TST: Tests for replace method when column contains pd.NA (#47480)

pandas/core/missing.py

@@ -88,12 +88,15 @@ def mask_missing(arr: ArrayLike, values_to_mask) -> npt.NDArray[np.bool_]:
 
     # GH 21977
     mask = np.zeros(arr.shape, dtype=bool)
+    arr_na_mask = ~isna(arr)
     for x in nonna:
         if is_numeric_v_string_like(arr, x):
             # GH#29553 prevent numpy deprecation warnings
             pass
         else:
-            new_mask = arr == x
+            # GH#47480
+            new_mask = np.zeros_like(arr, dtype=bool)
+            new_mask[arr_na_mask] = arr[arr_na_mask] == x
             if not isinstance(new_mask, np.ndarray):
                 # usually BooleanArray
                 new_mask = new_mask.to_numpy(dtype=bool, na_value=False)

pandas/tests/frame/methods/test_replace.py

@@ -1503,6 +1503,14 @@ def test_replace_value_none_dtype_numeric(self, val):
         result = df.replace({val: None})
         tm.assert_frame_equal(result, expected)
 
+    @pytest.mark.parametrize("dtype", [None, "Int64", "Float64"])
+    def test_replace_df_containing_na(self, dtype):
+        # GH#47480
+        df = DataFrame({"A": [4, 1, pd.NA], "B": [1, 3, 2]}, dtype=dtype)
+        df.replace(to_replace=1, value=100, inplace=True)
+        expected = DataFrame({"A": [4, 100, pd.NA], "B": [100, 3, 2]}, dtype=dtype)
+        tm.assert_frame_equal(df, expected)
+
 
 class TestDataFrameReplaceRegex:
     @pytest.mark.parametrize(

pandas/tests/series/methods/test_replace.py

@@ -674,3 +674,11 @@ def test_replace_value_none_dtype_numeric(self, val):
         result = ser.replace(val, None)
         expected = pd.Series([1, None], dtype=object)
         tm.assert_series_equal(result, expected)
+
+    @pytest.mark.parametrize("dtype", [None, "Int64", "Float64"])
+    def test_replace_series_containing_na(self, dtype):
+        # GH#47480
+        df = pd.Series([4, 1, pd.NA, 1], dtype=dtype)
+        df.replace(to_replace=1, value=100, inplace=True)
+        expected = pd.Series([4, 100, pd.NA, 100], dtype=dtype)
+        tm.assert_series_equal(df, expected)