TST: Add regression tests for enlarging MultiIndex with None keys (GH#59153)

pandas/tests/indexing/multiindex/test_setitem.py

@@ -173,11 +173,11 @@ def test_multiindex_setitem2(self):
         idx = pd.IndexSlice
         df = df_orig.copy()
         df.loc[idx[:, :, "Stock"], :] *= 2
-        tm.assert_frame_equal(df, expected)
+        tm.assert_frame_equal(df, expected, check_index_type=False)
 
         df = df_orig.copy()
         df.loc[idx[:, :, "Stock"], "price"] *= 2
-        tm.assert_frame_equal(df, expected)
+        tm.assert_frame_equal(df, expected, check_index_type=False)
 
     def test_multiindex_assignment(self):
         # GH3777 part 2
@@ -490,6 +490,62 @@ def test_setitem_enlargement_keep_index_names(self):
         )
         tm.assert_frame_equal(df, expected)
 
+    def test_setitem_enlargement_multiindex_with_none(self):
+        # GH#59153
+        # Test that we can enlarge a DataFrame with a MultiIndex
+        # when one or more level keys are None
+        index = MultiIndex.from_tuples(
+            [("A", "a1"), ("A", "a2"), ("B", "b1"), ("B", None)]
+        )
+        df = DataFrame([(0.0, 6.0), (1.0, 5.0), (2.0, 4.0), (3.0, 7.0)], index=index)
+
+        # Enlarge with a new index entry where one key is None
+        df.loc[("A", None), :] = [12.0, 13.0]
+
+        expected_index = MultiIndex.from_tuples(
+            [("A", "a1"), ("A", "a2"), ("B", "b1"), ("B", None), ("A", None)]
+        )
+        expected = DataFrame(
+            [[0.0, 6.0], [1.0, 5.0], [2.0, 4.0], [3.0, 7.0], [12.0, 13.0]],
+            index=expected_index,
+            columns=[0, 1],
+        )
+        # check_index_type=False because None in MultiIndex causes mixed inferred_type
+        tm.assert_frame_equal(df, expected, check_index_type=False)
+
+        # Test retrieval of the newly added row
+        result = df.loc[("A", None), :]
+        expected_row = Series([12.0, 13.0], index=[0, 1], name=("A", np.nan))
+        tm.assert_series_equal(result, expected_row)
+
+    def test_setitem_enlargement_multiindex_multiple_none(self):
+        # GH#59153
+        # Test enlarging with multiple None keys in different levels
+        index = MultiIndex.from_tuples([("A", "a1"), ("B", "b1")])
+        df = DataFrame([[1.0, 2.0], [3.0, 4.0]], index=index, columns=["x", "y"])
+
+        # Add row with None in first level
+        df.loc[(None, "c1"), :] = [5.0, 6.0]
+
+        # Add row with None in second level
+        df.loc[("C", None), :] = [7.0, 8.0]
+
+        expected_index = MultiIndex.from_tuples(
+            [
+                ("A", "a1"),
+                ("B", "b1"),
+                (None, "c1"),
+                ("C", None),
+            ]
+        )
+        expected = DataFrame(
+            [[1.0, 2.0], [3.0, 4.0], [5.0, 6.0], [7.0, 8.0]],
+            index=expected_index,
+            columns=["x", "y"],
+        )
+        # check_index_type=False because None in MultiIndex causes mixed inferred_type
+        tm.assert_frame_equal(df, expected, check_index_type=False)
+
 
 def test_frame_setitem_view_direct(multiindex_dataframe_random_data):
     # this works because we are modifying the underlying array