BUG: Fix inconsistent returned objects when applying groupby aggregations (pandas-dev#61508)

* Wrapped return object

* Added tests

* Whatsnew

* pre-commit

Author: arthurlw

doc/source/whatsnew/v3.0.0.rst

@@ -825,6 +825,7 @@ Groupby/resample/rolling
 - Bug in :meth:`DataFrame.resample` and :meth:`Series.resample` were not keeping the index name when the index had :class:`ArrowDtype` timestamp dtype (:issue:`61222`)
 - Bug in :meth:`DataFrame.resample` changing index type to :class:`MultiIndex` when the dataframe is empty and using an upsample method (:issue:`55572`)
 - Bug in :meth:`DataFrameGroupBy.agg` that raises ``AttributeError`` when there is dictionary input and duplicated columns, instead of returning a DataFrame with the aggregation of all duplicate columns. (:issue:`55041`)
+- Bug in :meth:`DataFrameGroupBy.agg` where applying a user-defined function to an empty DataFrame returned a Series instead of an empty DataFrame. (:issue:`61503`)
 - Bug in :meth:`DataFrameGroupBy.apply` and :meth:`SeriesGroupBy.apply` for empty data frame with ``group_keys=False`` still creating output index using group keys. (:issue:`60471`)
 - Bug in :meth:`DataFrameGroupBy.apply` that was returning a completely empty DataFrame when all return values of ``func`` were ``None`` instead of returning an empty DataFrame with the original columns and dtypes. (:issue:`57775`)
 - Bug in :meth:`DataFrameGroupBy.apply` with ``as_index=False`` that was returning :class:`MultiIndex` instead of returning :class:`Index`. (:issue:`58291`)

pandas/core/groupby/generic.py

@@ -504,11 +504,13 @@ def aggregate(self, func=None, *args, engine=None, engine_kwargs=None, **kwargs)
                 #  inference. We default to using the existing dtype.
                 #  xref GH#51445
                 obj = self._obj_with_exclusions
-                return self.obj._constructor(
-                    [],
-                    name=self.obj.name,
-                    index=self._grouper.result_index,
-                    dtype=obj.dtype,
+                return self._wrap_aggregated_output(
+                    self.obj._constructor(
+                        [],
+                        name=self.obj.name,
+                        index=self._grouper.result_index,
+                        dtype=obj.dtype,
+                    )
                 )
             return self._python_agg_general(func, *args, **kwargs)
 

pandas/tests/groupby/aggregate/test_aggregate.py

@@ -1807,3 +1807,20 @@ def test_groupby_aggregation_func_list_multi_index_duplicate_columns():
         index=Index(["level1.1", "level1.2"]),
     )
     tm.assert_frame_equal(result, expected)
+
+
+def test_groupby_aggregate_empty_builtin_sum():
+    df = DataFrame(columns=["Group", "Data"])
+    result = df.groupby(["Group"], as_index=False)["Data"].agg("sum")
+    expected = DataFrame(columns=["Group", "Data"])
+    tm.assert_frame_equal(result, expected)
+
+
+def test_groupby_aggregate_empty_udf():
+    def func(x):
+        return sum(x)
+
+    df = DataFrame(columns=["Group", "Data"])
+    result = df.groupby(["Group"], as_index=False)["Data"].agg(func)
+    expected = DataFrame(columns=["Group", "Data"])
+    tm.assert_frame_equal(result, expected)