🎨 handle empty in , make whatsnewentry public-facing

Author: Marco Gorelli

doc/source/whatsnew/v1.0.0.rst

@@ -1132,7 +1132,7 @@ Groupby/resample/rolling
 - Bug in :meth:`DataFrame.groupby` when using nunique on axis=1 (:issue:`30253`)
 - Bug in :meth:`GroupBy.quantile` with multiple list-like q value and integer column names (:issue:`30289`)
 - Bug in :meth:`GroupBy.pct_change` and :meth:`core.groupby.SeriesGroupBy.pct_change` causes ``TypeError`` when ``fill_method`` is ``None`` (:issue:`30463`)
-- Bug in :meth:`SeriesGroupBy._aggregate_multiple_funcs` was resulting in aggregations being overwritten when they shared the same name (:issue:`30092`)
+- Bug in :meth:`SeriesGroupBy.aggregate` was resulting in aggregations being overwritten when they shared the same name (:issue:`30092`)
 
 Reshaping
 ^^^^^^^^^

pandas/core/groupby/generic.py

@@ -311,7 +311,7 @@ def _aggregate_multiple_funcs(self, arg):
 
             arg = zip(columns, arg)
 
-        results = {}
+        results: Mapping[base.OutputKey, Union[Series, DataFrame]] = {}
         for idx, (name, func) in enumerate(arg):
             obj = self
 
@@ -326,10 +326,7 @@ def _aggregate_multiple_funcs(self, arg):
         if any(isinstance(x, DataFrame) for x in results.values()):
             # let higher level handle
             return {key.label: value for key, value in results.items()}
-
-        if results:
-            return DataFrame(self._wrap_aggregated_output(results), columns=columns)
-        return DataFrame(columns=columns)
+        return DataFrame(self._wrap_aggregated_output(results), columns=columns)
 
     def _wrap_series_output(
         self, output: Mapping[base.OutputKey, Union[Series, np.ndarray]], index: Index
@@ -360,8 +357,10 @@ def _wrap_series_output(
         if len(output) > 1:
             result = DataFrame(indexed_output, index=index)
             result.columns = columns
-        else:
+        elif not columns.empty:
             result = Series(indexed_output[0], index=index, name=columns[0])
+        else:
+            result = DataFrame()
 
         return result