BUG: GroupbyRolling with an empty frame (pandas-dev#36208)

Co-authored-by: Matt Roeschke <[email protected]>

doc/source/whatsnew/v1.1.2.rst

@@ -24,7 +24,7 @@ Fixed regressions
 - Fix regression in pickle roundtrip of the ``closed`` attribute of :class:`IntervalIndex` (:issue:`35658`)
 - Fixed regression in :meth:`DataFrameGroupBy.agg` where a ``ValueError: buffer source array is read-only`` would be raised when the underlying array is read-only (:issue:`36014`)
 - Fixed regression in :meth:`Series.groupby.rolling` number of levels of :class:`MultiIndex` in input was compressed to one (:issue:`36018`)
--
+- Fixed regression in :class:`DataFrameGroupBy` on an empty :class:`DataFrame` (:issue:`36197`)
 
 .. ---------------------------------------------------------------------------
 

pandas/core/window/rolling.py

@@ -2240,10 +2240,12 @@ def _create_blocks(self, obj: FrameOrSeriesUnion):
         """
         # Ensure the object we're rolling over is monotonically sorted relative
         # to the groups
-        groupby_order = np.concatenate(
-            list(self._groupby.grouper.indices.values())
-        ).astype(np.int64)
-        obj = obj.take(groupby_order)
+        # GH 36197
+        if not obj.empty:
+            groupby_order = np.concatenate(
+                list(self._groupby.grouper.indices.values())
+            ).astype(np.int64)
+            obj = obj.take(groupby_order)
         return super()._create_blocks(obj)
 
     def _get_cython_func_type(self, func: str) -> Callable:

pandas/tests/window/test_grouper.py

@@ -393,3 +393,15 @@ def test_groupby_rolling_index_changed(self, func):
             name="a",
         )
         tm.assert_series_equal(result, expected)
+
+    def test_groupby_rolling_empty_frame(self):
+        # GH 36197
+        expected = pd.DataFrame({"s1": []})
+        result = expected.groupby("s1").rolling(window=1).sum()
+        expected.index = pd.MultiIndex.from_tuples([], names=["s1", None])
+        tm.assert_frame_equal(result, expected)
+
+        expected = pd.DataFrame({"s1": [], "s2": []})
+        result = expected.groupby(["s1", "s2"]).rolling(window=1).sum()
+        expected.index = pd.MultiIndex.from_tuples([], names=["s1", "s2", None])
+        tm.assert_frame_equal(result, expected)