_compression(filepath_or_buffer, compression):
"""
Get the compression method for filepath_or_buffer. If compression='infer',
the inferred compression method is returned. Otherwise, the input
compression method is returned unchanged, unless it's invalid, in which
case an error is raised.
... | def _infer_compression(filepath_or_buffer, compression):
"""
Get the compression method for filepath_or_buffer. If compression='infer',
the inferred compression method is returned. Otherwise, the input
compression method is returned unchanged, unless it's invalid, in which
case an error is raised.
... | [
"Get",
"the",
"compression",
"method",
"for",
"filepath_or_buffer",
".",
"If",
"compression",
"=",
"infer",
"the",
"inferred",
"compression",
"method",
"is",
"returned",
".",
"Otherwise",
"the",
"input",
"compression",
"method",
"is",
"returned",
"unchanged",
"unl... | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/io/common.py#L235-L286 | [
"def",
"_infer_compression",
"(",
"filepath_or_buffer",
",",
"compression",
")",
":",
"# No compression has been explicitly specified",
"if",
"compression",
"is",
"None",
":",
"return",
"None",
"# Infer compression",
"if",
"compression",
"==",
"'infer'",
":",
"# Convert a... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | _get_handle | Get file handle for given path/buffer and mode.
Parameters
----------
path_or_buf :
a path (str) or buffer
mode : str
mode to open path_or_buf with
encoding : str or None
compression : {'infer', 'gzip', 'bz2', 'zip', 'xz', None}, default None
If 'infer' and `filepath_or_... | pandas/io/common.py | def _get_handle(path_or_buf, mode, encoding=None, compression=None,
memory_map=False, is_text=True):
"""
Get file handle for given path/buffer and mode.
Parameters
----------
path_or_buf :
a path (str) or buffer
mode : str
mode to open path_or_buf with
encodi... | def _get_handle(path_or_buf, mode, encoding=None, compression=None,
memory_map=False, is_text=True):
"""
Get file handle for given path/buffer and mode.
Parameters
----------
path_or_buf :
a path (str) or buffer
mode : str
mode to open path_or_buf with
encodi... | [
"Get",
"file",
"handle",
"for",
"given",
"path",
"/",
"buffer",
"and",
"mode",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/io/common.py#L289-L410 | [
"def",
"_get_handle",
"(",
"path_or_buf",
",",
"mode",
",",
"encoding",
"=",
"None",
",",
"compression",
"=",
"None",
",",
"memory_map",
"=",
"False",
",",
"is_text",
"=",
"True",
")",
":",
"try",
":",
"from",
"s3fs",
"import",
"S3File",
"need_text_wrappin... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | _td_array_cmp | Wrap comparison operations to convert timedelta-like to timedelta64 | pandas/core/arrays/timedeltas.py | def _td_array_cmp(cls, op):
"""
Wrap comparison operations to convert timedelta-like to timedelta64
"""
opname = '__{name}__'.format(name=op.__name__)
nat_result = opname == '__ne__'
def wrapper(self, other):
if isinstance(other, (ABCDataFrame, ABCSeries, ABCIndexClass)):
re... | def _td_array_cmp(cls, op):
"""
Wrap comparison operations to convert timedelta-like to timedelta64
"""
opname = '__{name}__'.format(name=op.__name__)
nat_result = opname == '__ne__'
def wrapper(self, other):
if isinstance(other, (ABCDataFrame, ABCSeries, ABCIndexClass)):
re... | [
"Wrap",
"comparison",
"operations",
"to",
"convert",
"timedelta",
"-",
"like",
"to",
"timedelta64"
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/arrays/timedeltas.py#L56-L102 | [
"def",
"_td_array_cmp",
"(",
"cls",
",",
"op",
")",
":",
"opname",
"=",
"'__{name}__'",
".",
"format",
"(",
"name",
"=",
"op",
".",
"__name__",
")",
"nat_result",
"=",
"opname",
"==",
"'__ne__'",
"def",
"wrapper",
"(",
"self",
",",
"other",
")",
":",
... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | sequence_to_td64ns | Parameters
----------
array : list-like
copy : bool, default False
unit : str, default "ns"
The timedelta unit to treat integers as multiples of.
errors : {"raise", "coerce", "ignore"}, default "raise"
How to handle elements that cannot be converted to timedelta64[ns].
See ``... | pandas/core/arrays/timedeltas.py | def sequence_to_td64ns(data, copy=False, unit="ns", errors="raise"):
"""
Parameters
----------
array : list-like
copy : bool, default False
unit : str, default "ns"
The timedelta unit to treat integers as multiples of.
errors : {"raise", "coerce", "ignore"}, default "raise"
H... | def sequence_to_td64ns(data, copy=False, unit="ns", errors="raise"):
"""
Parameters
----------
array : list-like
copy : bool, default False
unit : str, default "ns"
The timedelta unit to treat integers as multiples of.
errors : {"raise", "coerce", "ignore"}, default "raise"
H... | [
"Parameters",
"----------",
"array",
":",
"list",
"-",
"like",
"copy",
":",
"bool",
"default",
"False",
"unit",
":",
"str",
"default",
"ns",
"The",
"timedelta",
"unit",
"to",
"treat",
"integers",
"as",
"multiples",
"of",
".",
"errors",
":",
"{",
"raise",
... | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/arrays/timedeltas.py#L854-L947 | [
"def",
"sequence_to_td64ns",
"(",
"data",
",",
"copy",
"=",
"False",
",",
"unit",
"=",
"\"ns\"",
",",
"errors",
"=",
"\"raise\"",
")",
":",
"inferred_freq",
"=",
"None",
"unit",
"=",
"parse_timedelta_unit",
"(",
"unit",
")",
"# Unwrap whatever we have into a np.... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | ints_to_td64ns | Convert an ndarray with integer-dtype to timedelta64[ns] dtype, treating
the integers as multiples of the given timedelta unit.
Parameters
----------
data : numpy.ndarray with integer-dtype
unit : str, default "ns"
The timedelta unit to treat integers as multiples of.
Returns
-----... | pandas/core/arrays/timedeltas.py | def ints_to_td64ns(data, unit="ns"):
"""
Convert an ndarray with integer-dtype to timedelta64[ns] dtype, treating
the integers as multiples of the given timedelta unit.
Parameters
----------
data : numpy.ndarray with integer-dtype
unit : str, default "ns"
The timedelta unit to treat... | def ints_to_td64ns(data, unit="ns"):
"""
Convert an ndarray with integer-dtype to timedelta64[ns] dtype, treating
the integers as multiples of the given timedelta unit.
Parameters
----------
data : numpy.ndarray with integer-dtype
unit : str, default "ns"
The timedelta unit to treat... | [
"Convert",
"an",
"ndarray",
"with",
"integer",
"-",
"dtype",
"to",
"timedelta64",
"[",
"ns",
"]",
"dtype",
"treating",
"the",
"integers",
"as",
"multiples",
"of",
"the",
"given",
"timedelta",
"unit",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/arrays/timedeltas.py#L950-L987 | [
"def",
"ints_to_td64ns",
"(",
"data",
",",
"unit",
"=",
"\"ns\"",
")",
":",
"copy_made",
"=",
"False",
"unit",
"=",
"unit",
"if",
"unit",
"is",
"not",
"None",
"else",
"\"ns\"",
"if",
"data",
".",
"dtype",
"!=",
"np",
".",
"int64",
":",
"# converting to... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | objects_to_td64ns | Convert a object-dtyped or string-dtyped array into an
timedelta64[ns]-dtyped array.
Parameters
----------
data : ndarray or Index
unit : str, default "ns"
The timedelta unit to treat integers as multiples of.
errors : {"raise", "coerce", "ignore"}, default "raise"
How to handle... | pandas/core/arrays/timedeltas.py | def objects_to_td64ns(data, unit="ns", errors="raise"):
"""
Convert a object-dtyped or string-dtyped array into an
timedelta64[ns]-dtyped array.
Parameters
----------
data : ndarray or Index
unit : str, default "ns"
The timedelta unit to treat integers as multiples of.
errors : ... | def objects_to_td64ns(data, unit="ns", errors="raise"):
"""
Convert a object-dtyped or string-dtyped array into an
timedelta64[ns]-dtyped array.
Parameters
----------
data : ndarray or Index
unit : str, default "ns"
The timedelta unit to treat integers as multiples of.
errors : ... | [
"Convert",
"a",
"object",
"-",
"dtyped",
"or",
"string",
"-",
"dtyped",
"array",
"into",
"an",
"timedelta64",
"[",
"ns",
"]",
"-",
"dtyped",
"array",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/arrays/timedeltas.py#L990-L1023 | [
"def",
"objects_to_td64ns",
"(",
"data",
",",
"unit",
"=",
"\"ns\"",
",",
"errors",
"=",
"\"raise\"",
")",
":",
"# coerce Index to np.ndarray, converting string-dtype if necessary",
"values",
"=",
"np",
".",
"array",
"(",
"data",
",",
"dtype",
"=",
"np",
".",
"o... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | TimedeltaArray._add_datetime_arraylike | Add DatetimeArray/Index or ndarray[datetime64] to TimedeltaArray. | pandas/core/arrays/timedeltas.py | def _add_datetime_arraylike(self, other):
"""
Add DatetimeArray/Index or ndarray[datetime64] to TimedeltaArray.
"""
if isinstance(other, np.ndarray):
# At this point we have already checked that dtype is datetime64
from pandas.core.arrays import DatetimeArray
... | def _add_datetime_arraylike(self, other):
"""
Add DatetimeArray/Index or ndarray[datetime64] to TimedeltaArray.
"""
if isinstance(other, np.ndarray):
# At this point we have already checked that dtype is datetime64
from pandas.core.arrays import DatetimeArray
... | [
"Add",
"DatetimeArray",
"/",
"Index",
"or",
"ndarray",
"[",
"datetime64",
"]",
"to",
"TimedeltaArray",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/arrays/timedeltas.py#L392-L402 | [
"def",
"_add_datetime_arraylike",
"(",
"self",
",",
"other",
")",
":",
"if",
"isinstance",
"(",
"other",
",",
"np",
".",
"ndarray",
")",
":",
"# At this point we have already checked that dtype is datetime64",
"from",
"pandas",
".",
"core",
".",
"arrays",
"import",
... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | TimedeltaArray.components | Return a dataframe of the components (days, hours, minutes,
seconds, milliseconds, microseconds, nanoseconds) of the Timedeltas.
Returns
-------
a DataFrame | pandas/core/arrays/timedeltas.py | def components(self):
"""
Return a dataframe of the components (days, hours, minutes,
seconds, milliseconds, microseconds, nanoseconds) of the Timedeltas.
Returns
-------
a DataFrame
"""
from pandas import DataFrame
columns = ['days', 'hours', 'm... | def components(self):
"""
Return a dataframe of the components (days, hours, minutes,
seconds, milliseconds, microseconds, nanoseconds) of the Timedeltas.
Returns
-------
a DataFrame
"""
from pandas import DataFrame
columns = ['days', 'hours', 'm... | [
"Return",
"a",
"dataframe",
"of",
"the",
"components",
"(",
"days",
"hours",
"minutes",
"seconds",
"milliseconds",
"microseconds",
"nanoseconds",
")",
"of",
"the",
"Timedeltas",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/arrays/timedeltas.py#L819-L845 | [
"def",
"components",
"(",
"self",
")",
":",
"from",
"pandas",
"import",
"DataFrame",
"columns",
"=",
"[",
"'days'",
",",
"'hours'",
",",
"'minutes'",
",",
"'seconds'",
",",
"'milliseconds'",
",",
"'microseconds'",
",",
"'nanoseconds'",
"]",
"hasnans",
"=",
"... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | register_writer | Add engine to the excel writer registry.io.excel.
You must use this method to integrate with ``to_excel``.
Parameters
----------
klass : ExcelWriter | pandas/io/excel/_util.py | def register_writer(klass):
"""
Add engine to the excel writer registry.io.excel.
You must use this method to integrate with ``to_excel``.
Parameters
----------
klass : ExcelWriter
"""
if not callable(klass):
raise ValueError("Can only register callables as engines")
engine... | def register_writer(klass):
"""
Add engine to the excel writer registry.io.excel.
You must use this method to integrate with ``to_excel``.
Parameters
----------
klass : ExcelWriter
"""
if not callable(klass):
raise ValueError("Can only register callables as engines")
engine... | [
"Add",
"engine",
"to",
"the",
"excel",
"writer",
"registry",
".",
"io",
".",
"excel",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/io/excel/_util.py#L10-L23 | [
"def",
"register_writer",
"(",
"klass",
")",
":",
"if",
"not",
"callable",
"(",
"klass",
")",
":",
"raise",
"ValueError",
"(",
"\"Can only register callables as engines\"",
")",
"engine_name",
"=",
"klass",
".",
"engine",
"_writers",
"[",
"engine_name",
"]",
"="... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | _excel2num | Convert Excel column name like 'AB' to 0-based column index.
Parameters
----------
x : str
The Excel column name to convert to a 0-based column index.
Returns
-------
num : int
The column index corresponding to the name.
Raises
------
ValueError
Part of the... | pandas/io/excel/_util.py | def _excel2num(x):
"""
Convert Excel column name like 'AB' to 0-based column index.
Parameters
----------
x : str
The Excel column name to convert to a 0-based column index.
Returns
-------
num : int
The column index corresponding to the name.
Raises
------
... | def _excel2num(x):
"""
Convert Excel column name like 'AB' to 0-based column index.
Parameters
----------
x : str
The Excel column name to convert to a 0-based column index.
Returns
-------
num : int
The column index corresponding to the name.
Raises
------
... | [
"Convert",
"Excel",
"column",
"name",
"like",
"AB",
"to",
"0",
"-",
"based",
"column",
"index",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/io/excel/_util.py#L57-L86 | [
"def",
"_excel2num",
"(",
"x",
")",
":",
"index",
"=",
"0",
"for",
"c",
"in",
"x",
".",
"upper",
"(",
")",
".",
"strip",
"(",
")",
":",
"cp",
"=",
"ord",
"(",
"c",
")",
"if",
"cp",
"<",
"ord",
"(",
"\"A\"",
")",
"or",
"cp",
">",
"ord",
"(... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
train | _range2cols | Convert comma separated list of column names and ranges to indices.
Parameters
----------
areas : str
A string containing a sequence of column ranges (or areas).
Returns
-------
cols : list
A list of 0-based column indices.
Examples
--------
>>> _range2cols('A:E')
... | pandas/io/excel/_util.py | def _range2cols(areas):
"""
Convert comma separated list of column names and ranges to indices.
Parameters
----------
areas : str
A string containing a sequence of column ranges (or areas).
Returns
-------
cols : list
A list of 0-based column indices.
Examples
... | def _range2cols(areas):
"""
Convert comma separated list of column names and ranges to indices.
Parameters
----------
areas : str
A string containing a sequence of column ranges (or areas).
Returns
-------
cols : list
A list of 0-based column indices.
Examples
... | [
"Convert",
"comma",
"separated",
"list",
"of",
"column",
"names",
"and",
"ranges",
"to",
"indices",
"."
] | pandas-dev/pandas | python | https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/io/excel/_util.py#L89-L119 | [
"def",
"_range2cols",
"(",
"areas",
")",
":",
"cols",
"=",
"[",
"]",
"for",
"rng",
"in",
"areas",
".",
"split",
"(",
"\",\"",
")",
":",
"if",
"\":\"",
"in",
"rng",
":",
"rng",
"=",
"rng",
".",
"split",
"(",
"\":\"",
")",
"cols",
".",
"extend",
... | 9feb3ad92cc0397a04b665803a49299ee7aa1037 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.