BUG: groupby.apply raising a TypeError when __getitem__ selects multlple columns

doc/source/whatsnew/v2.1.0.rst

@@ -413,10 +413,10 @@ Groupby/resample/rolling
   or :class:`PeriodIndex`, and the ``groupby`` method was given a function as its first argument,
   the function operated on the whole index rather than each element of the index. (:issue:`51979`)
 - Bug in :meth:`DataFrameGroupBy.apply` causing an error to be raised when the input :class:`DataFrame` was subset as a :class:`DataFrame` after groupby (``[['a']]`` and not ``['a']``) and the given callable returned :class:`Series` that were not all indexed the same. (:issue:`52444`)
+- Bug in :meth:`DataFrameGroupBy.apply` raising a ``TypeError`` when selecting multiple columns and providing a function that returns ``np.ndarray`` results (:issue:`18930`)
 - Bug in :meth:`GroupBy.groups` with a datetime key in conjunction with another key produced incorrect number of group keys (:issue:`51158`)
 - Bug in :meth:`GroupBy.quantile` may implicitly sort the result index with ``sort=False`` (:issue:`53009`)
 - Bug in :meth:`GroupBy.var` failing to raise ``TypeError`` when called with datetime64, timedelta64 or :class:`PeriodDtype` values (:issue:`52128`, :issue:`53045`)
--
 
 Reshaping
 ^^^^^^^^^

pandas/core/groupby/generic.py

@@ -51,6 +51,7 @@
     CategoricalDtype,
     IntervalDtype,
 )
+from pandas.core.dtypes.inference import is_hashable
 from pandas.core.dtypes.missing import (
     isna,
     notna,
@@ -1474,9 +1475,16 @@ def _wrap_applied_output(
             #  fall through to the outer else clause
             # TODO: sure this is right?  we used to do this
             #  after raising AttributeError above
-            return self.obj._constructor_sliced(
-                values, index=key_index, name=self._selection
-            )
+            # GH 18930
+            if not is_hashable(self._selection):
+                # error: Need type annotation for "name"
+                name = tuple(self._selection)  # type: ignore[var-annotated, arg-type]
+            else:
+                # error: Incompatible types in assignment
+                # (expression has type "Hashable", variable
+                # has type "Tuple[Any, ...]")
+                name = self._selection  # type: ignore[assignment]
+            return self.obj._constructor_sliced(values, index=key_index, name=name)
         elif not isinstance(first_not_none, Series):
             # values are not series or array-like but scalars
             # self._selection not passed through to Series as the

pandas/tests/groupby/test_apply.py

@@ -1404,3 +1404,15 @@ def test_apply_inconsistent_output(group_col):
     )
 
     tm.assert_series_equal(result, expected)
+
+
+def test_apply_array_output_multi_getitem():
+    # GH 18930
+    df = DataFrame(
+        {"A": {"a": 1, "b": 2}, "B": {"a": 1, "b": 2}, "C": {"a": 1, "b": 2}}
+    )
+    result = df.groupby("A")[["B", "C"]].apply(lambda x: np.array([0]))
+    expected = Series(
+        [np.array([0])] * 2, index=Index([1, 2], name="A"), name=("B", "C")
+    )
+    tm.assert_series_equal(result, expected)