TST: regression test for concat with keys and mixed-freq PeriodIndex columns (#65439)

Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

Author: jbrockmendel

pandas/tests/reshape/concat/test_datetimes.py

@@ -575,6 +575,30 @@ def test_concat_period_other_series3(self):
         tm.assert_series_equal(result, expected)
         assert result.dtype == "object"
 
+    def test_concat_keys_mixed_freq_period_columns(self):
+        # GH#51489 concat with keys must not raise IncompatibleFrequency
+        # when the inputs have PeriodIndex columns with different freq
+        q_period = pd.period_range("2022-1-1", "2022-12-31", freq="Q")
+        y_period = pd.period_range("2019-1-1", "2023-1-1", freq="Y")
+
+        q_df = DataFrame([range(len(q_period))], columns=q_period)
+        y_df = DataFrame([range(len(y_period))], columns=y_period)
+
+        result = concat([q_df, y_df], keys=["Quarterly", "Yearly"], axis=1)
+
+        expected_inner = Index(list(q_period) + list(y_period), dtype=object)
+        expected_columns = MultiIndex.from_arrays(
+            [
+                ["Quarterly"] * len(q_period) + ["Yearly"] * len(y_period),
+                expected_inner,
+            ]
+        )
+        expected = DataFrame(
+            [list(range(len(q_period))) + list(range(len(y_period)))],
+            columns=expected_columns,
+        )
+        tm.assert_frame_equal(result, expected)
+
 
 def test_concat_timedelta64_block():
     rng = to_timedelta(np.arange(10), unit="s")