HyukjinKwon commented on code in PR #36660:
URL: https://github.com/apache/spark/pull/36660#discussion_r888603854
##########
python/pyspark/pandas/groupby.py:
##########
@@ -759,6 +759,99 @@ def skew(scol: Column) -> Column:
bool_to_numeric=True,
)
+ # TODO: 'axis', 'skipna', 'level' parameter should be implemented.
+ def mad(self) -> FrameLike:
+ """
+ Compute mean absolute deviation of groups, excluding missing values.
+
+ .. versionadded:: 3.4.0
+
+ Examples
+ --------
+ >>> df = ps.DataFrame({"A": [1, 2, 1, 1], "B": [True, False, False,
True],
+ ... "C": [3, 4, 3, 4], "D": ["a", "b", "b", "a"]})
+
+ >>> df.groupby("A").mad()
+ B C
+ A
+ 1 0.444444 0.444444
+ 2 0.000000 0.000000
+
+ >>> df.B.groupby(df.A).mad()
+ A
+ 1 0.444444
+ 2 0.000000
+ Name: B, dtype: float64
+
+ See Also
+ --------
+ pyspark.pandas.Series.groupby
+ pyspark.pandas.DataFrame.groupby
+ """
+
+ groupkey_names = [SPARK_INDEX_NAME_FORMAT(i) for i in
range(len(self._groupkeys))]
+ groupkey_scols = [s.alias(name) for s, name in
zip(self._groupkeys_scols, groupkey_names)]
+
+ agg_columns = []
+ for psser in self._agg_columns:
+ if isinstance(psser.spark.data_type, BooleanType):
+ agg_columns.append(psser.astype(int))
+ elif isinstance(psser.spark.data_type, NumericType):
+ agg_columns.append(psser)
+
+ sdf = self._psdf._internal.spark_frame.select(
+ *groupkey_scols, *[psser.spark.column for psser in agg_columns]
+ )
+
+ internal = InternalFrame(
+ spark_frame=sdf,
+ index_spark_columns=[scol_for(sdf, col) for col in groupkey_names],
+ index_names=[psser._column_label for psser in self._groupkeys],
+ index_fields=[
+ psser._internal.data_fields[0].copy(name=name)
+ for psser, name in zip(self._groupkeys, groupkey_names)
+ ],
+ data_spark_columns=[
+ scol_for(sdf, psser._internal.data_spark_column_names[0]) for
psser in agg_columns
+ ],
+ column_labels=[psser._column_label for psser in agg_columns],
+ data_fields=[psser._internal.data_fields[0] for psser in
agg_columns],
+ column_label_names=self._psdf._internal.column_label_names,
+ )
+ psdf: DataFrame = DataFrame(internal)
+
+ if len(psdf._internal.column_labels) > 0:
Review Comment:
Maybe lets add some comments here.
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