Backport PR #43054: REGR: SeriesGrouper using Timestamp index (#43081)

Co-authored-by: jbrockmendel <jbrockmendel@gmail.com>

Author: meeseeksmachine

doc/source/whatsnew/v1.3.3.rst

@@ -16,7 +16,7 @@ Fixed regressions
 ~~~~~~~~~~~~~~~~~
 - Fixed regression in :class:`DataFrame` constructor failing to broadcast for defined :class:`Index` and len one list of :class:`Timestamp` (:issue:`42810`)
 - Performance regression in :meth:`core.window.ewm.ExponentialMovingWindow.mean` (:issue:`42333`)
--
+- Fixed regression in :meth:`.GroupBy.agg` incorrectly raising in some cases (:issue:`42390`)
 -
 
 .. ---------------------------------------------------------------------------

pandas/core/indexes/datetimelike.py

@@ -626,7 +626,7 @@ def _with_freq(self, freq):
     @property
     def _has_complex_internals(self) -> bool:
         # used to avoid libreduction code paths, which raise or require conversion
-        return False
+        return True
 
     def is_type_compatible(self, kind: str) -> bool:
         return kind in self._data._infer_matches

pandas/tests/groupby/aggregate/test_aggregate.py

@@ -1259,3 +1259,18 @@ def test_groupby_index_object_dtype():
     )
     expected = Series([False, True], index=expected_index, name="p")
     tm.assert_series_equal(res, expected)
+
+
+def test_timeseries_groupby_agg():
+    # GH#43290
+
+    def func(ser):
+        if ser.isna().all():
+            return None
+        return np.sum(ser)
+
+    df = DataFrame([1.0], index=[pd.Timestamp("2018-01-16 00:00:00+00:00")])
+    res = df.groupby(lambda x: 1).agg(func)
+
+    expected = DataFrame([[1.0]], index=[1])
+    tm.assert_frame_equal(res, expected)