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DOC: Updated groupby.expanding arguments #61352

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Merged
merged 2 commits into from
Apr 25, 2025
Merged

DOC: Updated groupby.expanding arguments #61352

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dd47e19
updated expanding args
arthurlw Apr 25, 2025
ef5f582
fixed punctuation
arthurlw Apr 25, 2025
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31 changes: 19 additions & 12 deletions pandas/core/groupby/groupby.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3809,19 +3809,26 @@ def rolling(
)

@final
def expanding(self, *args, **kwargs) -> ExpandingGroupby:
def expanding(
self,
min_periods: int = 1,
method: str = "single",
) -> ExpandingGroupby:
"""
Return an expanding grouper, providing expanding functionality per group.

Arguments are the same as `:meth:DataFrame.rolling` except that ``step`` cannot
be specified.
Comment on lines -3816 to -3817
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Doesn't rolling accept many more arguments, e.g. window?

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I opened #61361 just to be sure this doesn't get forgotten.

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This was incorrect, the signature is fine here.


Parameters
----------
*args : tuple
Positional arguments passed to the expanding window constructor.
**kwargs : dict
Keyword arguments passed to the expanding window constructor.
min_periods : int, default 1
Minimum number of observations in window required to have a value;
otherwise, result is ``np.nan``.

method : str {'single', 'table'}, default 'single'
Execute the expanding operation per single column or row (``'single'``)
or over the entire object (``'table'``).

This argument is only implemented when specifying ``engine='numba'``
in the method call.

Returns
-------
Expand All @@ -3844,7 +3851,7 @@ def expanding(self, *args, **kwargs) -> ExpandingGroupby:
... }
... )
>>> df
Class Value
Class Value
0 A 10
1 A 20
2 A 30
Expand All @@ -3853,7 +3860,7 @@ def expanding(self, *args, **kwargs) -> ExpandingGroupby:
5 B 60

>>> df.groupby("Class").expanding().mean()
Value
Value
Class
A 0 10.0
1 15.0
Expand All @@ -3866,9 +3873,9 @@ def expanding(self, *args, **kwargs) -> ExpandingGroupby:

return ExpandingGroupby(
self._selected_obj,
*args,
min_periods=min_periods,
method=method,
_grouper=self._grouper,
**kwargs,
)

@final
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