Fixups

Author: rhshadrach

pandas/core/apply.py

@@ -609,7 +609,9 @@ def new_dict_like(self, method: str) -> DataFrame | Series:
             is_ndframe = [isinstance(r, ABCNDFrame) for r in results]
 
         # combine results
+        result: DataFrame | Series
         if all(is_ndframe):
+            keys_to_use: Iterable[Hashable]
             keys_to_use = [k for k in arg.keys() if not results[k].empty]
             keys_to_use = keys_to_use if keys_to_use != [] else arg.keys()
             if selected_obj.ndim == 2:
@@ -619,8 +621,6 @@ def new_dict_like(self, method: str) -> DataFrame | Series:
                 keys_to_use = ktu
             keys = None if selected_obj.ndim == 1 else keys_to_use
             result = concat({k: results[k] for k in keys_to_use}, keys=keys, axis=1)
-            if result.ndim == 1:
-                result = result.to_frame()
         elif any(is_ndframe):
             # There is a mix of NDFrames and scalars
             raise ValueError(

pandas/tests/apply/test_frame_apply.py

@@ -1450,9 +1450,9 @@ def test_apply_no_suffix_index(request):
     result = pdf.apply([np.square, lambda x: x, lambda x: x])
     if get_option("mode.new_udf_methods"):
         columns = MultiIndex.from_product(
-            [["A", "B"], ["square", "<lambda>", "<lambda>"]]
+            [["square", "<lambda>", "<lambda>"], ["A", "B"]]
         )
-        expected = DataFrame([[16, 4, 4, 81, 9, 9]], columns=columns)
+        expected = DataFrame(3 * [[16, 81, 4, 9, 4, 9]], columns=columns)
     else:
         columns = MultiIndex.from_product(
             [["A", "B"], ["square", "<lambda>", "<lambda>"]]