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DEPR: Remove unnecessary kwargs in groupby ops #50483

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18 changes: 10 additions & 8 deletions pandas/core/groupby/generic.py
Original file line number Diff line number Diff line change
Expand Up @@ -897,9 +897,12 @@ def take(
self,
indices: TakeIndexer,
axis: Axis = 0,
**kwargs,
) -> Series:
result = self._op_via_apply("take", indices=indices, axis=axis, **kwargs)
result = self._op_via_apply(
"take",
indices=indices,
axis=axis,
)
return result

@doc(Series.skew.__doc__)
Expand All @@ -908,14 +911,12 @@ def skew(
axis: Axis | lib.NoDefault = lib.no_default,
skipna: bool = True,
numeric_only: bool = False,
**kwargs,
) -> Series:
result = self._op_via_apply(
"skew",
axis=axis,
skipna=skipna,
numeric_only=numeric_only,
**kwargs,
)
return result

Expand Down Expand Up @@ -2276,9 +2277,12 @@ def take(
self,
indices: TakeIndexer,
axis: Axis | None = 0,
**kwargs,
) -> DataFrame:
result = self._op_via_apply("take", indices=indices, axis=axis, **kwargs)
result = self._op_via_apply(
"take",
indices=indices,
axis=axis,
)
return result

@doc(DataFrame.skew.__doc__)
Expand All @@ -2287,14 +2291,12 @@ def skew(
axis: Axis | None | lib.NoDefault = lib.no_default,
skipna: bool = True,
numeric_only: bool = False,
**kwargs,
) -> DataFrame:
result = self._op_via_apply(
"skew",
axis=axis,
skipna=skipna,
numeric_only=numeric_only,
**kwargs,
)
return result

Expand Down
20 changes: 12 additions & 8 deletions pandas/core/groupby/groupby.py
Original file line number Diff line number Diff line change
Expand Up @@ -3411,38 +3411,42 @@ def rank(
@final
@Substitution(name="groupby")
@Appender(_common_see_also)
def cumprod(self, axis: Axis = 0, *args, **kwargs) -> NDFrameT:
def cumprod(self, axis: Axis = 0) -> NDFrameT:
"""
Cumulative product for each group.

Returns
-------
Series or DataFrame
"""
nv.validate_groupby_func("cumprod", args, kwargs, ["numeric_only", "skipna"])
nv.validate_groupby_func("cumprod", ["numeric_only", "skipna"])
if axis != 0:
f = lambda x: x.cumprod(axis=axis, **kwargs)
f = lambda x: x.cumprod(
axis=axis,
)
return self._python_apply_general(f, self._selected_obj, is_transform=True)

return self._cython_transform("cumprod", **kwargs)
return self._cython_transform(
"cumprod",
)

@final
@Substitution(name="groupby")
@Appender(_common_see_also)
def cumsum(self, axis: Axis = 0, *args, **kwargs) -> NDFrameT:
def cumsum(self, axis: Axis = 0) -> NDFrameT:
"""
Cumulative sum for each group.

Returns
-------
Series or DataFrame
"""
nv.validate_groupby_func("cumsum", args, kwargs, ["numeric_only", "skipna"])
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The CI is failing because of this. You can't simply delete the values, you should provide an empty tuple and an empty dictionary instead.

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Yes will do

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i am getting this error Error: The runner has received a shutdown signal...' in GHA. GH 45651 , could you help on this.

nv.validate_groupby_func("cumsum", ["numeric_only", "skipna"])
if axis != 0:
f = lambda x: x.cumsum(axis=axis, **kwargs)
f = lambda x: x.cumsum(axis=axis)
return self._python_apply_general(f, self._selected_obj, is_transform=True)

return self._cython_transform("cumsum", **kwargs)
return self._cython_transform("cumsum")

@final
@Substitution(name="groupby")
Expand Down