REF: de-duplicate operate-column-wise code, pct_change (pandas-dev#43506)

Author: jbrockmendel

pandas/core/groupby/generic.py

@@ -792,24 +792,6 @@ def count(self) -> Series:
         )
         return self._reindex_output(result, fill_value=0)
 
-    def pct_change(self, periods=1, fill_method="pad", limit=None, freq=None):
-        """Calculate pct_change of each value to previous entry in group"""
-        # TODO: Remove this conditional when #23918 is fixed
-        if freq:
-            return self.apply(
-                lambda x: x.pct_change(
-                    periods=periods, fill_method=fill_method, limit=limit, freq=freq
-                )
-            )
-        if fill_method is None:  # GH30463
-            fill_method = "pad"
-            limit = 0
-        filled = getattr(self, fill_method)(limit=limit)
-        fill_grp = filled.groupby(self.grouper.codes)
-        shifted = fill_grp.shift(periods=periods, freq=freq)
-
-        return (filled / shifted) - 1
-
     @doc(Series.nlargest)
     def nlargest(self, n: int = 5, keep: str = "first"):
         f = partial(Series.nlargest, n=n, keep=keep)
@@ -1086,14 +1068,10 @@ def _aggregate_item_by_item(self, func, *args, **kwargs) -> DataFrame:
         #  test_resample_apply_product
 
         obj = self._obj_with_exclusions
-        result: dict[int | str, NDFrame] = {}
-        for i, item in enumerate(obj):
-            ser = obj.iloc[:, i]
-            colg = SeriesGroupBy(
-                ser, selection=item, grouper=self.grouper, exclusions=self.exclusions
-            )
+        result: dict[int, NDFrame] = {}
 
-            result[i] = colg.aggregate(func, *args, **kwargs)
+        for i, (item, sgb) in enumerate(self._iterate_column_groupbys(obj)):
+            result[i] = sgb.aggregate(func, *args, **kwargs)
 
         res_df = self.obj._constructor(result)
         res_df.columns = obj.columns
@@ -1368,14 +1346,7 @@ def _transform_item_by_item(self, obj: DataFrame, wrapper) -> DataFrame:
         #  gets here with non-unique columns
         output = {}
         inds = []
-        for i, col in enumerate(obj):
-            subset = obj.iloc[:, i]
-            sgb = SeriesGroupBy(
-                subset,
-                selection=col,
-                grouper=self.grouper,
-                exclusions=self.exclusions,
-            )
+        for i, (colname, sgb) in enumerate(self._iterate_column_groupbys(obj)):
             try:
                 output[i] = sgb.transform(wrapper)
             except TypeError:

pandas/core/groupby/groupby.py

@@ -3236,6 +3236,7 @@ def shift(self, periods=1, freq=None, axis=0, fill_value=None):
         )
         return res
 
+    @final
     @Substitution(name="groupby")
     @Appender(_common_see_also)
     def pct_change(self, periods=1, fill_method="pad", limit=None, freq=None, axis=0):
@@ -3247,6 +3248,7 @@ def pct_change(self, periods=1, fill_method="pad", limit=None, freq=None, axis=0
         Series or DataFrame
             Percentage changes within each group.
         """
+        # TODO: Remove this conditional for SeriesGroupBy when GH#23918 is fixed
         if freq is not None or axis != 0:
             return self.apply(
                 lambda x: x.pct_change(