TST add test for dtype consistency with pd replace #23305

pandas/tests/frame/methods/test_replace.py

@@ -1420,3 +1420,83 @@ def test_replace_period_ignore_float(self):
         result = df.replace(1.0, 0.0)
         expected = pd.DataFrame({"Per": [pd.Period("2020-01")] * 3})
         tm.assert_frame_equal(expected, result)
+
+    def test_replace_value_category_type(self):
+        """
+        Test to ensure category dtypes are maintained
+        after replace with direct values
+        """
+
+        # create input data
+        input_dict = {
+            "col1": [1, 2, 3, 4],
+            "col2": ["a", "b", "c", "d"],
+            "col3": [1.5, 2.5, 3.5, 4.5],
+            "col4": ["cat1", "cat2", "cat3", "cat4"],
+            "col5": ["obj1", "obj2", "obj3", "obj4"],
+        }
+        # explicitly cast columns as category and order them
+        input_df = pd.DataFrame(data=input_dict).astype(
+            {"col2": "category", "col4": "category"}
+        )
+        input_df["col2"] = input_df["col2"].cat.reorder_categories(
+            ["a", "b", "c", "d"], ordered=True
+        )
+        input_df["col4"] = input_df["col4"].cat.reorder_categories(
+            ["cat1", "cat2", "cat3", "cat4"], ordered=True
+        )
+
+        # create expected dataframe
+        expected_dict = {
+            "col1": [1, 2, 3, 4],
+            "col2": ["a", "b", "c", "z"],
+            "col3": [1.5, 2.5, 3.5, 4.5],
+            "col4": ["cat1", "catX", "cat3", "cat4"],
+            "col5": ["obj9", "obj2", "obj3", "obj4"],
+        }
+        # explicitly cast columns as category and order them
+        expected_df = pd.DataFrame(data=expected_dict).astype(
+            {"col2": "category", "col4": "category"}
+        )
+        expected_df["col2"] = expected_df["col2"].cat.reorder_categories(
+            ["a", "b", "c", "z"], ordered=True
+        )
+        expected_df["col4"] = expected_df["col4"].cat.reorder_categories(
+            ["cat1", "catX", "cat3", "cat4"], ordered=True
+        )
+
+        # replace values in input dataframe
+        input_df = input_df.replace("d", "z")
+        input_df = input_df.replace("obj1", "obj9")
+        input_df = input_df.replace("cat2", "catX")
+
+        tm.assert_frame_equal(input_df, expected_df)
+
+    @pytest.mark.xfail(
+        reason="category dtype gets changed to object type after replace, see #35268",
+        strict=True,
+    )
+    def test_replace_dict_category_type(self, input_category_df, expected_category_df):
+        """
+        Test to ensure category dtypes are maintained
+        after replace with dict values
+        """
+
+        # create input dataframe
+        input_dict = {"col1": ["a"], "col2": ["obj1"], "col3": ["cat1"]}
+        # explicitly cast columns as category
+        input_df = pd.DataFrame(data=input_dict).astype(
+            {"col1": "category", "col2": "category", "col3": "category"}
+        )
+
+        # create expected dataframe
+        expected_dict = {"col1": ["z"], "col2": ["obj9"], "col3": ["catX"]}
+        # explicitly cast columns as category
+        expected_df = pd.DataFrame(data=expected_dict).astype(
+            {"col1": "category", "col2": "category", "col3": "category"}
+        )
+
+        # replace values in input dataframe using a dict
+        input_df = input_df.replace({"a": "z", "obj1": "obj9", "cat1": "catX"})
+
+        tm.assert_frame_equal(input_df, expected_df)