DEPR: DataFrameGroupBy.apply operating on the group keys

doc/source/whatsnew/v2.1.0.rst

@@ -149,7 +149,7 @@ Other API changes
 
 Deprecations
 ~~~~~~~~~~~~
-- Deprecated :meth:`.DataFrameGroupBy.apply` operating on the grouping column(s) (:issue:`7155`)
+- Deprecated :meth:`.DataFrameGroupBy.apply` and :class:`.Resampler` methods operating on the grouping column(s); subset the data to exclude the grouping column(s) to adopt future behavior and avoid the ``FutureWarning`` (:issue:`7155`)
 - Deprecated silently dropping unrecognized timezones when parsing strings to datetimes (:issue:`18702`)
 - Deprecated :meth:`DataFrame._data` and :meth:`Series._data`, use public APIs instead (:issue:`33333`)
 - Deprecated :meth:`.Groupby.all` and :meth:`.GroupBy.any` with datetime64 or :class:`PeriodDtype` values, matching the :class:`Series` and :class:`DataFrame` deprecations (:issue:`34479`)

pandas/core/groupby/groupby.py

@@ -1492,15 +1492,8 @@ def f(g):
                     and self._selection is None
                     and self._selected_obj.shape != self._obj_with_exclusions.shape
                 ):
-                    msg = (
-                        f"{type(self).__name__}.apply operated on the grouping "
-                        f"columns. This behavior is deprecated, and in a future "
-                        f"version of pandas the grouping columns will be excluded "
-                        f"from the operation. Subset the data to exclude the "
-                        f"groupings and silence this warning."
-                    )
                     warnings.warn(
-                        message=msg,
+                        message=_apply_groupings_depr.format(type(self).__name__),
                         category=FutureWarning,
                         stacklevel=find_stack_level(),
                     )
@@ -4330,3 +4323,12 @@ def _insert_quantile_level(idx: Index, qs: npt.NDArray[np.float64]) -> MultiInde
     else:
         mi = MultiIndex.from_product([idx, qs])
     return mi
+
+
+# GH#7155
+_apply_groupings_depr = (
+    "{}.apply operated on the grouping columns. This behavior is deprecated, "
+    "and in a future version of pandas the grouping columns will be excluded "
+    "from the operation. Subset the data to exclude the groupings and silence "
+    "this warning."
+)

pandas/core/resample.py

@@ -55,6 +55,7 @@
 from pandas.core.groupby.groupby import (
     BaseGroupBy,
     GroupBy,
+    _apply_groupings_depr,
     _pipe_template,
     get_groupby,
 )
@@ -424,12 +425,7 @@ def _groupby_and_aggregate(self, how, *args, **kwargs):
         )
 
         target_message = "DataFrameGroupBy.apply operated on the grouping columns"
-        new_message = (
-            "DataFrame.resample operated on the grouping columns. "
-            "This behavior is deprecated, and in a future version of "
-            "pandas the grouping columns will be excluded from the operation. "
-            "Subset the data to exclude the groupings and silence this warning."
-        )
+        new_message = _apply_groupings_depr.format(type(self).__name__)
 
         try:
             if callable(how):

pandas/core/reshape/pivot.py

@@ -15,7 +15,6 @@
     Appender,
     Substitution,
 )
-from pandas.util._exceptions import rewrite_warning
 
 from pandas.core.dtypes.cast import maybe_downcast_to_dtype
 from pandas.core.dtypes.common import (
@@ -458,19 +457,7 @@ def _all_key():
             return (margins_name,) + ("",) * (len(cols) - 1)
 
         if len(rows) > 0:
-            target_message = "DataFrameGroupBy.apply operated on the grouping columns"
-            new_message = (
-                "DataFrame.pivot_table operated on the grouping columns. "
-                "This behavior is deprecated, and in a future version of "
-                "pandas the grouping columns will be excluded from the operation. "
-                "Can the user do something here?"
-            )
-            with rewrite_warning(
-                target_message=target_message,
-                target_category=FutureWarning,
-                new_message=new_message,
-            ):
-                margin = data[rows].groupby(rows, observed=observed).apply(aggfunc)
+            margin = data.groupby(rows, observed=observed)[rows].apply(aggfunc)
             all_key = _all_key()
             table[all_key] = margin
             result = table
@@ -488,7 +475,7 @@ def _all_key():
         margin_keys = table.columns
 
     if len(cols):
-        row_margin = data[cols].groupby(cols, observed=observed).apply(aggfunc)
+        row_margin = data.groupby(cols, observed=observed)[cols].apply(aggfunc)
     else:
         row_margin = Series(np.nan, index=result.columns)
 

pandas/tests/reshape/test_pivot.py

@@ -1172,32 +1172,26 @@ def test_margins_no_values_no_cols(self, data):
     def test_margins_no_values_two_rows(self, data):
         # Regression test on pivot table: no values passed but rows are a
         # multi-index
-        msg = "DataFrame.pivot_table operated on the grouping columns"
-        with tm.assert_produces_warning(FutureWarning, match=msg):
-            result = data[["A", "B", "C"]].pivot_table(
-                index=["A", "B"], columns="C", aggfunc=len, margins=True
-            )
+        result = data[["A", "B", "C"]].pivot_table(
+            index=["A", "B"], columns="C", aggfunc=len, margins=True
+        )
         assert result.All.tolist() == [3.0, 1.0, 4.0, 3.0, 11.0]
 
     def test_margins_no_values_one_row_one_col(self, data):
         # Regression test on pivot table: no values passed but row and col
         # defined
-        msg = "DataFrame.pivot_table operated on the grouping columns"
-        with tm.assert_produces_warning(FutureWarning, match=msg):
-            result = data[["A", "B"]].pivot_table(
-                index="A", columns="B", aggfunc=len, margins=True
-            )
+        result = data[["A", "B"]].pivot_table(
+            index="A", columns="B", aggfunc=len, margins=True
+        )
         assert result.All.tolist() == [4.0, 7.0, 11.0]
 
     def test_margins_no_values_two_row_two_cols(self, data):
         # Regression test on pivot table: no values passed but rows and cols
         # are multi-indexed
         data["D"] = ["a", "b", "c", "d", "e", "f", "g", "h", "i", "j", "k"]
-        msg = "DataFrame.pivot_table operated on the grouping columns"
-        with tm.assert_produces_warning(FutureWarning, match=msg):
-            result = data[["A", "B", "C", "D"]].pivot_table(
-                index=["A", "B"], columns=["C", "D"], aggfunc=len, margins=True
-            )
+        result = data[["A", "B", "C", "D"]].pivot_table(
+            index=["A", "B"], columns=["C", "D"], aggfunc=len, margins=True
+        )
         assert result.All.tolist() == [3.0, 1.0, 4.0, 3.0, 11.0]
 
     @pytest.mark.parametrize("margin_name", ["foo", "one", 666, None, ["a", "b"]])

scripts/validate_unwanted_patterns.py

@@ -37,6 +37,7 @@
     "_agg_template_series",
     "_agg_template_frame",
     "_pipe_template",
+    "_apply_groupings_depr",
     "__main__",
     "_transform_template",
     "_flex_comp_doc_FRAME",