From 2dafa84eaecad1a15e73b944e57533a41fc16167 Mon Sep 17 00:00:00 2001
From: D067751 <fabrizio.primerano@sap.com>
Date: Fri, 21 Apr 2023 01:10:55 +0200
Subject: [PATCH] Test for #34164

---
 pandas/tests/groupby/test_groupby.py | 42 ++++++++++++++++++++++++++++
 1 file changed, 42 insertions(+)

diff --git a/pandas/tests/groupby/test_groupby.py b/pandas/tests/groupby/test_groupby.py
index b5b13d6b10511..41bd9454aa961 100644
--- a/pandas/tests/groupby/test_groupby.py
+++ b/pandas/tests/groupby/test_groupby.py
@@ -16,6 +16,7 @@
     DataFrame,
     Grouper,
     Index,
+    Interval,
     MultiIndex,
     RangeIndex,
     Series,
@@ -2970,3 +2971,44 @@ def test_groupby_numeric_only_std_no_result(numeric_only):
             ValueError, match="could not convert string to float: 'bar'"
         ):
             dfgb.std(numeric_only=numeric_only)
+
+
+def test_grouping_with_categorical_interval_columns():
+    # GH#34164
+    df = DataFrame({"x": [0.1, 0.2, 0.3, -0.4, 0.5], "w": ["a", "b", "a", "c", "a"]})
+    qq = pd.qcut(df["x"], q=np.linspace(0, 1, 5))
+    result = df.groupby([qq, "w"], observed=False)["x"].agg("mean")
+    categorical_index_level_1 = Categorical(
+        [
+            Interval(-0.401, 0.1, closed="right"),
+            Interval(0.1, 0.2, closed="right"),
+            Interval(0.2, 0.3, closed="right"),
+            Interval(0.3, 0.5, closed="right"),
+        ],
+        ordered=True,
+    )
+    index_level_2 = ["a", "b", "c"]
+    mi = MultiIndex.from_product(
+        [categorical_index_level_1, index_level_2], names=["x", "w"]
+    )
+    expected = Series(
+        np.array(
+            [
+                0.1,
+                np.nan,
+                -0.4,
+                np.nan,
+                0.2,
+                np.nan,
+                0.3,
+                np.nan,
+                np.nan,
+                0.5,
+                np.nan,
+                np.nan,
+            ]
+        ),
+        index=mi,
+        name="x",
+    )
+    tm.assert_series_equal(result, expected)