Backport PR #42541: REGR: concat(ints, bools) casting to object #42092 (#42548)

Co-authored-by: jbrockmendel <[email protected]>

Author: meeseeksmachine

doc/source/whatsnew/v1.3.1.rst

@@ -23,7 +23,7 @@ Fixed regressions
 - Performance regression in :meth:`DataFrame.to_dict` and :meth:`Series.to_dict` when ``orient`` argument one of "records", "dict", or "split" (:issue:`42352`)
 - Fixed regression in indexing with a ``list`` subclass incorrectly raising ``TypeError`` (:issue:`42433`, :issue:`42461`)
 - Fixed regression in :meth:`DataFrame.isin` and :meth:`Series.isin` raising ``TypeError`` with nullable data containing at least one missing value (:issue:`42405`)
--
+- Regression in :func:`concat` between objects with bool dtype and integer dtype casting to object instead of to integer (:issue:`42092`)
 
 .. ---------------------------------------------------------------------------
 

pandas/core/internals/concat.py

@@ -592,6 +592,9 @@ def _is_uniform_join_units(join_units: list[JoinUnit]) -> bool:
         # e.g. DatetimeLikeBlock can be dt64 or td64, but these are not uniform
         all(
             is_dtype_equal(ju.block.dtype, join_units[0].block.dtype)
+            # GH#42092 we only want the dtype_equal check for non-numeric blocks
+            #  (for now, may change but that would need a deprecation)
+            or ju.block.dtype.kind in ["b", "i", "u"]
             for ju in join_units
         )
         and

pandas/tests/reshape/concat/test_dataframe.py

@@ -170,3 +170,13 @@ def test_concat_dataframe_keys_bug(self, sort):
         # it works
         result = concat([t1, t2], axis=1, keys=["t1", "t2"], sort=sort)
         assert list(result.columns) == [("t1", "value"), ("t2", "value")]
+
+    def test_concat_bool_with_int(self):
+        # GH#42092 we may want to change this to return object, but that
+        #  would need a deprecation
+        df1 = DataFrame(Series([True, False, True, True], dtype="bool"))
+        df2 = DataFrame(Series([1, 0, 1], dtype="int64"))
+
+        result = concat([df1, df2])
+        expected = concat([df1.astype("int64"), df2])
+        tm.assert_frame_equal(result, expected)