From 384bc7bd85116a458cdd9a30cf94279aed391a0f Mon Sep 17 00:00:00 2001
From: Matthew Roeschke <emailformattr@gmail.com>
Date: Thu, 6 Aug 2020 10:45:19 -0700
Subject: [PATCH] Backport PR #35513: BUG: RollingGroupby respects __getitem__

---
 doc/source/whatsnew/v1.1.1.rst      |  3 +--
 pandas/core/window/rolling.py       |  4 ++++
 pandas/tests/window/test_grouper.py | 25 +++++++++++++++++++++++++
 3 files changed, 30 insertions(+), 2 deletions(-)

diff --git a/doc/source/whatsnew/v1.1.1.rst b/doc/source/whatsnew/v1.1.1.rst
index 6a327a4fc732f..5e36bfe6b6307 100644
--- a/doc/source/whatsnew/v1.1.1.rst
+++ b/doc/source/whatsnew/v1.1.1.rst
@@ -16,8 +16,7 @@ Fixed regressions
 ~~~~~~~~~~~~~~~~~
 
 - Fixed regression where :func:`read_csv` would raise a ``ValueError`` when ``pandas.options.mode.use_inf_as_na`` was set to ``True`` (:issue:`35493`).
--
--
+- Fixed regression in :class:`pandas.core.groupby.RollingGroupby` where column selection was ignored (:issue:`35486`)
 
 .. ---------------------------------------------------------------------------
 
diff --git a/pandas/core/window/rolling.py b/pandas/core/window/rolling.py
index 445f179248226..87bcaa7d9512f 100644
--- a/pandas/core/window/rolling.py
+++ b/pandas/core/window/rolling.py
@@ -2220,6 +2220,10 @@ def _apply(
     def _constructor(self):
         return Rolling
 
+    @cache_readonly
+    def _selected_obj(self):
+        return self._groupby._selected_obj
+
     def _create_blocks(self, obj: FrameOrSeries):
         """
         Split data into blocks & return conformed data.
diff --git a/pandas/tests/window/test_grouper.py b/pandas/tests/window/test_grouper.py
index 744ca264e91d9..ca5a9eccea4f5 100644
--- a/pandas/tests/window/test_grouper.py
+++ b/pandas/tests/window/test_grouper.py
@@ -214,3 +214,28 @@ def foo(x):
             name="value",
         )
         tm.assert_series_equal(result, expected)
+
+    def test_groupby_subselect_rolling(self):
+        # GH 35486
+        df = DataFrame(
+            {"a": [1, 2, 3, 2], "b": [4.0, 2.0, 3.0, 1.0], "c": [10, 20, 30, 20]}
+        )
+        result = df.groupby("a")[["b"]].rolling(2).max()
+        expected = DataFrame(
+            [np.nan, np.nan, 2.0, np.nan],
+            columns=["b"],
+            index=pd.MultiIndex.from_tuples(
+                ((1, 0), (2, 1), (2, 3), (3, 2)), names=["a", None]
+            ),
+        )
+        tm.assert_frame_equal(result, expected)
+
+        result = df.groupby("a")["b"].rolling(2).max()
+        expected = Series(
+            [np.nan, np.nan, 2.0, np.nan],
+            index=pd.MultiIndex.from_tuples(
+                ((1, 0), (2, 1), (2, 3), (3, 2)), names=["a", None]
+            ),
+            name="b",
+        )
+        tm.assert_series_equal(result, expected)