Revert previous commit (pandas-dev#39879)

Author: rhshadrach

pandas/core/apply.py

@@ -225,66 +225,51 @@ def agg_list_like(self, _axis: int) -> FrameOrSeriesUnion:
 
         results = []
         keys = []
-        ndims = []
 
         # degenerate case
-        # if selected_obj.ndim == 1:
-        for a in arg:
-            # colg = obj._gotitem(selected_obj.name, ndim=1, subset=selected_obj)
-            try:
-                # new_res = colg.aggregate(a)
-                print('selected_obj:', type(selected_obj))
-                print(selected_obj)
-                print('###')
-                new_res = selected_obj.aggregate(a)
-                print(new_res)
-
-            except TypeError:
-                pass
-            else:
-                results.append(new_res)
-                if isinstance(new_res, ABCNDFrame):
-                    ndims.append(new_res.ndim)
+        if selected_obj.ndim == 1:
+            for a in arg:
+                colg = obj._gotitem(selected_obj.name, ndim=1, subset=selected_obj)
+                try:
+                    new_res = colg.aggregate(a)
+
+                except TypeError:
+                    pass
                 else:
-                    ndims.append(0)
+                    results.append(new_res)
 
-                # make sure we find a good name
-                name = com.get_callable_name(a) or a
-                keys.append(name)
+                    # make sure we find a good name
+                    name = com.get_callable_name(a) or a
+                    keys.append(name)
 
         # multiples
-        # else:
-        #     for index, col in enumerate(selected_obj):
-        #         colg = obj._gotitem(col, ndim=1, subset=selected_obj.iloc[:, index])
-        #         try:
-        #             new_res = colg.aggregate(arg)
-        #         except (TypeError, DataError):
-        #             pass
-        #         except ValueError as err:
-        #             # cannot aggregate
-        #             if "Must produce aggregated value" in str(err):
-        #                 # raised directly in _aggregate_named
-        #                 pass
-        #             elif "no results" in str(err):
-        #                 # raised directly in _aggregate_multiple_funcs
-        #                 pass
-        #             else:
-        #                 raise
-        #         else:
-        #             results.append(new_res)
-        #             keys.append(col)
+        else:
+            for index, col in enumerate(selected_obj):
+                colg = obj._gotitem(col, ndim=1, subset=selected_obj.iloc[:, index])
+                try:
+                    new_res = colg.aggregate(arg)
+                except (TypeError, DataError):
+                    pass
+                except ValueError as err:
+                    # cannot aggregate
+                    if "Must produce aggregated value" in str(err):
+                        # raised directly in _aggregate_named
+                        pass
+                    elif "no results" in str(err):
+                        # raised directly in _aggregate_multiple_funcs
+                        pass
+                    else:
+                        raise
+                else:
+                    results.append(new_res)
+                    keys.append(col)
 
         # if we are empty
         if not len(results):
             raise ValueError("no results")
 
         try:
-            # if len(results) == 0:
-            #     result = results[0]
-            # else:
-            result = concat(results, keys=keys, axis=1, sort=False)
-            if all([e == 1 for e in ndims]):
-                result = result.T.infer_objects()
+            return concat(results, keys=keys, axis=1, sort=False)
         except TypeError as err:
 
             # we are concatting non-NDFrame objects,
@@ -297,12 +282,7 @@ def agg_list_like(self, _axis: int) -> FrameOrSeriesUnion:
                 raise ValueError(
                     "cannot combine transform and aggregation operations"
                 ) from err
-        else:
-            if result.columns.nlevels > 1:
-                new_order = [-1] + list(range(result.columns.nlevels - 1))
-                result = result.reorder_levels(new_order, axis='columns')
-                result = result[selected_obj.columns]
-        return result
+            return result
 
     def agg_dict_like(self, _axis: int) -> FrameOrSeriesUnion:
         """

pandas/tests/apply/test_frame_apply.py

@@ -1101,7 +1101,6 @@ def test_consistency_for_boxed(self, box, int_frame_const_col):
 
 class TestDataFrameAggregate:
     def test_agg_transform(self, axis, float_frame):
-        float_frame = float_frame.head()
         other_axis = 1 if axis in {0, "index"} else 0
 
         with np.errstate(all="ignore"):
@@ -1125,16 +1124,11 @@ def test_agg_transform(self, axis, float_frame):
                 expected.index = pd.MultiIndex.from_product(
                     [float_frame.index, ["sqrt"]]
                 )
-            print("result")
-            print(result)
-            print('expected')
-            print(expected)
             tm.assert_frame_equal(result, expected)
 
             # multiple items in list
             # these are in the order as if we are applying both
             # functions per series and then concatting
-            print('marker')
             result = float_frame.apply([np.abs, np.sqrt], axis=axis)
             expected = zip_frames([f_abs, f_sqrt], axis=other_axis)
             if axis in {0, "index"}:
@@ -1145,24 +1139,20 @@ def test_agg_transform(self, axis, float_frame):
                 expected.index = pd.MultiIndex.from_product(
                     [float_frame.index, ["absolute", "sqrt"]]
                 )
-            print()
-            print(result)
-            print()
-            print(expected)
             tm.assert_frame_equal(result, expected)
 
     def test_transform_and_agg_err(self, axis, float_frame):
         # cannot both transform and agg
         msg = "cannot combine transform and aggregation operations"
         with pytest.raises(ValueError, match=msg):
             with np.errstate(all="ignore"):
-                print(float_frame.agg(["max", "sqrt"], axis=axis))
+                float_frame.agg(["max", "sqrt"], axis=axis)
 
         df = DataFrame({"A": range(5), "B": 5})
 
         def f():
             with np.errstate(all="ignore"):
-                print(df.agg({"A": ["abs", "sum"], "B": ["mean", "max"]}, axis=axis))
+                df.agg({"A": ["abs", "sum"], "B": ["mean", "max"]}, axis=axis)
 
     def test_demo(self):
         # demonstration tests