diff --git a/pandas/core/groupby/generic.py b/pandas/core/groupby/generic.py
index fd07b472fc3da..3850f6bc12efd 100644
--- a/pandas/core/groupby/generic.py
+++ b/pandas/core/groupby/generic.py
@@ -269,11 +269,8 @@ def aggregate(self, func=None, *args, engine=None, engine_kwargs=None, **kwargs)
                 result = self._aggregate_named(func, *args, **kwargs)
 
                 # result is a dict whose keys are the elements of result_index
-                index = self.grouper.result_index
-                result = Series(result, index=index)
-                if not self.as_index:
-                    result = self._insert_inaxis_grouper(result)
-                    result.index = default_index(len(result))
+                result = Series(result, index=self.grouper.result_index)
+                result = self._wrap_aggregated_output(result)
                 return result
 
     agg = aggregate
@@ -1314,19 +1311,9 @@ def aggregate(self, func=None, *args, engine=None, engine_kwargs=None, **kwargs)
                     result = self._aggregate_frame(func)
 
                 else:
-                    sobj = self._selected_obj
-
-                    if isinstance(sobj, Series):
-                        # GH#35246 test_groupby_as_index_select_column_sum_empty_df
-                        result.columns = self._obj_with_exclusions.columns.copy()
-                    else:
-                        # Retain our column names
-                        result.columns._set_names(
-                            sobj.columns.names, level=list(range(sobj.columns.nlevels))
-                        )
-                        # select everything except for the last level, which is the one
-                        # containing the name of the function(s), see GH#32040
-                        result.columns = result.columns.droplevel(-1)
+                    # GH#32040, GH#35246
+                    # e.g. test_groupby_as_index_select_column_sum_empty_df
+                    result.columns = self._obj_with_exclusions.columns.copy()
 
         if not self.as_index:
             result = self._insert_inaxis_grouper(result)
@@ -1358,17 +1345,9 @@ def _aggregate_frame(self, func, *args, **kwargs) -> DataFrame:
         obj = self._obj_with_exclusions
 
         result: dict[Hashable, NDFrame | np.ndarray] = {}
-        if self.axis == 0:
-            # test_pass_args_kwargs_duplicate_columns gets here with non-unique columns
-            for name, data in self.grouper.get_iterator(obj, self.axis):
-                fres = func(data, *args, **kwargs)
-                result[name] = fres
-        else:
-            # we get here in a number of test_multilevel tests
-            for name in self.indices:
-                grp_df = self.get_group(name, obj=obj)
-                fres = func(grp_df, *args, **kwargs)
-                result[name] = fres
+        for name, grp_df in self.grouper.get_iterator(obj, self.axis):
+            fres = func(grp_df, *args, **kwargs)
+            result[name] = fres
 
         result_index = self.grouper.result_index
         other_ax = obj.axes[1 - self.axis]