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19,400 | pandas-dev/pandas | pandas/core/indexes/base.py | Index.to_series | def to_series(self, index=None, name=None):
"""
Create a Series with both index and values equal to the index keys
useful with map for returning an indexer based on an index.
Parameters
----------
index : Index, optional
index of resulting Series. If None, de... | python | def to_series(self, index=None, name=None):
"""
Create a Series with both index and values equal to the index keys
useful with map for returning an indexer based on an index.
Parameters
----------
index : Index, optional
index of resulting Series. If None, de... | [
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19,401 | pandas-dev/pandas | pandas/core/indexes/base.py | Index.to_frame | def to_frame(self, index=True, name=None):
"""
Create a DataFrame with a column containing the Index.
.. versionadded:: 0.24.0
Parameters
----------
index : boolean, default True
Set the index of the returned DataFrame as the original Index.
name : ... | python | def to_frame(self, index=True, name=None):
"""
Create a DataFrame with a column containing the Index.
.. versionadded:: 0.24.0
Parameters
----------
index : boolean, default True
Set the index of the returned DataFrame as the original Index.
name : ... | [
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19,402 | pandas-dev/pandas | pandas/core/indexes/base.py | Index._validate_names | def _validate_names(self, name=None, names=None, deep=False):
"""
Handles the quirks of having a singular 'name' parameter for general
Index and plural 'names' parameter for MultiIndex.
"""
from copy import deepcopy
if names is not None and name is not None:
r... | python | def _validate_names(self, name=None, names=None, deep=False):
"""
Handles the quirks of having a singular 'name' parameter for general
Index and plural 'names' parameter for MultiIndex.
"""
from copy import deepcopy
if names is not None and name is not None:
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19,403 | pandas-dev/pandas | pandas/core/indexes/base.py | Index.set_names | def set_names(self, names, level=None, inplace=False):
"""
Set Index or MultiIndex name.
Able to set new names partially and by level.
Parameters
----------
names : label or list of label
Name(s) to set.
level : int, label or list of int or label, op... | python | def set_names(self, names, level=None, inplace=False):
"""
Set Index or MultiIndex name.
Able to set new names partially and by level.
Parameters
----------
names : label or list of label
Name(s) to set.
level : int, label or list of int or label, op... | [
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19,404 | pandas-dev/pandas | pandas/core/indexes/base.py | Index.rename | def rename(self, name, inplace=False):
"""
Alter Index or MultiIndex name.
Able to set new names without level. Defaults to returning new index.
Length of names must match number of levels in MultiIndex.
Parameters
----------
name : label or list of labels
... | python | def rename(self, name, inplace=False):
"""
Alter Index or MultiIndex name.
Able to set new names without level. Defaults to returning new index.
Length of names must match number of levels in MultiIndex.
Parameters
----------
name : label or list of labels
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19,405 | pandas-dev/pandas | pandas/core/indexes/base.py | Index._validate_index_level | def _validate_index_level(self, level):
"""
Validate index level.
For single-level Index getting level number is a no-op, but some
verification must be done like in MultiIndex.
"""
if isinstance(level, int):
if level < 0 and level != -1:
rais... | python | def _validate_index_level(self, level):
"""
Validate index level.
For single-level Index getting level number is a no-op, but some
verification must be done like in MultiIndex.
"""
if isinstance(level, int):
if level < 0 and level != -1:
rais... | [
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19,406 | pandas-dev/pandas | pandas/core/indexes/base.py | Index.sortlevel | def sortlevel(self, level=None, ascending=True, sort_remaining=None):
"""
For internal compatibility with with the Index API.
Sort the Index. This is for compat with MultiIndex
Parameters
----------
ascending : boolean, default True
False to sort in descendi... | python | def sortlevel(self, level=None, ascending=True, sort_remaining=None):
"""
For internal compatibility with with the Index API.
Sort the Index. This is for compat with MultiIndex
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ascending : boolean, default True
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19,407 | pandas-dev/pandas | pandas/core/indexes/base.py | Index._isnan | def _isnan(self):
"""
Return if each value is NaN.
"""
if self._can_hold_na:
return isna(self)
else:
# shouldn't reach to this condition by checking hasnans beforehand
values = np.empty(len(self), dtype=np.bool_)
values.fill(False)
... | python | def _isnan(self):
"""
Return if each value is NaN.
"""
if self._can_hold_na:
return isna(self)
else:
# shouldn't reach to this condition by checking hasnans beforehand
values = np.empty(len(self), dtype=np.bool_)
values.fill(False)
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19,408 | pandas-dev/pandas | pandas/core/indexes/base.py | Index.get_duplicates | def get_duplicates(self):
"""
Extract duplicated index elements.
.. deprecated:: 0.23.0
Use idx[idx.duplicated()].unique() instead
Returns a sorted list of index elements which appear more than once in
the index.
Returns
-------
array-like
... | python | def get_duplicates(self):
"""
Extract duplicated index elements.
.. deprecated:: 0.23.0
Use idx[idx.duplicated()].unique() instead
Returns a sorted list of index elements which appear more than once in
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Returns
-------
array-like
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19,409 | pandas-dev/pandas | pandas/core/indexes/base.py | Index._get_unique_index | def _get_unique_index(self, dropna=False):
"""
Returns an index containing unique values.
Parameters
----------
dropna : bool
If True, NaN values are dropped.
Returns
-------
uniques : index
"""
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"""
Returns an index containing unique values.
Parameters
----------
dropna : bool
If True, NaN values are dropped.
Returns
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uniques : index
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19,410 | pandas-dev/pandas | pandas/core/indexes/base.py | Index._get_reconciled_name_object | def _get_reconciled_name_object(self, other):
"""
If the result of a set operation will be self,
return self, unless the name changes, in which
case make a shallow copy of self.
"""
name = get_op_result_name(self, other)
if self.name != name:
return se... | python | def _get_reconciled_name_object(self, other):
"""
If the result of a set operation will be self,
return self, unless the name changes, in which
case make a shallow copy of self.
"""
name = get_op_result_name(self, other)
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return se... | [
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19,411 | pandas-dev/pandas | pandas/core/indexes/base.py | Index.union | def union(self, other, sort=None):
"""
Form the union of two Index objects.
Parameters
----------
other : Index or array-like
sort : bool or None, default None
Whether to sort the resulting Index.
* None : Sort the result, except when
... | python | def union(self, other, sort=None):
"""
Form the union of two Index objects.
Parameters
----------
other : Index or array-like
sort : bool or None, default None
Whether to sort the resulting Index.
* None : Sort the result, except when
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19,412 | pandas-dev/pandas | pandas/core/indexes/base.py | Index.difference | def difference(self, other, sort=None):
"""
Return a new Index with elements from the index that are not in
`other`.
This is the set difference of two Index objects.
Parameters
----------
other : Index or array-like
sort : False or None, default None
... | python | def difference(self, other, sort=None):
"""
Return a new Index with elements from the index that are not in
`other`.
This is the set difference of two Index objects.
Parameters
----------
other : Index or array-like
sort : False or None, default None
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19,413 | pandas-dev/pandas | pandas/core/indexes/base.py | Index.symmetric_difference | def symmetric_difference(self, other, result_name=None, sort=None):
"""
Compute the symmetric difference of two Index objects.
Parameters
----------
other : Index or array-like
result_name : str
sort : False or None, default None
Whether to sort the r... | python | def symmetric_difference(self, other, result_name=None, sort=None):
"""
Compute the symmetric difference of two Index objects.
Parameters
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result_name : str
sort : False or None, default None
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19,414 | pandas-dev/pandas | pandas/core/indexes/base.py | Index._invalid_indexer | def _invalid_indexer(self, form, key):
"""
Consistent invalid indexer message.
"""
raise TypeError("cannot do {form} indexing on {klass} with these "
"indexers [{key}] of {kind}".format(
form=form, klass=type(self), key=key,
... | python | def _invalid_indexer(self, form, key):
"""
Consistent invalid indexer message.
"""
raise TypeError("cannot do {form} indexing on {klass} with these "
"indexers [{key}] of {kind}".format(
form=form, klass=type(self), key=key,
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19,415 | pandas-dev/pandas | pandas/core/indexes/base.py | Index._try_convert_to_int_index | def _try_convert_to_int_index(cls, data, copy, name, dtype):
"""
Attempt to convert an array of data into an integer index.
Parameters
----------
data : The data to convert.
copy : Whether to copy the data or not.
name : The name of the index returned.
R... | python | def _try_convert_to_int_index(cls, data, copy, name, dtype):
"""
Attempt to convert an array of data into an integer index.
Parameters
----------
data : The data to convert.
copy : Whether to copy the data or not.
name : The name of the index returned.
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19,416 | pandas-dev/pandas | pandas/core/indexes/base.py | Index._coerce_to_ndarray | def _coerce_to_ndarray(cls, data):
"""
Coerces data to ndarray.
Converts other iterables to list first and then to array.
Does not touch ndarrays.
Raises
------
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When the data passed in is a scalar.
"""
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"""
Coerces data to ndarray.
Converts other iterables to list first and then to array.
Does not touch ndarrays.
Raises
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When the data passed in is a scalar.
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19,417 | pandas-dev/pandas | pandas/core/indexes/base.py | Index._coerce_scalar_to_index | def _coerce_scalar_to_index(self, item):
"""
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Parameters
----------
item : scalar item to coerce
"""
dtype = self.dtype
if self._is_numeric_dtype and isna(item):
# We can't coerce to t... | python | def _coerce_scalar_to_index(self, item):
"""
We need to coerce a scalar to a compat for our index type.
Parameters
----------
item : scalar item to coerce
"""
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19,418 | pandas-dev/pandas | pandas/core/indexes/base.py | Index._assert_can_do_op | def _assert_can_do_op(self, value):
"""
Check value is valid for scalar op.
"""
if not is_scalar(value):
msg = "'value' must be a scalar, passed: {0}"
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"""
Check value is valid for scalar op.
"""
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19,419 | pandas-dev/pandas | pandas/core/indexes/base.py | Index.append | def append(self, other):
"""
Append a collection of Index options together.
Parameters
----------
other : Index or list/tuple of indices
Returns
-------
appended : Index
"""
to_concat = [self]
if isinstance(other, (list, tuple))... | python | def append(self, other):
"""
Append a collection of Index options together.
Parameters
----------
other : Index or list/tuple of indices
Returns
-------
appended : Index
"""
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19,420 | pandas-dev/pandas | pandas/core/indexes/base.py | Index.putmask | def putmask(self, mask, value):
"""
Return a new Index of the values set with the mask.
See Also
--------
numpy.ndarray.putmask
"""
values = self.values.copy()
try:
np.putmask(values, mask, self._convert_for_op(value))
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"""
Return a new Index of the values set with the mask.
See Also
--------
numpy.ndarray.putmask
"""
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try:
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19,421 | pandas-dev/pandas | pandas/core/indexes/base.py | Index.equals | def equals(self, other):
"""
Determine if two Index objects contain the same elements.
"""
if self.is_(other):
return True
if not isinstance(other, Index):
return False
if is_object_dtype(self) and not is_object_dtype(other):
# if oth... | python | def equals(self, other):
"""
Determine if two Index objects contain the same elements.
"""
if self.is_(other):
return True
if not isinstance(other, Index):
return False
if is_object_dtype(self) and not is_object_dtype(other):
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19,422 | pandas-dev/pandas | pandas/core/indexes/base.py | Index.identical | def identical(self, other):
"""
Similar to equals, but check that other comparable attributes are
also equal.
"""
return (self.equals(other) and
all((getattr(self, c, None) == getattr(other, c, None)
for c in self._comparables)) and
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"""
Similar to equals, but check that other comparable attributes are
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"""
return (self.equals(other) and
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19,423 | pandas-dev/pandas | pandas/core/indexes/base.py | Index.asof | def asof(self, label):
"""
Return the label from the index, or, if not present, the previous one.
Assuming that the index is sorted, return the passed index label if it
is in the index, or return the previous index label if the passed one
is not in the index.
Parameters... | python | def asof(self, label):
"""
Return the label from the index, or, if not present, the previous one.
Assuming that the index is sorted, return the passed index label if it
is in the index, or return the previous index label if the passed one
is not in the index.
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19,424 | pandas-dev/pandas | pandas/core/indexes/base.py | Index.sort_values | def sort_values(self, return_indexer=False, ascending=True):
"""
Return a sorted copy of the index.
Return a sorted copy of the index, and optionally return the indices
that sorted the index itself.
Parameters
----------
return_indexer : bool, default False
... | python | def sort_values(self, return_indexer=False, ascending=True):
"""
Return a sorted copy of the index.
Return a sorted copy of the index, and optionally return the indices
that sorted the index itself.
Parameters
----------
return_indexer : bool, default False
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19,425 | pandas-dev/pandas | pandas/core/indexes/base.py | Index.argsort | def argsort(self, *args, **kwargs):
"""
Return the integer indices that would sort the index.
Parameters
----------
*args
Passed to `numpy.ndarray.argsort`.
**kwargs
Passed to `numpy.ndarray.argsort`.
Returns
-------
numpy... | python | def argsort(self, *args, **kwargs):
"""
Return the integer indices that would sort the index.
Parameters
----------
*args
Passed to `numpy.ndarray.argsort`.
**kwargs
Passed to `numpy.ndarray.argsort`.
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19,426 | pandas-dev/pandas | pandas/core/indexes/base.py | Index.get_value | def get_value(self, series, key):
"""
Fast lookup of value from 1-dimensional ndarray. Only use this if you
know what you're doing.
"""
# if we have something that is Index-like, then
# use this, e.g. DatetimeIndex
# Things like `Series._get_value` (via .at) pass... | python | def get_value(self, series, key):
"""
Fast lookup of value from 1-dimensional ndarray. Only use this if you
know what you're doing.
"""
# if we have something that is Index-like, then
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19,427 | pandas-dev/pandas | pandas/core/indexes/base.py | Index.set_value | def set_value(self, arr, key, value):
"""
Fast lookup of value from 1-dimensional ndarray.
Notes
-----
Only use this if you know what you're doing.
"""
self._engine.set_value(com.values_from_object(arr),
com.values_from_object(key),... | python | def set_value(self, arr, key, value):
"""
Fast lookup of value from 1-dimensional ndarray.
Notes
-----
Only use this if you know what you're doing.
"""
self._engine.set_value(com.values_from_object(arr),
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19,428 | pandas-dev/pandas | pandas/core/indexes/base.py | Index.get_indexer_for | def get_indexer_for(self, target, **kwargs):
"""
Guaranteed return of an indexer even when non-unique.
This dispatches to get_indexer or get_indexer_nonunique
as appropriate.
"""
if self.is_unique:
return self.get_indexer(target, **kwargs)
indexer, _ ... | python | def get_indexer_for(self, target, **kwargs):
"""
Guaranteed return of an indexer even when non-unique.
This dispatches to get_indexer or get_indexer_nonunique
as appropriate.
"""
if self.is_unique:
return self.get_indexer(target, **kwargs)
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19,429 | pandas-dev/pandas | pandas/core/indexes/base.py | Index.groupby | def groupby(self, values):
"""
Group the index labels by a given array of values.
Parameters
----------
values : array
Values used to determine the groups.
Returns
-------
groups : dict
{group name -> group labels}
"""
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"""
Group the index labels by a given array of values.
Parameters
----------
values : array
Values used to determine the groups.
Returns
-------
groups : dict
{group name -> group labels}
"""
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19,430 | pandas-dev/pandas | pandas/core/indexes/base.py | Index.isin | def isin(self, values, level=None):
"""
Return a boolean array where the index values are in `values`.
Compute boolean array of whether each index value is found in the
passed set of values. The length of the returned boolean array matches
the length of the index.
Param... | python | def isin(self, values, level=None):
"""
Return a boolean array where the index values are in `values`.
Compute boolean array of whether each index value is found in the
passed set of values. The length of the returned boolean array matches
the length of the index.
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19,431 | pandas-dev/pandas | pandas/core/indexes/base.py | Index.slice_indexer | def slice_indexer(self, start=None, end=None, step=None, kind=None):
"""
For an ordered or unique index, compute the slice indexer for input
labels and step.
Parameters
----------
start : label, default None
If None, defaults to the beginning
end : la... | python | def slice_indexer(self, start=None, end=None, step=None, kind=None):
"""
For an ordered or unique index, compute the slice indexer for input
labels and step.
Parameters
----------
start : label, default None
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19,432 | pandas-dev/pandas | pandas/core/indexes/base.py | Index._maybe_cast_indexer | def _maybe_cast_indexer(self, key):
"""
If we have a float key and are not a floating index, then try to cast
to an int if equivalent.
"""
if is_float(key) and not self.is_floating():
try:
ckey = int(key)
if ckey == key:
... | python | def _maybe_cast_indexer(self, key):
"""
If we have a float key and are not a floating index, then try to cast
to an int if equivalent.
"""
if is_float(key) and not self.is_floating():
try:
ckey = int(key)
if ckey == key:
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19,433 | pandas-dev/pandas | pandas/core/indexes/base.py | Index._validate_indexer | def _validate_indexer(self, form, key, kind):
"""
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typed bounds must be an integer.
"""
assert kind in ['ix', 'loc', 'getitem', 'iloc']
if key is None:
pass
elif is_integer(key):
... | python | def _validate_indexer(self, form, key, kind):
"""
If we are positional indexer, validate that we have appropriate
typed bounds must be an integer.
"""
assert kind in ['ix', 'loc', 'getitem', 'iloc']
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19,434 | pandas-dev/pandas | pandas/core/indexes/base.py | Index.get_slice_bound | def get_slice_bound(self, label, side, kind):
"""
Calculate slice bound that corresponds to given label.
Returns leftmost (one-past-the-rightmost if ``side=='right'``) position
of given label.
Parameters
----------
label : object
side : {'left', 'right'}... | python | def get_slice_bound(self, label, side, kind):
"""
Calculate slice bound that corresponds to given label.
Returns leftmost (one-past-the-rightmost if ``side=='right'``) position
of given label.
Parameters
----------
label : object
side : {'left', 'right'}... | [
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19,435 | pandas-dev/pandas | pandas/core/indexes/base.py | Index.slice_locs | def slice_locs(self, start=None, end=None, step=None, kind=None):
"""
Compute slice locations for input labels.
Parameters
----------
start : label, default None
If None, defaults to the beginning
end : label, default None
If None, defaults to the... | python | def slice_locs(self, start=None, end=None, step=None, kind=None):
"""
Compute slice locations for input labels.
Parameters
----------
start : label, default None
If None, defaults to the beginning
end : label, default None
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19,436 | pandas-dev/pandas | pandas/core/indexes/base.py | Index.insert | def insert(self, loc, item):
"""
Make new Index inserting new item at location.
Follows Python list.append semantics for negative values.
Parameters
----------
loc : int
item : object
Returns
-------
new_index : Index
"""
... | python | def insert(self, loc, item):
"""
Make new Index inserting new item at location.
Follows Python list.append semantics for negative values.
Parameters
----------
loc : int
item : object
Returns
-------
new_index : Index
"""
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19,437 | pandas-dev/pandas | pandas/core/indexes/base.py | Index.drop | def drop(self, labels, errors='raise'):
"""
Make new Index with passed list of labels deleted.
Parameters
----------
labels : array-like
errors : {'ignore', 'raise'}, default 'raise'
If 'ignore', suppress error and existing labels are dropped.
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"""
Make new Index with passed list of labels deleted.
Parameters
----------
labels : array-like
errors : {'ignore', 'raise'}, default 'raise'
If 'ignore', suppress error and existing labels are dropped.
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19,438 | pandas-dev/pandas | pandas/core/indexes/base.py | Index._add_comparison_methods | def _add_comparison_methods(cls):
"""
Add in comparison methods.
"""
cls.__eq__ = _make_comparison_op(operator.eq, cls)
cls.__ne__ = _make_comparison_op(operator.ne, cls)
cls.__lt__ = _make_comparison_op(operator.lt, cls)
cls.__gt__ = _make_comparison_op(operator.... | python | def _add_comparison_methods(cls):
"""
Add in comparison methods.
"""
cls.__eq__ = _make_comparison_op(operator.eq, cls)
cls.__ne__ = _make_comparison_op(operator.ne, cls)
cls.__lt__ = _make_comparison_op(operator.lt, cls)
cls.__gt__ = _make_comparison_op(operator.... | [
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19,439 | pandas-dev/pandas | pandas/core/indexes/base.py | Index._validate_for_numeric_unaryop | def _validate_for_numeric_unaryop(self, op, opstr):
"""
Validate if we can perform a numeric unary operation.
"""
if not self._is_numeric_dtype:
raise TypeError("cannot evaluate a numeric op "
"{opstr} for type: {typ}"
.... | python | def _validate_for_numeric_unaryop(self, op, opstr):
"""
Validate if we can perform a numeric unary operation.
"""
if not self._is_numeric_dtype:
raise TypeError("cannot evaluate a numeric op "
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19,440 | pandas-dev/pandas | pandas/core/indexes/base.py | Index._validate_for_numeric_binop | def _validate_for_numeric_binop(self, other, op):
"""
Return valid other; evaluate or raise TypeError if we are not of
the appropriate type.
Notes
-----
This is an internal method called by ops.
"""
opstr = '__{opname}__'.format(opname=op.__name__)
... | python | def _validate_for_numeric_binop(self, other, op):
"""
Return valid other; evaluate or raise TypeError if we are not of
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Notes
-----
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"""
opstr = '__{opname}__'.format(opname=op.__name__)
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19,441 | pandas-dev/pandas | pandas/core/indexes/base.py | Index._add_numeric_methods_binary | def _add_numeric_methods_binary(cls):
"""
Add in numeric methods.
"""
cls.__add__ = _make_arithmetic_op(operator.add, cls)
cls.__radd__ = _make_arithmetic_op(ops.radd, cls)
cls.__sub__ = _make_arithmetic_op(operator.sub, cls)
cls.__rsub__ = _make_arithmetic_op(ops... | python | def _add_numeric_methods_binary(cls):
"""
Add in numeric methods.
"""
cls.__add__ = _make_arithmetic_op(operator.add, cls)
cls.__radd__ = _make_arithmetic_op(ops.radd, cls)
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19,442 | pandas-dev/pandas | pandas/core/indexes/base.py | Index._add_numeric_methods_unary | def _add_numeric_methods_unary(cls):
"""
Add in numeric unary methods.
"""
def _make_evaluate_unary(op, opstr):
def _evaluate_numeric_unary(self):
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"""
Add in numeric unary methods.
"""
def _make_evaluate_unary(op, opstr):
def _evaluate_numeric_unary(self):
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19,443 | pandas-dev/pandas | pandas/core/indexes/base.py | Index._add_logical_methods | def _add_logical_methods(cls):
"""
Add in logical methods.
"""
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These parameters will be passed to numpy.%(outname)s.
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These parameters will be passed to numpy.%(outnam... | python | def _add_logical_methods(cls):
"""
Add in logical methods.
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19,444 | pandas-dev/pandas | pandas/core/groupby/grouper.py | Grouper._set_grouper | def _set_grouper(self, obj, sort=False):
"""
given an object and the specifications, setup the internal grouper
for this particular specification
Parameters
----------
obj : the subject object
sort : bool, default False
whether the resulting grouper s... | python | def _set_grouper(self, obj, sort=False):
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19,445 | pandas-dev/pandas | pandas/core/missing.py | _interpolate_scipy_wrapper | def _interpolate_scipy_wrapper(x, y, new_x, method, fill_value=None,
bounds_error=False, order=None, **kwargs):
"""
Passed off to scipy.interpolate.interp1d. method is scipy's kind.
Returns an array interpolated at new_x. Add any new methods to
the list in _clean_interp_m... | python | def _interpolate_scipy_wrapper(x, y, new_x, method, fill_value=None,
bounds_error=False, order=None, **kwargs):
"""
Passed off to scipy.interpolate.interp1d. method is scipy's kind.
Returns an array interpolated at new_x. Add any new methods to
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19,446 | pandas-dev/pandas | pandas/core/missing.py | _from_derivatives | def _from_derivatives(xi, yi, x, order=None, der=0, extrapolate=False):
"""
Convenience function for interpolate.BPoly.from_derivatives.
Construct a piecewise polynomial in the Bernstein basis, compatible
with the specified values and derivatives at breakpoints.
Parameters
----------
xi : ... | python | def _from_derivatives(xi, yi, x, order=None, der=0, extrapolate=False):
"""
Convenience function for interpolate.BPoly.from_derivatives.
Construct a piecewise polynomial in the Bernstein basis, compatible
with the specified values and derivatives at breakpoints.
Parameters
----------
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19,447 | pandas-dev/pandas | pandas/core/missing.py | interpolate_2d | def interpolate_2d(values, method='pad', axis=0, limit=None, fill_value=None,
dtype=None):
"""
Perform an actual interpolation of values, values will be make 2-d if
needed fills inplace, returns the result.
"""
transf = (lambda x: x) if axis == 0 else (lambda x: x.T)
# resha... | python | def interpolate_2d(values, method='pad', axis=0, limit=None, fill_value=None,
dtype=None):
"""
Perform an actual interpolation of values, values will be make 2-d if
needed fills inplace, returns the result.
"""
transf = (lambda x: x) if axis == 0 else (lambda x: x.T)
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19,448 | pandas-dev/pandas | pandas/core/missing.py | _cast_values_for_fillna | def _cast_values_for_fillna(values, dtype):
"""
Cast values to a dtype that algos.pad and algos.backfill can handle.
"""
# TODO: for int-dtypes we make a copy, but for everything else this
# alters the values in-place. Is this intentional?
if (is_datetime64_dtype(dtype) or is_datetime64tz_dty... | python | def _cast_values_for_fillna(values, dtype):
"""
Cast values to a dtype that algos.pad and algos.backfill can handle.
"""
# TODO: for int-dtypes we make a copy, but for everything else this
# alters the values in-place. Is this intentional?
if (is_datetime64_dtype(dtype) or is_datetime64tz_dty... | [
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19,449 | pandas-dev/pandas | pandas/core/missing.py | fill_zeros | def fill_zeros(result, x, y, name, fill):
"""
If this is a reversed op, then flip x,y
If we have an integer value (or array in y)
and we have 0's, fill them with the fill,
return the result.
Mask the nan's from x.
"""
if fill is None or is_float_dtype(result):
return result
... | python | def fill_zeros(result, x, y, name, fill):
"""
If this is a reversed op, then flip x,y
If we have an integer value (or array in y)
and we have 0's, fill them with the fill,
return the result.
Mask the nan's from x.
"""
if fill is None or is_float_dtype(result):
return result
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19,450 | pandas-dev/pandas | pandas/core/missing.py | dispatch_missing | def dispatch_missing(op, left, right, result):
"""
Fill nulls caused by division by zero, casting to a diffferent dtype
if necessary.
Parameters
----------
op : function (operator.add, operator.div, ...)
left : object (Index for non-reversed ops)
right : object (Index fof reversed ops)
... | python | def dispatch_missing(op, left, right, result):
"""
Fill nulls caused by division by zero, casting to a diffferent dtype
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Parameters
----------
op : function (operator.add, operator.div, ...)
left : object (Index for non-reversed ops)
right : object (Index fof reversed ops)
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19,451 | pandas-dev/pandas | pandas/core/missing.py | _interp_limit | def _interp_limit(invalid, fw_limit, bw_limit):
"""
Get indexers of values that won't be filled
because they exceed the limits.
Parameters
----------
invalid : boolean ndarray
fw_limit : int or None
forward limit to index
bw_limit : int or None
backward limit to index
... | python | def _interp_limit(invalid, fw_limit, bw_limit):
"""
Get indexers of values that won't be filled
because they exceed the limits.
Parameters
----------
invalid : boolean ndarray
fw_limit : int or None
forward limit to index
bw_limit : int or None
backward limit to index
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backward limit to index
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19,452 | pandas-dev/pandas | pandas/io/formats/console.py | in_interactive_session | def in_interactive_session():
""" check if we're running in an interactive shell
returns True if running under python/ipython interactive shell
"""
from pandas import get_option
def check_main():
try:
import __main__ as main
except ModuleNotFoundError:
retur... | python | def in_interactive_session():
""" check if we're running in an interactive shell
returns True if running under python/ipython interactive shell
"""
from pandas import get_option
def check_main():
try:
import __main__ as main
except ModuleNotFoundError:
retur... | [
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19,453 | pandas-dev/pandas | pandas/core/groupby/categorical.py | recode_for_groupby | def recode_for_groupby(c, sort, observed):
"""
Code the categories to ensure we can groupby for categoricals.
If observed=True, we return a new Categorical with the observed
categories only.
If sort=False, return a copy of self, coded with categories as
returned by .unique(), followed by any c... | python | def recode_for_groupby(c, sort, observed):
"""
Code the categories to ensure we can groupby for categoricals.
If observed=True, we return a new Categorical with the observed
categories only.
If sort=False, return a copy of self, coded with categories as
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19,454 | pandas-dev/pandas | pandas/io/parquet.py | get_engine | def get_engine(engine):
""" return our implementation """
if engine == 'auto':
engine = get_option('io.parquet.engine')
if engine == 'auto':
# try engines in this order
try:
return PyArrowImpl()
except ImportError:
pass
try:
retu... | python | def get_engine(engine):
""" return our implementation """
if engine == 'auto':
engine = get_option('io.parquet.engine')
if engine == 'auto':
# try engines in this order
try:
return PyArrowImpl()
except ImportError:
pass
try:
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19,455 | pandas-dev/pandas | pandas/io/parquet.py | to_parquet | def to_parquet(df, path, engine='auto', compression='snappy', index=None,
partition_cols=None, **kwargs):
"""
Write a DataFrame to the parquet format.
Parameters
----------
path : str
File path or Root Directory path. Will be used as Root Directory path
while writing ... | python | def to_parquet(df, path, engine='auto', compression='snappy', index=None,
partition_cols=None, **kwargs):
"""
Write a DataFrame to the parquet format.
Parameters
----------
path : str
File path or Root Directory path. Will be used as Root Directory path
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19,456 | pandas-dev/pandas | pandas/core/groupby/ops.py | generate_bins_generic | def generate_bins_generic(values, binner, closed):
"""
Generate bin edge offsets and bin labels for one array using another array
which has bin edge values. Both arrays must be sorted.
Parameters
----------
values : array of values
binner : a comparable array of values representing bins int... | python | def generate_bins_generic(values, binner, closed):
"""
Generate bin edge offsets and bin labels for one array using another array
which has bin edge values. Both arrays must be sorted.
Parameters
----------
values : array of values
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19,457 | pandas-dev/pandas | pandas/core/groupby/ops.py | BaseGrouper.size | def size(self):
"""
Compute group sizes
"""
ids, _, ngroup = self.group_info
ids = ensure_platform_int(ids)
if ngroup:
out = np.bincount(ids[ids != -1], minlength=ngroup)
else:
out = []
return Series(out,
inde... | python | def size(self):
"""
Compute group sizes
"""
ids, _, ngroup = self.group_info
ids = ensure_platform_int(ids)
if ngroup:
out = np.bincount(ids[ids != -1], minlength=ngroup)
else:
out = []
return Series(out,
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19,458 | pandas-dev/pandas | pandas/core/reshape/melt.py | lreshape | def lreshape(data, groups, dropna=True, label=None):
"""
Reshape long-format data to wide. Generalized inverse of DataFrame.pivot
Parameters
----------
data : DataFrame
groups : dict
{new_name : list_of_columns}
dropna : boolean, default True
Examples
--------
>>> data ... | python | def lreshape(data, groups, dropna=True, label=None):
"""
Reshape long-format data to wide. Generalized inverse of DataFrame.pivot
Parameters
----------
data : DataFrame
groups : dict
{new_name : list_of_columns}
dropna : boolean, default True
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--------
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19,459 | pandas-dev/pandas | pandas/core/reshape/melt.py | wide_to_long | def wide_to_long(df, stubnames, i, j, sep="", suffix=r'\d+'):
r"""
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You ... | python | def wide_to_long(df, stubnames, i, j, sep="", suffix=r'\d+'):
r"""
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19,460 | pandas-dev/pandas | pandas/core/groupby/groupby.py | _GroupBy._get_indices | def _get_indices(self, names):
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19,461 | pandas-dev/pandas | pandas/core/groupby/groupby.py | _GroupBy._set_group_selection | def _set_group_selection(self):
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NOTE: this should be paired with a call to _reset_group_selection
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... | python | def _set_group_selection(self):
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Create group based selection.
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19,462 | pandas-dev/pandas | pandas/core/groupby/groupby.py | _GroupBy.get_group | def get_group(self, name, obj=None):
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Parameters
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name : object
the name of the group to get as a DataFrame
obj : NDFrame, default None
the NDFrame to take the DataFrame out of. If
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19,463 | pandas-dev/pandas | pandas/core/groupby/groupby.py | _GroupBy._try_cast | def _try_cast(self, result, obj, numeric_only=False):
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"""
Try to cast the result to our obj original type,
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19,464 | pandas-dev/pandas | pandas/core/groupby/groupby.py | GroupBy.sem | def sem(self, ddof=1):
"""
Compute standard error of the mean of groups, excluding missing values.
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Parameters
----------
ddof : integer, default 1
degrees of freedom
"""
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19,465 | pandas-dev/pandas | pandas/core/groupby/groupby.py | GroupBy.size | def size(self):
"""
Compute group sizes.
"""
result = self.grouper.size()
if isinstance(self.obj, Series):
result.name = getattr(self.obj, 'name', None)
return result | python | def size(self):
"""
Compute group sizes.
"""
result = self.grouper.size()
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19,466 | pandas-dev/pandas | pandas/core/groupby/groupby.py | GroupBy._add_numeric_operations | def _add_numeric_operations(cls):
"""
Add numeric operations to the GroupBy generically.
"""
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"""
Add numeric operations to the GroupBy generically.
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19,467 | pandas-dev/pandas | pandas/core/groupby/groupby.py | GroupBy.resample | def resample(self, rule, *args, **kwargs):
"""
Provide resampling when using a TimeGrouper.
Given a grouper, the function resamples it according to a string
"string" -> "frequency".
See the :ref:`frequency aliases <timeseries.offset_aliases>`
documentation for more deta... | python | def resample(self, rule, *args, **kwargs):
"""
Provide resampling when using a TimeGrouper.
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19,468 | pandas-dev/pandas | pandas/core/groupby/groupby.py | GroupBy.rolling | def rolling(self, *args, **kwargs):
"""
Return a rolling grouper, providing rolling functionality per group.
"""
from pandas.core.window import RollingGroupby
return RollingGroupby(self, *args, **kwargs) | python | def rolling(self, *args, **kwargs):
"""
Return a rolling grouper, providing rolling functionality per group.
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19,469 | pandas-dev/pandas | pandas/core/groupby/groupby.py | GroupBy.expanding | def expanding(self, *args, **kwargs):
"""
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19,470 | pandas-dev/pandas | pandas/core/groupby/groupby.py | GroupBy._fill | def _fill(self, direction, limit=None):
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Shared function for `pad` and `backfill` to call Cython method.
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Direction passed to underlying Cython function. `bfill` will cause
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19,471 | pandas-dev/pandas | pandas/core/groupby/groupby.py | GroupBy.quantile | def quantile(self, q=0.5, interpolation='linear'):
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Parameters
----------
q : float or array-like, default 0.5 (50% quantile)
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i... | python | def quantile(self, q=0.5, interpolation='linear'):
"""
Return group values at the given quantile, a la numpy.percentile.
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q : float or array-like, default 0.5 (50% quantile)
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19,472 | pandas-dev/pandas | pandas/core/groupby/groupby.py | GroupBy.ngroup | def ngroup(self, ascending=True):
"""
Number each group from 0 to the number of groups - 1.
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numbers given to the groups match the order in which the groups
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19,473 | pandas-dev/pandas | pandas/core/groupby/groupby.py | GroupBy.cumcount | def cumcount(self, ascending=True):
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19,474 | pandas-dev/pandas | pandas/core/groupby/groupby.py | GroupBy.rank | def rank(self, method='average', ascending=True, na_option='keep',
pct=False, axis=0):
"""
Provide the rank of values within each group.
Parameters
----------
method : {'average', 'min', 'max', 'first', 'dense'}, default 'average'
* average: average rank... | python | def rank(self, method='average', ascending=True, na_option='keep',
pct=False, axis=0):
"""
Provide the rank of values within each group.
Parameters
----------
method : {'average', 'min', 'max', 'first', 'dense'}, default 'average'
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19,475 | pandas-dev/pandas | pandas/core/groupby/groupby.py | GroupBy.cumprod | def cumprod(self, axis=0, *args, **kwargs):
"""
Cumulative product for each group.
"""
nv.validate_groupby_func('cumprod', args, kwargs,
['numeric_only', 'skipna'])
if axis != 0:
return self.apply(lambda x: x.cumprod(axis=axis, **kwarg... | python | def cumprod(self, axis=0, *args, **kwargs):
"""
Cumulative product for each group.
"""
nv.validate_groupby_func('cumprod', args, kwargs,
['numeric_only', 'skipna'])
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19,476 | pandas-dev/pandas | pandas/core/groupby/groupby.py | GroupBy.cummin | def cummin(self, axis=0, **kwargs):
"""
Cumulative min for each group.
"""
if axis != 0:
return self.apply(lambda x: np.minimum.accumulate(x, axis))
return self._cython_transform('cummin', numeric_only=False) | python | def cummin(self, axis=0, **kwargs):
"""
Cumulative min for each group.
"""
if axis != 0:
return self.apply(lambda x: np.minimum.accumulate(x, axis))
return self._cython_transform('cummin', numeric_only=False) | [
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19,477 | pandas-dev/pandas | pandas/core/groupby/groupby.py | GroupBy.cummax | def cummax(self, axis=0, **kwargs):
"""
Cumulative max for each group.
"""
if axis != 0:
return self.apply(lambda x: np.maximum.accumulate(x, axis))
return self._cython_transform('cummax', numeric_only=False) | python | def cummax(self, axis=0, **kwargs):
"""
Cumulative max for each group.
"""
if axis != 0:
return self.apply(lambda x: np.maximum.accumulate(x, axis))
return self._cython_transform('cummax', numeric_only=False) | [
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19,478 | pandas-dev/pandas | pandas/core/groupby/groupby.py | GroupBy._get_cythonized_result | def _get_cythonized_result(self, how, grouper, aggregate=False,
cython_dtype=None, needs_values=False,
needs_mask=False, needs_ngroups=False,
result_is_index=False,
pre_processing=None, post_proce... | python | def _get_cythonized_result(self, how, grouper, aggregate=False,
cython_dtype=None, needs_values=False,
needs_mask=False, needs_ngroups=False,
result_is_index=False,
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19,479 | pandas-dev/pandas | pandas/core/groupby/groupby.py | GroupBy.shift | def shift(self, periods=1, freq=None, axis=0, fill_value=None):
"""
Shift each group by periods observations.
Parameters
----------
periods : integer, default 1
number of periods to shift
freq : frequency string
axis : axis to shift, default 0
... | python | def shift(self, periods=1, freq=None, axis=0, fill_value=None):
"""
Shift each group by periods observations.
Parameters
----------
periods : integer, default 1
number of periods to shift
freq : frequency string
axis : axis to shift, default 0
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19,480 | pandas-dev/pandas | pandas/core/groupby/groupby.py | GroupBy.head | def head(self, n=5):
"""
Return first n rows of each group.
Essentially equivalent to ``.apply(lambda x: x.head(n))``,
except ignores as_index flag.
%(see_also)s
Examples
--------
>>> df = pd.DataFrame([[1, 2], [1, 4], [5, 6]],
... | python | def head(self, n=5):
"""
Return first n rows of each group.
Essentially equivalent to ``.apply(lambda x: x.head(n))``,
except ignores as_index flag.
%(see_also)s
Examples
--------
>>> df = pd.DataFrame([[1, 2], [1, 4], [5, 6]],
... | [
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19,481 | pandas-dev/pandas | pandas/core/groupby/groupby.py | GroupBy.tail | def tail(self, n=5):
"""
Return last n rows of each group.
Essentially equivalent to ``.apply(lambda x: x.tail(n))``,
except ignores as_index flag.
%(see_also)s
Examples
--------
>>> df = pd.DataFrame([['a', 1], ['a', 2], ['b', 1], ['b', 2]],
... | python | def tail(self, n=5):
"""
Return last n rows of each group.
Essentially equivalent to ``.apply(lambda x: x.tail(n))``,
except ignores as_index flag.
%(see_also)s
Examples
--------
>>> df = pd.DataFrame([['a', 1], ['a', 2], ['b', 1], ['b', 2]],
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19,482 | pandas-dev/pandas | pandas/tseries/holiday.py | next_monday | def next_monday(dt):
"""
If holiday falls on Saturday, use following Monday instead;
if holiday falls on Sunday, use Monday instead
"""
if dt.weekday() == 5:
return dt + timedelta(2)
elif dt.weekday() == 6:
return dt + timedelta(1)
return dt | python | def next_monday(dt):
"""
If holiday falls on Saturday, use following Monday instead;
if holiday falls on Sunday, use Monday instead
"""
if dt.weekday() == 5:
return dt + timedelta(2)
elif dt.weekday() == 6:
return dt + timedelta(1)
return dt | [
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19,483 | pandas-dev/pandas | pandas/tseries/holiday.py | previous_friday | def previous_friday(dt):
"""
If holiday falls on Saturday or Sunday, use previous Friday instead.
"""
if dt.weekday() == 5:
return dt - timedelta(1)
elif dt.weekday() == 6:
return dt - timedelta(2)
return dt | python | def previous_friday(dt):
"""
If holiday falls on Saturday or Sunday, use previous Friday instead.
"""
if dt.weekday() == 5:
return dt - timedelta(1)
elif dt.weekday() == 6:
return dt - timedelta(2)
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19,484 | pandas-dev/pandas | pandas/tseries/holiday.py | next_workday | def next_workday(dt):
"""
returns next weekday used for observances
"""
dt += timedelta(days=1)
while dt.weekday() > 4:
# Mon-Fri are 0-4
dt += timedelta(days=1)
return dt | python | def next_workday(dt):
"""
returns next weekday used for observances
"""
dt += timedelta(days=1)
while dt.weekday() > 4:
# Mon-Fri are 0-4
dt += timedelta(days=1)
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19,485 | pandas-dev/pandas | pandas/tseries/holiday.py | previous_workday | def previous_workday(dt):
"""
returns previous weekday used for observances
"""
dt -= timedelta(days=1)
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# Mon-Fri are 0-4
dt -= timedelta(days=1)
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"""
returns previous weekday used for observances
"""
dt -= timedelta(days=1)
while dt.weekday() > 4:
# Mon-Fri are 0-4
dt -= timedelta(days=1)
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19,486 | pandas-dev/pandas | pandas/tseries/holiday.py | Holiday.dates | def dates(self, start_date, end_date, return_name=False):
"""
Calculate holidays observed between start date and end date
Parameters
----------
start_date : starting date, datetime-like, optional
end_date : ending date, datetime-like, optional
return_name : bool,... | python | def dates(self, start_date, end_date, return_name=False):
"""
Calculate holidays observed between start date and end date
Parameters
----------
start_date : starting date, datetime-like, optional
end_date : ending date, datetime-like, optional
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19,487 | pandas-dev/pandas | pandas/tseries/holiday.py | Holiday._reference_dates | def _reference_dates(self, start_date, end_date):
"""
Get reference dates for the holiday.
Return reference dates for the holiday also returning the year
prior to the start_date and year following the end_date. This ensures
that any offsets to be applied will yield the holidays... | python | def _reference_dates(self, start_date, end_date):
"""
Get reference dates for the holiday.
Return reference dates for the holiday also returning the year
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19,488 | pandas-dev/pandas | pandas/tseries/holiday.py | AbstractHolidayCalendar.holidays | def holidays(self, start=None, end=None, return_name=False):
"""
Returns a curve with holidays between start_date and end_date
Parameters
----------
start : starting date, datetime-like, optional
end : ending date, datetime-like, optional
return_name : bool, opti... | python | def holidays(self, start=None, end=None, return_name=False):
"""
Returns a curve with holidays between start_date and end_date
Parameters
----------
start : starting date, datetime-like, optional
end : ending date, datetime-like, optional
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end : ending date, datetime-like, optional
return_name : bool, optional
If True, return a series that has dates and holiday names.
... | [
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19,489 | pandas-dev/pandas | pandas/tseries/holiday.py | AbstractHolidayCalendar.merge_class | def merge_class(base, other):
"""
Merge holiday calendars together. The base calendar
will take precedence to other. The merge will be done
based on each holiday's name.
Parameters
----------
base : AbstractHolidayCalendar
instance/subclass or array of ... | python | def merge_class(base, other):
"""
Merge holiday calendars together. The base calendar
will take precedence to other. The merge will be done
based on each holiday's name.
Parameters
----------
base : AbstractHolidayCalendar
instance/subclass or array of ... | [
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19,490 | pandas-dev/pandas | pandas/tseries/holiday.py | AbstractHolidayCalendar.merge | def merge(self, other, inplace=False):
"""
Merge holiday calendars together. The caller's class
rules take precedence. The merge will be done
based on each holiday's name.
Parameters
----------
other : holiday calendar
inplace : bool (default=False)
... | python | def merge(self, other, inplace=False):
"""
Merge holiday calendars together. The caller's class
rules take precedence. The merge will be done
based on each holiday's name.
Parameters
----------
other : holiday calendar
inplace : bool (default=False)
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19,491 | pandas-dev/pandas | pandas/_config/config.py | register_option | def register_option(key, defval, doc='', validator=None, cb=None):
"""Register an option in the package-wide pandas config object
Parameters
----------
key - a fully-qualified key, e.g. "x.y.option - z".
defval - the default value of the option
doc - a string description of the o... | python | def register_option(key, defval, doc='', validator=None, cb=None):
"""Register an option in the package-wide pandas config object
Parameters
----------
key - a fully-qualified key, e.g. "x.y.option - z".
defval - the default value of the option
doc - a string description of the o... | [
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doc - a string description of the option
validator - a function of a single argument, should raise `Value... | [
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19,492 | pandas-dev/pandas | pandas/_config/config.py | deprecate_option | def deprecate_option(key, msg=None, rkey=None, removal_ver=None):
"""
Mark option `key` as deprecated, if code attempts to access this option,
a warning will be produced, using `msg` if given, or a default message
if not.
if `rkey` is given, any access to the key will be re-routed to `rkey`.
Ne... | python | def deprecate_option(key, msg=None, rkey=None, removal_ver=None):
"""
Mark option `key` as deprecated, if code attempts to access this option,
a warning will be produced, using `msg` if given, or a default message
if not.
if `rkey` is given, any access to the key will be re-routed to `rkey`.
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19,493 | pandas-dev/pandas | pandas/_config/config.py | _select_options | def _select_options(pat):
"""returns a list of keys matching `pat`
if pat=="all", returns all registered options
"""
# short-circuit for exact key
if pat in _registered_options:
return [pat]
# else look through all of them
keys = sorted(_registered_options.keys())
if pat == 'a... | python | def _select_options(pat):
"""returns a list of keys matching `pat`
if pat=="all", returns all registered options
"""
# short-circuit for exact key
if pat in _registered_options:
return [pat]
# else look through all of them
keys = sorted(_registered_options.keys())
if pat == 'a... | [
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19,494 | pandas-dev/pandas | pandas/_config/config.py | _translate_key | def _translate_key(key):
"""
if key id deprecated and a replacement key defined, will return the
replacement key, otherwise returns `key` as - is
"""
d = _get_deprecated_option(key)
if d:
return d.rkey or key
else:
return key | python | def _translate_key(key):
"""
if key id deprecated and a replacement key defined, will return the
replacement key, otherwise returns `key` as - is
"""
d = _get_deprecated_option(key)
if d:
return d.rkey or key
else:
return key | [
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19,495 | pandas-dev/pandas | pandas/_config/config.py | _build_option_description | def _build_option_description(k):
""" Builds a formatted description of a registered option and prints it """
o = _get_registered_option(k)
d = _get_deprecated_option(k)
s = '{k} '.format(k=k)
if o.doc:
s += '\n'.join(o.doc.strip().split('\n'))
else:
s += 'No description avail... | python | def _build_option_description(k):
""" Builds a formatted description of a registered option and prints it """
o = _get_registered_option(k)
d = _get_deprecated_option(k)
s = '{k} '.format(k=k)
if o.doc:
s += '\n'.join(o.doc.strip().split('\n'))
else:
s += 'No description avail... | [
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19,496 | pandas-dev/pandas | pandas/_config/config.py | config_prefix | def config_prefix(prefix):
"""contextmanager for multiple invocations of API with a common prefix
supported API functions: (register / get / set )__option
Warning: This is not thread - safe, and won't work properly if you import
the API functions into your module using the "from x import y" construct.... | python | def config_prefix(prefix):
"""contextmanager for multiple invocations of API with a common prefix
supported API functions: (register / get / set )__option
Warning: This is not thread - safe, and won't work properly if you import
the API functions into your module using the "from x import y" construct.... | [
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19,497 | pandas-dev/pandas | pandas/core/arrays/interval.py | maybe_convert_platform_interval | def maybe_convert_platform_interval(values):
"""
Try to do platform conversion, with special casing for IntervalArray.
Wrapper around maybe_convert_platform that alters the default return
dtype in certain cases to be compatible with IntervalArray. For example,
empty lists return with integer dtype ... | python | def maybe_convert_platform_interval(values):
"""
Try to do platform conversion, with special casing for IntervalArray.
Wrapper around maybe_convert_platform that alters the default return
dtype in certain cases to be compatible with IntervalArray. For example,
empty lists return with integer dtype ... | [
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19,498 | pandas-dev/pandas | pandas/core/dtypes/inference.py | is_file_like | def is_file_like(obj):
"""
Check if the object is a file-like object.
For objects to be considered file-like, they must
be an iterator AND have either a `read` and/or `write`
method as an attribute.
Note: file-like objects must be iterable, but
iterable objects need not be file-like.
... | python | def is_file_like(obj):
"""
Check if the object is a file-like object.
For objects to be considered file-like, they must
be an iterator AND have either a `read` and/or `write`
method as an attribute.
Note: file-like objects must be iterable, but
iterable objects need not be file-like.
... | [
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Note: file-like objects must be iterable, but
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.. versionadded:: 0.20.0
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19,499 | pandas-dev/pandas | pandas/core/dtypes/inference.py | is_list_like | def is_list_like(obj, allow_sets=True):
"""
Check if the object is list-like.
Objects that are considered list-like are for example Python
lists, tuples, sets, NumPy arrays, and Pandas Series.
Strings and datetime objects, however, are not considered list-like.
Parameters
----------
o... | python | def is_list_like(obj, allow_sets=True):
"""
Check if the object is list-like.
Objects that are considered list-like are for example Python
lists, tuples, sets, NumPy arrays, and Pandas Series.
Strings and datetime objects, however, are not considered list-like.
Parameters
----------
o... | [
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