BUG: Fix BaseWindowGroupby.aggregate where as_index is ignored

doc/source/whatsnew/v2.2.0.rst

@@ -168,6 +168,7 @@ Performance improvements
 Bug fixes
 ~~~~~~~~~
 - Bug in :class:`AbstractHolidayCalendar` where timezone data was not propagated when computing holiday observances (:issue:`54580`)
+- Bug in :meth:`BaseWindowGroupby.aggregate` where ``_as_index`` attribute is ignored (:issue:`31007`)
 
 Categorical
 ^^^^^^^^^^^

pandas/core/window/ewm.py

@@ -919,6 +919,12 @@ def _get_window_indexer(self) -> GroupbyIndexer:
         )
         return window_indexer
 
+    @doc(_shared_docs["aggregate"])
+    def aggregate(self, func, *args, **kwargs):
+        return super().aggregate(func, *args, **kwargs)
+
+    agg = aggregate
+
 
 class OnlineExponentialMovingWindow(ExponentialMovingWindow):
     def __init__(

pandas/core/window/expanding.py

@@ -962,3 +962,9 @@ def _get_window_indexer(self) -> GroupbyIndexer:
             window_indexer=ExpandingIndexer,
         )
         return window_indexer
+
+    @doc(_shared_docs["aggregate"])
+    def aggregate(self, func, *args, **kwargs):
+        return super().aggregate(func, *args, **kwargs)
+
+    agg = aggregate

pandas/core/window/rolling.py

@@ -875,6 +875,14 @@ def _gotitem(self, key, ndim, subset=None):
             subset = self.obj.set_index(self._on)
         return super()._gotitem(key, ndim, subset=subset)
 
+    def aggregate(self, func, *args, **kwargs):
+        result = super().aggregate(func, *args, **kwargs)
+        if not self._as_index:
+            result = result.reset_index(level=list(range(len(self._grouper.names))))
+        return result
+
+    agg = aggregate
+
 
 class Window(BaseWindow):
     """
@@ -2911,3 +2919,9 @@ def _validate_datetimelike_monotonic(self):
                     f"Each group within {on} must be monotonic. "
                     f"Sort the values in {on} first."
                 )
+
+    @doc(_shared_docs["aggregate"])
+    def aggregate(self, func, *args, **kwargs):
+        return super().aggregate(func, *args, **kwargs)
+
+    agg = aggregate

pandas/tests/window/test_groupby.py

@@ -846,10 +846,20 @@ def test_groupby_level(self):
         tm.assert_series_equal(result, expected)
 
     @pytest.mark.parametrize(
-        "by, expected_data",
+        "func, by, expected_data",
         [
-            [["id"], {"num": [100.0, 150.0, 150.0, 200.0]}],
             [
+                lambda x: x.agg({"num": "mean"}),
+                ["id"],
+                {"num": [100.0, 150.0, 150.0, 200.0]},
+            ],
+            [
+                lambda x: x.mean(),
+                ["id"],
+                {"num": [100.0, 150.0, 150.0, 200.0]},
+            ],
+            [
+                lambda x: x.mean(),
                 ["id", "index"],
                 {
                     "date": [
@@ -863,8 +873,8 @@ def test_groupby_level(self):
             ],
         ],
     )
-    def test_as_index_false(self, by, expected_data):
-        # GH 39433
+    def test_as_index_false(self, func, by, expected_data):
+        # GH 39433, 31007
         data = [
             ["A", "2018-01-01", 100.0],
             ["A", "2018-01-02", 200.0],
@@ -876,8 +886,8 @@ def test_as_index_false(self, by, expected_data):
         df = df.set_index(["date"])
 
         gp_by = [getattr(df, attr) for attr in by]
-        result = (
-            df.groupby(gp_by, as_index=False).rolling(window=2, min_periods=1).mean()
+        result = func(
+            df.groupby(gp_by, as_index=False).rolling(window=2, min_periods=1)
         )
 
         expected = {"id": ["A", "A", "B", "B"]}