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DOC: Update GroupBy docstrings with See Also requirements #59748

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merged 3 commits into from
Sep 12, 2024
Merged

DOC: Update GroupBy docstrings with See Also requirements #59748

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7816f2e
update groupby docstrings
ktseng4096 Sep 8, 2024
d0865a1
fix function name
ktseng4096 Sep 9, 2024
468b9c1
Merge branch 'main' into groupby_filter_docstring
ktseng4096 Sep 9, 2024
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8 changes: 0 additions & 8 deletions ci/code_checks.sh
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Expand Up @@ -163,35 +163,27 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
-i "pandas.core.groupby.DataFrameGroupBy.agg RT03" \
-i "pandas.core.groupby.DataFrameGroupBy.aggregate RT03" \
-i "pandas.core.groupby.DataFrameGroupBy.boxplot PR07,RT03,SA01" \
-i "pandas.core.groupby.DataFrameGroupBy.filter SA01" \
-i "pandas.core.groupby.DataFrameGroupBy.get_group RT03,SA01" \
-i "pandas.core.groupby.DataFrameGroupBy.groups SA01" \
-i "pandas.core.groupby.DataFrameGroupBy.hist RT03" \
-i "pandas.core.groupby.DataFrameGroupBy.indices SA01" \
-i "pandas.core.groupby.DataFrameGroupBy.max SA01" \
-i "pandas.core.groupby.DataFrameGroupBy.min SA01" \
-i "pandas.core.groupby.DataFrameGroupBy.nth PR02" \
-i "pandas.core.groupby.DataFrameGroupBy.nunique SA01" \
-i "pandas.core.groupby.DataFrameGroupBy.ohlc SA01" \
-i "pandas.core.groupby.DataFrameGroupBy.plot PR02" \
-i "pandas.core.groupby.DataFrameGroupBy.sem SA01" \
-i "pandas.core.groupby.DataFrameGroupBy.sum SA01" \
-i "pandas.core.groupby.SeriesGroupBy.__iter__ RT03,SA01" \
-i "pandas.core.groupby.SeriesGroupBy.agg RT03" \
-i "pandas.core.groupby.SeriesGroupBy.aggregate RT03" \
-i "pandas.core.groupby.SeriesGroupBy.filter PR01,SA01" \
-i "pandas.core.groupby.SeriesGroupBy.get_group RT03,SA01" \
-i "pandas.core.groupby.SeriesGroupBy.groups SA01" \
-i "pandas.core.groupby.SeriesGroupBy.indices SA01" \
-i "pandas.core.groupby.SeriesGroupBy.is_monotonic_decreasing SA01" \
-i "pandas.core.groupby.SeriesGroupBy.is_monotonic_increasing SA01" \
-i "pandas.core.groupby.SeriesGroupBy.max SA01" \
-i "pandas.core.groupby.SeriesGroupBy.min SA01" \
-i "pandas.core.groupby.SeriesGroupBy.nth PR02" \
-i "pandas.core.groupby.SeriesGroupBy.ohlc SA01" \
-i "pandas.core.groupby.SeriesGroupBy.plot PR02" \
-i "pandas.core.groupby.SeriesGroupBy.sem SA01" \
-i "pandas.core.groupby.SeriesGroupBy.sum SA01" \
-i "pandas.core.resample.Resampler.__iter__ RT03,SA01" \
-i "pandas.core.resample.Resampler.ffill RT03" \
-i "pandas.core.resample.Resampler.get_group RT03,SA01" \
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14 changes: 14 additions & 0 deletions pandas/core/groupby/generic.py
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Expand Up @@ -603,12 +603,21 @@ def filter(self, func, dropna: bool = True, *args, **kwargs):
dropna : bool
Drop groups that do not pass the filter. True by default; if False,
groups that evaluate False are filled with NaNs.
*args
Additional positional arguments to pass to `func`.
**kwargs
Additional keyword arguments to pass to `func`.

Returns
-------
Series
The filtered subset of the original Series.

See Also
--------
Series.filter: Filter elements of ungrouped Series.
DataFrameGroupBy.filter : Filter elements of grouped DataFrame.

Notes
-----
Functions that mutate the passed object can produce unexpected
Expand Down Expand Up @@ -1953,6 +1962,11 @@ def filter(self, func, dropna: bool = True, *args, **kwargs) -> DataFrame:
DataFrame
The filtered subset of the original DataFrame.

See Also
--------
DataFrame.filter: Filter elements of ungrouped DataFrame.
SeriesGroupBy.filter : Filter elements of grouped Series.

Notes
-----
Each subframe is endowed the attribute 'name' in case you need to know
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9 changes: 9 additions & 0 deletions pandas/core/groupby/groupby.py
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Expand Up @@ -199,6 +199,15 @@ class providing the base-class of operations.
Series or DataFrame
Computed {fname} of values within each group.

See Also
--------
Series.min : Return the min of the group values.
DataFrame.min : Return the min of the group values.
Series.max : Return the max of the group values.
DataFrame.max : Return the max of the group values.
Series.sum : Return the sum of the group values.
DataFrame.sum : Return the sum of the group values.
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Why "group values" if you're linking to e.g. Series.min?

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Maybe just Series values or DataFrame values as appropriate?

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@ktseng4096 ktseng4096 Sep 9, 2024 •
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Thanks for catching that, I referenced the wrong function, should have been the groupby versions of those functions.

I saw elsewhere that a different template had all the functions that used the template in the see also section so I went with that same approach.

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@rhshadrach let me know if this is appropriate or not.


Examples
--------
{example}
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