sort_index not sorting when multi-index made by different categorical types

pandas/tests/groupby/test_groupby.py

@@ -146,6 +146,33 @@ def func(dataf):
     assert isinstance(result, DataFrame)
 
 
+def test_multi_index_sort():
+    # GH 24271
+    df = DataFrame(
+        {
+            "group": ["A"] * 6 + ["B"] * 6,
+            "dose": ["high", "med", "low"] * 4,
+            "outcomes": np.arange(12.0),
+        }
+    )
+
+    df.dose = pd.Categorical(df.dose, categories=["low", "med", "high"], ordered=True)
+
+    result = df.groupby("group")["dose"].value_counts()
+    result = result.sort_index(level=0, sort_remaining=True)
+    index = [
+        ("A", "low"),
+        ("A", "med"),
+        ("A", "high"),
+        ("B", "low"),
+        ("B", "med"),
+        ("B", "high"),
+    ]
+    index = MultiIndex.from_tuples(index, names=["group", "dose"])
+    expected = Series([2] * 6, index=index, name="dose")
+    tm.assert_series_equal(result, expected)
+
+
 def test_inconsistent_return_type():
     # GH5592
     # inconsistent return type