prevent fast_apply case for _has_complex_internals

pandas/core/groupby/ops.py

@@ -164,8 +164,8 @@ def apply(self, f, data: FrameOrSeries, axis: int = 0):
  com.get_callable_name(f) not in base.plotting_methods
  and isinstance(splitter, FrameSplitter)
  and axis == 0
- # apply_frame_axis0 doesn't allow MultiIndex
- and not isinstance(sdata.index, MultiIndex)
+ # fast_apply/libreduction doesn't allow non-numpy backed indexes
+ and not sdata.index._has_complex_internals
  ):
  try:
  result_values, mutated = splitter.fast_apply(f, group_keys)

pandas/tests/groupby/test_apply.py

@@ -811,3 +811,19 @@ def test_groupby_apply_datetime_result_dtypes():
  index=["observation", "color", "mood", "intensity", "score"],
  )
  tm.assert_series_equal(result, expected)
+
+
+@pytest.mark.parametrize(
+ "index",
+ [
+ pd.CategoricalIndex(list("abc")),
+ pd.interval_range(0, 3),
+ pd.period_range("2020", periods=3, freq="D"),
+ pd.MultiIndex.from_tuples([("a", 0), ("a", 1), ("b", 0)]),
+ ],
+)
+def test_apply_index_has_complex_internals(index):
+ # GH 31248
+ df = DataFrame({"group": [1, 1, 2], "value": [0, 1, 0]}, index=index)
+ result = df.groupby("group").apply(lambda x: x)
+ tm.assert_frame_equal(result, df)