update groupby docstrings

Author: ktseng4096

ci/code_checks.sh

@@ -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" \

pandas/core/groupby/generic.py

@@ -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
@@ -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

pandas/core/groupby/groupby.py

@@ -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.
+
 Examples
 --------
 {example}