BUG: Using agg with groupy, as_index=False still returning group variable as index

doc/source/whatsnew/v0.25.0.rst

@@ -172,7 +172,7 @@ Plotting
 Groupby/Resample/Rolling
 ^^^^^^^^^^^^^^^^^^^^^^^^
 
--
+- Fixed bug in GroupBy when using as_index=False (issue:`25011`)
 -
 -
 

pandas/core/base.py

@@ -557,7 +557,7 @@ def is_any_frame():
             # we require a list, but not an 'str'
             return self._aggregate_multiple_funcs(arg,
                                                   _level=_level,
-                                                  _axis=_axis), None
+                                                  _axis=_axis), True
         else:
             result = None
 

pandas/tests/groupby/aggregate/test_aggregate.py

@@ -286,3 +286,46 @@ def test_multi_function_flexible_mix(df):
     with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
         result = grouped.aggregate(d)
     tm.assert_frame_equal(result, expected)
+
+
+def test_not_as_index_agg_list():
+
+    # GH 25011
+    # expected behavhior of agg with as_index=True
+    as_index = False
+    array = [[3, 1, 2],
+             [3, 3, 4],
+             [4, 5, 6],
+             [4, 7, 8]]
+    df = pd.DataFrame(array, columns=['shouldnt_be_index', 'A', 'B'])
+    groupby = df.groupby('shouldnt_be_index', as_index=as_index)
+    result = groupby.agg(['min', 'max'])
+
+    array2 = [[3, 1, 3, 2, 4],
+              [4, 5, 7, 6, 8]]
+    columns = pd.MultiIndex(levels=[['A', 'B', 'shouldnt_be_index'],
+                                    ['min', 'max', '']],
+                            codes=[[2, 0, 0, 1, 1], [2, 0, 1, 0, 1]])
+    expected = pd.DataFrame(array2, columns=columns)
+
+    tm.assert_frame_equal(result, expected)
+
+    # expected behavhior of agg with as_index=True
+    as_index = True
+    array = [[3, 1, 2],
+             [3, 3, 4],
+             [4, 5, 6],
+             [4, 7, 8]]
+    df = pd.DataFrame(array, columns=['should_be_index', 'A', 'B'])
+    groupby = df.groupby('should_be_index', as_index=as_index)
+    result = groupby.agg(['min', 'max'])
+
+    array2 = [[1, 3, 2, 4],
+              [5, 7, 6, 8]]
+    columns = pd.MultiIndex(levels=[['A', 'B'],
+                                        ['min', 'max']],
+                                codes=[[0, 0, 1, 1], [0, 1, 0, 1]])
+    index = pd.Series([3, 4], name='should_be_index')
+    expected = pd.DataFrame(array2, columns=columns, index=index)
+
+    tm.assert_frame_equal(result, expected)