BUG: groupby agg fails silently with mixed dtypes

doc/source/whatsnew/v1.3.3.rst

@@ -17,6 +17,7 @@ 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`)
+- Fixed regression in :meth:`.GroupBy.agg` where it was failing silently with mixed data types  (:issue:`43209`)
 - Fixed regression in :meth:`RangeIndex.where` and :meth:`RangeIndex.putmask` raising ``AssertionError`` when result did not represent a :class:`RangeIndex` (:issue:`43240`)
 
 .. ---------------------------------------------------------------------------

pandas/core/groupby/generic.py

@@ -41,6 +41,7 @@
     doc,
 )
 
+from pandas.core.dtypes.cast import find_common_type
 from pandas.core.dtypes.common import (
     ensure_int64,
     is_bool,
@@ -1056,7 +1057,8 @@ def aggregate(self, func=None, *args, engine=None, engine_kwargs=None, **kwargs)
     def _iterate_slices(self) -> Iterable[Series]:
         obj = self._selected_obj
         if self.axis == 1:
-            obj = obj.T
+            transposed_dtype = find_common_type(obj.dtypes.tolist())
+            obj = obj.T.astype(transposed_dtype, copy=False)
 
         if isinstance(obj, Series) and obj.name not in self.exclusions:
             # Occurs when doing DataFrameGroupBy(...)["X"]
@@ -1597,7 +1599,8 @@ def _gotitem(self, key, ndim: int, subset=None):
     def _get_data_to_aggregate(self) -> Manager2D:
         obj = self._obj_with_exclusions
         if self.axis == 1:
-            return obj.T._mgr
+            transposed_dtype = find_common_type(obj.dtypes.tolist())
+            return obj.T.astype(transposed_dtype, copy=False)._mgr
         else:
             return obj._mgr
 

pandas/tests/groupby/test_groupby.py

@@ -2419,3 +2419,26 @@ def test_rolling_wrong_param_min_period():
     result_error_msg = r"__init__\(\) got an unexpected keyword argument 'min_period'"
     with pytest.raises(TypeError, match=result_error_msg):
         test_df.groupby("name")["val"].rolling(window=2, min_period=1).sum()
+
+
+@pytest.mark.parametrize(
+    "func, expected, dtype, result_dtype",
+    [
+        ("sum", [5, 7, 9], int, "int64"),
+        ("std", [4.5 ** 0.5] * 3, int, float),
+        ("var", [4.5] * 3, int, float),
+        ("sum", [5, 7, 9], "Int64", "Int64"),
+        # result_dtype should ideally be Float64
+        ("std", [4.5 ** 0.5] * 3, "Int64", float),
+        ("var", [4.5] * 3, "Int64", "Float64"),
+    ],
+)
+def test_multiindex_groupby(func, expected, dtype, result_dtype):
+    # GH#43209
+    df = DataFrame(
+        [[1, 2, 3, 4, 5, 6]] * 3,
+        columns=MultiIndex.from_product([["a", "b"], ["i", "j", "k"]]),
+    ).astype({("a", "j"): dtype, ("b", "j"): dtype})
+    result = df.groupby(level=1, axis=1).agg(func)
+    expected = DataFrame([expected] * 3, columns=["i", "j", "k"], dtype=result_dtype)
+    tm.assert_frame_equal(result, expected)