INSTRUCTION stringlengths 1 8.43k | RESPONSE stringlengths 75 104k |
|---|---|
Convert usecols into a compatible format for parsing in parsers. py. | def _maybe_convert_usecols(usecols):
"""
Convert `usecols` into a compatible format for parsing in `parsers.py`.
Parameters
----------
usecols : object
The use-columns object to potentially convert.
Returns
-------
converted : object
The compatible format of `usecols`.
... |
Forward fill blank entries in row but only inside the same parent index. | def _fill_mi_header(row, control_row):
"""Forward fill blank entries in row but only inside the same parent index.
Used for creating headers in Multiindex.
Parameters
----------
row : list
List of items in a single row.
control_row : list of bool
Helps to determine if particular... |
Pop the header name for MultiIndex parsing. | def _pop_header_name(row, index_col):
"""
Pop the header name for MultiIndex parsing.
Parameters
----------
row : list
The data row to parse for the header name.
index_col : int, list
The index columns for our data. Assumed to be non-null.
Returns
-------
header_nam... |
Ensure that we are grabbing the correct scope. | def _ensure_scope(level, global_dict=None, local_dict=None, resolvers=(),
target=None, **kwargs):
"""Ensure that we are grabbing the correct scope."""
return Scope(level + 1, global_dict=global_dict, local_dict=local_dict,
resolvers=resolvers, target=target) |
Replace a number with its hexadecimal representation. Used to tag temporary variables with their calling scope s id. | def _replacer(x):
"""Replace a number with its hexadecimal representation. Used to tag
temporary variables with their calling scope's id.
"""
# get the hex repr of the binary char and remove 0x and pad by pad_size
# zeros
try:
hexin = ord(x)
except TypeError:
# bytes literals... |
Return the padded hexadecimal id of obj. | def _raw_hex_id(obj):
"""Return the padded hexadecimal id of ``obj``."""
# interpret as a pointer since that's what really what id returns
packed = struct.pack('@P', id(obj))
return ''.join(map(_replacer, packed)) |
Return a prettier version of obj | def _get_pretty_string(obj):
"""Return a prettier version of obj
Parameters
----------
obj : object
Object to pretty print
Returns
-------
s : str
Pretty print object repr
"""
sio = StringIO()
pprint.pprint(obj, stream=sio)
return sio.getvalue() |
Resolve a variable name in a possibly local context | def resolve(self, key, is_local):
"""Resolve a variable name in a possibly local context
Parameters
----------
key : str
A variable name
is_local : bool
Flag indicating whether the variable is local or not (prefixed with
the '@' symbol)
... |
Replace a variable name with a potentially new value. | def swapkey(self, old_key, new_key, new_value=None):
"""Replace a variable name, with a potentially new value.
Parameters
----------
old_key : str
Current variable name to replace
new_key : str
New variable name to replace `old_key` with
new_value... |
Get specifically scoped variables from a list of stack frames. | def _get_vars(self, stack, scopes):
"""Get specifically scoped variables from a list of stack frames.
Parameters
----------
stack : list
A list of stack frames as returned by ``inspect.stack()``
scopes : sequence of strings
A sequence containing valid sta... |
Update the current scope by going back level levels. | def update(self, level):
"""Update the current scope by going back `level` levels.
Parameters
----------
level : int or None, optional, default None
"""
sl = level + 1
# add sl frames to the scope starting with the
# most distant and overwriting with mor... |
Add a temporary variable to the scope. | def add_tmp(self, value):
"""Add a temporary variable to the scope.
Parameters
----------
value : object
An arbitrary object to be assigned to a temporary variable.
Returns
-------
name : basestring
The name of the temporary variable crea... |
Return the full scope for use with passing to engines transparently as a mapping. | def full_scope(self):
"""Return the full scope for use with passing to engines transparently
as a mapping.
Returns
-------
vars : DeepChainMap
All variables in this scope.
"""
maps = [self.temps] + self.resolvers.maps + self.scope.maps
return ... |
Read SAS files stored as either XPORT or SAS7BDAT format files. | def read_sas(filepath_or_buffer, format=None, index=None, encoding=None,
chunksize=None, iterator=False):
"""
Read SAS files stored as either XPORT or SAS7BDAT format files.
Parameters
----------
filepath_or_buffer : string or file-like object
Path to the SAS file.
format :... |
Install the scalar coercion methods. | def _coerce_method(converter):
"""
Install the scalar coercion methods.
"""
def wrapper(self):
if len(self) == 1:
return converter(self.iloc[0])
raise TypeError("cannot convert the series to "
"{0}".format(str(converter)))
wrapper.__name__ = "__{... |
Derive the _data and index attributes of a new Series from a dictionary input. | def _init_dict(self, data, index=None, dtype=None):
"""
Derive the "_data" and "index" attributes of a new Series from a
dictionary input.
Parameters
----------
data : dict or dict-like
Data used to populate the new Series
index : Index or index-like,... |
Construct Series from array. | def from_array(cls, arr, index=None, name=None, dtype=None, copy=False,
fastpath=False):
"""
Construct Series from array.
.. deprecated :: 0.23.0
Use pd.Series(..) constructor instead.
"""
warnings.warn("'from_array' is deprecated and will be remov... |
Override generic we want to set the _typ here. | def _set_axis(self, axis, labels, fastpath=False):
"""
Override generic, we want to set the _typ here.
"""
if not fastpath:
labels = ensure_index(labels)
is_all_dates = labels.is_all_dates
if is_all_dates:
if not isinstance(labels,
... |
Return object Series which contains boxed values. | def asobject(self):
"""
Return object Series which contains boxed values.
.. deprecated :: 0.23.0
Use ``astype(object)`` instead.
*this is an internal non-public method*
"""
warnings.warn("'asobject' is deprecated. Use 'astype(object)'"
... |
Return selected slices of an array along given axis as a Series. | def compress(self, condition, *args, **kwargs):
"""
Return selected slices of an array along given axis as a Series.
.. deprecated:: 0.24.0
See Also
--------
numpy.ndarray.compress
"""
msg = ("Series.compress(condition) is deprecated. "
"U... |
Return the * integer * indices of the elements that are non - zero. | def nonzero(self):
"""
Return the *integer* indices of the elements that are non-zero.
.. deprecated:: 0.24.0
Please use .to_numpy().nonzero() as a replacement.
This method is equivalent to calling `numpy.nonzero` on the
series data. For compatibility with NumPy, the... |
Create a new view of the Series. | def view(self, dtype=None):
"""
Create a new view of the Series.
This function will return a new Series with a view of the same
underlying values in memory, optionally reinterpreted with a new data
type. The new data type must preserve the same size in bytes as to not
ca... |
Return the i - th value or values in the Series by location. | def _ixs(self, i, axis=0):
"""
Return the i-th value or values in the Series by location.
Parameters
----------
i : int, slice, or sequence of integers
Returns
-------
scalar (int) or Series (slice, sequence)
"""
try:
# dispa... |
Repeat elements of a Series. | def repeat(self, repeats, axis=None):
"""
Repeat elements of a Series.
Returns a new Series where each element of the current Series
is repeated consecutively a given number of times.
Parameters
----------
repeats : int or array of ints
The number of... |
Generate a new DataFrame or Series with the index reset. | def reset_index(self, level=None, drop=False, name=None, inplace=False):
"""
Generate a new DataFrame or Series with the index reset.
This is useful when the index needs to be treated as a column, or
when the index is meaningless and needs to be reset to the default
before anoth... |
Render a string representation of the Series. | def to_string(self, buf=None, na_rep='NaN', float_format=None, header=True,
index=True, length=False, dtype=False, name=False,
max_rows=None):
"""
Render a string representation of the Series.
Parameters
----------
buf : StringIO-like, optiona... |
Convert Series to { label - > value } dict or dict - like object. | def to_dict(self, into=dict):
"""
Convert Series to {label -> value} dict or dict-like object.
Parameters
----------
into : class, default dict
The collections.abc.Mapping subclass to use as the return
object. Can be the actual class or an empty
... |
Convert Series to DataFrame. | def to_frame(self, name=None):
"""
Convert Series to DataFrame.
Parameters
----------
name : object, default None
The passed name should substitute for the series name (if it has
one).
Returns
-------
DataFrame
DataFra... |
Convert Series to SparseSeries. | def to_sparse(self, kind='block', fill_value=None):
"""
Convert Series to SparseSeries.
Parameters
----------
kind : {'block', 'integer'}, default 'block'
fill_value : float, defaults to NaN (missing)
Value to use for filling NaN values.
Returns
... |
Set the Series name. | def _set_name(self, name, inplace=False):
"""
Set the Series name.
Parameters
----------
name : str
inplace : bool
whether to modify `self` directly or return a copy
"""
inplace = validate_bool_kwarg(inplace, 'inplace')
ser = self if i... |
Return number of non - NA/ null observations in the Series. | def count(self, level=None):
"""
Return number of non-NA/null observations in the Series.
Parameters
----------
level : int or level name, default None
If the axis is a MultiIndex (hierarchical), count along a
particular level, collapsing into a smaller S... |
Return Series with duplicate values removed. | def drop_duplicates(self, keep='first', inplace=False):
"""
Return Series with duplicate values removed.
Parameters
----------
keep : {'first', 'last', ``False``}, default 'first'
- 'first' : Drop duplicates except for the first occurrence.
- 'last' : Dro... |
Return the row label of the minimum value. | def idxmin(self, axis=0, skipna=True, *args, **kwargs):
"""
Return the row label of the minimum value.
If multiple values equal the minimum, the first row label with that
value is returned.
Parameters
----------
skipna : bool, default True
Exclude NA... |
Return the row label of the maximum value. | def idxmax(self, axis=0, skipna=True, *args, **kwargs):
"""
Return the row label of the maximum value.
If multiple values equal the maximum, the first row label with that
value is returned.
Parameters
----------
skipna : bool, default True
Exclude NA... |
Round each value in a Series to the given number of decimals. | def round(self, decimals=0, *args, **kwargs):
"""
Round each value in a Series to the given number of decimals.
Parameters
----------
decimals : int
Number of decimal places to round to (default: 0).
If decimals is negative, it specifies the number of
... |
Return value at the given quantile. | def quantile(self, q=0.5, interpolation='linear'):
"""
Return value at the given quantile.
Parameters
----------
q : float or array-like, default 0.5 (50% quantile)
0 <= q <= 1, the quantile(s) to compute.
interpolation : {'linear', 'lower', 'higher', 'midpoi... |
Compute correlation with other Series excluding missing values. | def corr(self, other, method='pearson', min_periods=None):
"""
Compute correlation with `other` Series, excluding missing values.
Parameters
----------
other : Series
Series with which to compute the correlation.
method : {'pearson', 'kendall', 'spearman'} or... |
Compute covariance with Series excluding missing values. | def cov(self, other, min_periods=None):
"""
Compute covariance with Series, excluding missing values.
Parameters
----------
other : Series
Series with which to compute the covariance.
min_periods : int, optional
Minimum number of observations need... |
First discrete difference of element. | def diff(self, periods=1):
"""
First discrete difference of element.
Calculates the difference of a Series element compared with another
element in the Series (default is element in previous row).
Parameters
----------
periods : int, default 1
Period... |
Compute the dot product between the Series and the columns of other. | def dot(self, other):
"""
Compute the dot product between the Series and the columns of other.
This method computes the dot product between the Series and another
one, or the Series and each columns of a DataFrame, or the Series and
each columns of an array.
It can also... |
Concatenate two or more Series. | def append(self, to_append, ignore_index=False, verify_integrity=False):
"""
Concatenate two or more Series.
Parameters
----------
to_append : Series or list/tuple of Series
Series to append with self.
ignore_index : bool, default False
If True, d... |
Perform generic binary operation with optional fill value. | def _binop(self, other, func, level=None, fill_value=None):
"""
Perform generic binary operation with optional fill value.
Parameters
----------
other : Series
func : binary operator
fill_value : float or object
Value to substitute for NA/null values.... |
Combine the Series with a Series or scalar according to func. | def combine(self, other, func, fill_value=None):
"""
Combine the Series with a Series or scalar according to `func`.
Combine the Series and `other` using `func` to perform elementwise
selection for combined Series.
`fill_value` is assumed when value is missing at some index
... |
Combine Series values choosing the calling Series s values first. | def combine_first(self, other):
"""
Combine Series values, choosing the calling Series's values first.
Parameters
----------
other : Series
The value(s) to be combined with the `Series`.
Returns
-------
Series
The result of combin... |
Modify Series in place using non - NA values from passed Series. Aligns on index. | def update(self, other):
"""
Modify Series in place using non-NA values from passed
Series. Aligns on index.
Parameters
----------
other : Series
Examples
--------
>>> s = pd.Series([1, 2, 3])
>>> s.update(pd.Series([4, 5, 6]))
>>... |
Sort by the values. | def sort_values(self, axis=0, ascending=True, inplace=False,
kind='quicksort', na_position='last'):
"""
Sort by the values.
Sort a Series in ascending or descending order by some
criterion.
Parameters
----------
axis : {0 or 'index'}, default... |
Sort Series by index labels. | def sort_index(self, axis=0, level=None, ascending=True, inplace=False,
kind='quicksort', na_position='last', sort_remaining=True):
"""
Sort Series by index labels.
Returns a new Series sorted by label if `inplace` argument is
``False``, otherwise updates the original... |
Override ndarray. argsort. Argsorts the value omitting NA/ null values and places the result in the same locations as the non - NA values. | def argsort(self, axis=0, kind='quicksort', order=None):
"""
Override ndarray.argsort. Argsorts the value, omitting NA/null values,
and places the result in the same locations as the non-NA values.
Parameters
----------
axis : int
Has no effect but is accepte... |
Return the largest n elements. | def nlargest(self, n=5, keep='first'):
"""
Return the largest `n` elements.
Parameters
----------
n : int, default 5
Return this many descending sorted values.
keep : {'first', 'last', 'all'}, default 'first'
When there are duplicate values that c... |
Return the smallest n elements. | def nsmallest(self, n=5, keep='first'):
"""
Return the smallest `n` elements.
Parameters
----------
n : int, default 5
Return this many ascending sorted values.
keep : {'first', 'last', 'all'}, default 'first'
When there are duplicate values that ... |
Swap levels i and j in a MultiIndex. | def swaplevel(self, i=-2, j=-1, copy=True):
"""
Swap levels i and j in a MultiIndex.
Parameters
----------
i, j : int, str (can be mixed)
Level of index to be swapped. Can pass level name as string.
Returns
-------
Series
Series w... |
Rearrange index levels using input order. | def reorder_levels(self, order):
"""
Rearrange index levels using input order.
May not drop or duplicate levels.
Parameters
----------
order : list of int representing new level order
(reference level by number or key)
Returns
-------
... |
Map values of Series according to input correspondence. | def map(self, arg, na_action=None):
"""
Map values of Series according to input correspondence.
Used for substituting each value in a Series with another value,
that may be derived from a function, a ``dict`` or
a :class:`Series`.
Parameters
----------
a... |
Invoke function on values of Series. | def apply(self, func, convert_dtype=True, args=(), **kwds):
"""
Invoke function on values of Series.
Can be ufunc (a NumPy function that applies to the entire Series)
or a Python function that only works on single values.
Parameters
----------
func : function
... |
Perform a reduction operation. | def _reduce(self, op, name, axis=0, skipna=True, numeric_only=None,
filter_type=None, **kwds):
"""
Perform a reduction operation.
If we have an ndarray as a value, then simply perform the operation,
otherwise delegate to the object.
"""
delegate = self._v... |
Alter Series index labels or name. | def rename(self, index=None, **kwargs):
"""
Alter Series index labels or name.
Function / dict values must be unique (1-to-1). Labels not contained in
a dict / Series will be left as-is. Extra labels listed don't throw an
error.
Alternatively, change ``Series.name`` wit... |
Conform Series to new index with optional filling logic. | def reindex_axis(self, labels, axis=0, **kwargs):
"""
Conform Series to new index with optional filling logic.
.. deprecated:: 0.21.0
Use ``Series.reindex`` instead.
"""
# for compatibility with higher dims
if axis != 0:
raise ValueError("cannot r... |
Return the memory usage of the Series. | def memory_usage(self, index=True, deep=False):
"""
Return the memory usage of the Series.
The memory usage can optionally include the contribution of
the index and of elements of `object` dtype.
Parameters
----------
index : bool, default True
Speci... |
Check whether values are contained in Series. | def isin(self, values):
"""
Check whether `values` are contained in Series.
Return a boolean Series showing whether each element in the Series
matches an element in the passed sequence of `values` exactly.
Parameters
----------
values : set or list-like
... |
Return boolean Series equivalent to left < = series < = right. | def between(self, left, right, inclusive=True):
"""
Return boolean Series equivalent to left <= series <= right.
This function returns a boolean vector containing `True` wherever the
corresponding Series element is between the boundary values `left` and
`right`. NA values are tr... |
Read CSV file. | def from_csv(cls, path, sep=',', parse_dates=True, header=None,
index_col=0, encoding=None, infer_datetime_format=False):
"""
Read CSV file.
.. deprecated:: 0.21.0
Use :func:`pandas.read_csv` instead.
It is preferable to use the more powerful :func:`pandas.... |
Return a new Series with missing values removed. | def dropna(self, axis=0, inplace=False, **kwargs):
"""
Return a new Series with missing values removed.
See the :ref:`User Guide <missing_data>` for more on which values are
considered missing, and how to work with missing data.
Parameters
----------
axis : {0 o... |
Return Series without null values. | def valid(self, inplace=False, **kwargs):
"""
Return Series without null values.
.. deprecated:: 0.23.0
Use :meth:`Series.dropna` instead.
"""
warnings.warn("Method .valid will be removed in a future version. "
"Use .dropna instead.", FutureWarn... |
Cast to DatetimeIndex of Timestamps at * beginning * of period. | def to_timestamp(self, freq=None, how='start', copy=True):
"""
Cast to DatetimeIndex of Timestamps, at *beginning* of period.
Parameters
----------
freq : str, default frequency of PeriodIndex
Desired frequency.
how : {'s', 'e', 'start', 'end'}
Co... |
Convert Series from DatetimeIndex to PeriodIndex with desired frequency ( inferred from index if not passed ). | def to_period(self, freq=None, copy=True):
"""
Convert Series from DatetimeIndex to PeriodIndex with desired
frequency (inferred from index if not passed).
Parameters
----------
freq : str, default None
Frequency associated with the PeriodIndex.
copy ... |
Convert argument to a numeric type. | def to_numeric(arg, errors='raise', downcast=None):
"""
Convert argument to a numeric type.
The default return dtype is `float64` or `int64`
depending on the data supplied. Use the `downcast` parameter
to obtain other dtypes.
Please note that precision loss may occur if really large numbers
... |
Create a 0 - dim ndarray containing the fill value | def _get_fill(arr: ABCSparseArray) -> np.ndarray:
"""
Create a 0-dim ndarray containing the fill value
Parameters
----------
arr : SparseArray
Returns
-------
fill_value : ndarray
0-dim ndarray with just the fill value.
Notes
-----
coerce fill_value to arr dtype if... |
Perform a binary operation between two arrays. | def _sparse_array_op(
left: ABCSparseArray,
right: ABCSparseArray,
op: Callable,
name: str
) -> Any:
"""
Perform a binary operation between two arrays.
Parameters
----------
left : Union[SparseArray, ndarray]
right : Union[SparseArray, ndarray]
op : Callable
... |
wrap op result to have correct dtype | def _wrap_result(name, data, sparse_index, fill_value, dtype=None):
"""
wrap op result to have correct dtype
"""
if name.startswith('__'):
# e.g. __eq__ --> eq
name = name[2:-2]
if name in ('eq', 'ne', 'lt', 'gt', 'le', 'ge'):
dtype = np.bool
fill_value = lib.item_from_... |
array must be SparseSeries or SparseArray | def _maybe_to_sparse(array):
"""
array must be SparseSeries or SparseArray
"""
if isinstance(array, ABCSparseSeries):
array = array.values.copy()
return array |
return an ndarray for our input in a platform independent manner | def _sanitize_values(arr):
"""
return an ndarray for our input,
in a platform independent manner
"""
if hasattr(arr, 'values'):
arr = arr.values
else:
# scalar
if is_scalar(arr):
arr = [arr]
# ndarray
if isinstance(arr, np.ndarray):
... |
Convert ndarray to sparse format | def make_sparse(arr, kind='block', fill_value=None, dtype=None, copy=False):
"""
Convert ndarray to sparse format
Parameters
----------
arr : ndarray
kind : {'block', 'integer'}
fill_value : NaN or another value
dtype : np.dtype, optional
copy : bool, default False
Returns
... |
The percent of non - fill_value points as decimal. | def density(self):
"""
The percent of non- ``fill_value`` points, as decimal.
Examples
--------
>>> s = SparseArray([0, 0, 1, 1, 1], fill_value=0)
>>> s.density
0.6
"""
r = float(self.sp_index.npoints) / float(self.sp_index.length)
return ... |
Fill missing values with value. | def fillna(self, value=None, method=None, limit=None):
"""
Fill missing values with `value`.
Parameters
----------
value : scalar, optional
method : str, optional
.. warning::
Using 'method' will result in high memory use,
as a... |
Get the location of the first missing value. | def _first_fill_value_loc(self):
"""
Get the location of the first missing value.
Returns
-------
int
"""
if len(self) == 0 or self.sp_index.npoints == len(self):
return -1
indices = self.sp_index.to_int_index().indices
if not len(ind... |
Returns a Series containing counts of unique values. | def value_counts(self, dropna=True):
"""
Returns a Series containing counts of unique values.
Parameters
----------
dropna : boolean, default True
Don't include counts of NaN, even if NaN is in sp_values.
Returns
-------
counts : Series
... |
Change the dtype of a SparseArray. | def astype(self, dtype=None, copy=True):
"""
Change the dtype of a SparseArray.
The output will always be a SparseArray. To convert to a dense
ndarray with a certain dtype, use :meth:`numpy.asarray`.
Parameters
----------
dtype : np.dtype or ExtensionDtype
... |
Map categories using input correspondence ( dict Series or function ). | def map(self, mapper):
"""
Map categories using input correspondence (dict, Series, or function).
Parameters
----------
mapper : dict, Series, callable
The correspondence from old values to new.
Returns
-------
SparseArray
The out... |
Tests whether all elements evaluate True | def all(self, axis=None, *args, **kwargs):
"""
Tests whether all elements evaluate True
Returns
-------
all : bool
See Also
--------
numpy.all
"""
nv.validate_all(args, kwargs)
values = self.sp_values
if len(values) != l... |
Tests whether at least one of elements evaluate True | def any(self, axis=0, *args, **kwargs):
"""
Tests whether at least one of elements evaluate True
Returns
-------
any : bool
See Also
--------
numpy.any
"""
nv.validate_any(args, kwargs)
values = self.sp_values
if len(val... |
Sum of non - NA/ null values | def sum(self, axis=0, *args, **kwargs):
"""
Sum of non-NA/null values
Returns
-------
sum : float
"""
nv.validate_sum(args, kwargs)
valid_vals = self._valid_sp_values
sp_sum = valid_vals.sum()
if self._null_fill_value:
return s... |
Cumulative sum of non - NA/ null values. | def cumsum(self, axis=0, *args, **kwargs):
"""
Cumulative sum of non-NA/null values.
When performing the cumulative summation, any non-NA/null values will
be skipped. The resulting SparseArray will preserve the locations of
NaN values, but the fill value will be `np.nan` regardl... |
Mean of non - NA/ null values | def mean(self, axis=0, *args, **kwargs):
"""
Mean of non-NA/null values
Returns
-------
mean : float
"""
nv.validate_mean(args, kwargs)
valid_vals = self._valid_sp_values
sp_sum = valid_vals.sum()
ct = len(valid_vals)
if self._nul... |
Tokenize a Python source code string. | def tokenize_string(source):
"""Tokenize a Python source code string.
Parameters
----------
source : str
A Python source code string
"""
line_reader = StringIO(source).readline
token_generator = tokenize.generate_tokens(line_reader)
# Loop over all tokens till a backtick (`) is... |
Replace & with and and | with or so that bitwise precedence is changed to boolean precedence. | def _replace_booleans(tok):
"""Replace ``&`` with ``and`` and ``|`` with ``or`` so that bitwise
precedence is changed to boolean precedence.
Parameters
----------
tok : tuple of int, str
ints correspond to the all caps constants in the tokenize module
Returns
-------
t : tuple ... |
Replace local variables with a syntactically valid name. | def _replace_locals(tok):
"""Replace local variables with a syntactically valid name.
Parameters
----------
tok : tuple of int, str
ints correspond to the all caps constants in the tokenize module
Returns
-------
t : tuple of int, str
Either the input or token or the replac... |
Clean up a column name if surrounded by backticks. | def _clean_spaces_backtick_quoted_names(tok):
"""Clean up a column name if surrounded by backticks.
Backtick quoted string are indicated by a certain tokval value. If a string
is a backtick quoted token it will processed by
:func:`_remove_spaces_column_name` so that the parser can find this
string ... |
Compose a collection of tokenization functions | def _preparse(source, f=_compose(_replace_locals, _replace_booleans,
_rewrite_assign,
_clean_spaces_backtick_quoted_names)):
"""Compose a collection of tokenization functions
Parameters
----------
source : str
A Python source cod... |
Filter out AST nodes that are subclasses of superclass. | def _filter_nodes(superclass, all_nodes=_all_nodes):
"""Filter out AST nodes that are subclasses of ``superclass``."""
node_names = (node.__name__ for node in all_nodes
if issubclass(node, superclass))
return frozenset(node_names) |
Return a function that raises a NotImplementedError with a passed node name. | def _node_not_implemented(node_name, cls):
"""Return a function that raises a NotImplementedError with a passed node
name.
"""
def f(self, *args, **kwargs):
raise NotImplementedError("{name!r} nodes are not "
"implemented".format(name=node_name))
return f |
Decorator to disallow certain nodes from parsing. Raises a NotImplementedError instead. | def disallow(nodes):
"""Decorator to disallow certain nodes from parsing. Raises a
NotImplementedError instead.
Returns
-------
disallowed : callable
"""
def disallowed(cls):
cls.unsupported_nodes = ()
for node in nodes:
new_method = _node_not_implemented(node, c... |
Return a function to create an op class with its symbol already passed. | def _op_maker(op_class, op_symbol):
"""Return a function to create an op class with its symbol already passed.
Returns
-------
f : callable
"""
def f(self, node, *args, **kwargs):
"""Return a partial function with an Op subclass with an operator
already passed.
Returns... |
Decorator to add default implementation of ops. | def add_ops(op_classes):
"""Decorator to add default implementation of ops."""
def f(cls):
for op_attr_name, op_class in op_classes.items():
ops = getattr(cls, '{name}_ops'.format(name=op_attr_name))
ops_map = getattr(cls, '{name}_op_nodes_map'.format(
name=op_att... |
Get the names in an expression | def names(self):
"""Get the names in an expression"""
if is_term(self.terms):
return frozenset([self.terms.name])
return frozenset(term.name for term in com.flatten(self.terms)) |
return a boolean whether I can attempt conversion to a TimedeltaIndex | def _is_convertible_to_index(other):
"""
return a boolean whether I can attempt conversion to a TimedeltaIndex
"""
if isinstance(other, TimedeltaIndex):
return True
elif (len(other) > 0 and
other.inferred_type not in ('floating', 'mixed-integer', 'integer',
... |
Return a fixed frequency TimedeltaIndex with day as the default frequency | def timedelta_range(start=None, end=None, periods=None, freq=None,
name=None, closed=None):
"""
Return a fixed frequency TimedeltaIndex, with day as the default
frequency
Parameters
----------
start : string or timedelta-like, default None
Left bound for generating t... |
Returns a FrozenList with other concatenated to the end of self. | def union(self, other):
"""
Returns a FrozenList with other concatenated to the end of self.
Parameters
----------
other : array-like
The array-like whose elements we are concatenating.
Returns
-------
diff : FrozenList
The collec... |
Returns a FrozenList with elements from other removed from self. | def difference(self, other):
"""
Returns a FrozenList with elements from other removed from self.
Parameters
----------
other : array-like
The array-like whose elements we are removing self.
Returns
-------
diff : FrozenList
The c... |
Find indices to insert value so as to maintain order. | def searchsorted(self, value, side="left", sorter=None):
"""
Find indices to insert `value` so as to maintain order.
For full documentation, see `numpy.searchsorted`
See Also
--------
numpy.searchsorted : Equivalent function.
"""
# We are much more perf... |
Segregate Series based on type and coerce into matrices. | def arrays_to_mgr(arrays, arr_names, index, columns, dtype=None):
"""
Segregate Series based on type and coerce into matrices.
Needs to handle a lot of exceptional cases.
"""
# figure out the index, if necessary
if index is None:
index = extract_index(arrays)
else:
index = e... |
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