BUG: RecursionError when attempting to replace np.nan values (pandas-dev#45725)

Author: roib20

pandas/tests/frame/methods/test_replace.py

@@ -661,16 +661,13 @@ def test_replace_simple_nested_dict_with_nonexistent_value(self):
         result = df.replace({"col": {-1: "-", 1: "a", 4: "b"}})
         tm.assert_frame_equal(expected, result)
 
-    def test_replace_numpy_nan(self):
-        # GH#45725 ensure np.nan can be replaced with pd.NA
-        df = pd.DataFrame({"A": [np.nan], "B": [np.nan]}, dtype=object)
-        result = df.replace({np.nan: pd.NA})
-        expected = pd.DataFrame({"A": [pd.NA], "B": [pd.NA]}, dtype=object)
-        tm.assert_frame_equal(result, expected)
-
-        # same thing but with None
-        result = df.replace({np.nan: None})
-        expected = pd.DataFrame({"A": [None], "B": [None]}, dtype=object)
+    @pytest.mark.parametrize("dtype", [object])
+    @pytest.mark.parametrize("to_replace, value", [(np.nan, pd.NA), (np.nan, None)])
+    def test_replace_numpy_nan(self, dtype, to_replace, value):
+        # GH#45725 ensure numpy.nan can be replaced with pandas.NA or None
+        df = pd.DataFrame({"A": [to_replace]}, dtype=dtype)
+        result = df.replace({to_replace: value})
+        expected = pd.DataFrame({"A": [value]}, dtype=dtype)
         tm.assert_frame_equal(result, expected)
 
     def test_replace_value_is_none(self, datetime_frame):

pandas/tests/series/methods/test_replace.py

@@ -36,17 +36,13 @@ def test_replace_explicit_none(self):
         assert expected.iloc[-1] is None
         tm.assert_series_equal(result, expected)
 
-    def test_replace_numpy_nan(self):
-        # GH#45725 ensure np.nan can be replaced
-        ser = pd.Series([np.nan, np.nan], dtype=object)
-        result = ser.replace({np.nan: pd.NA})
-        expected = pd.Series([pd.NA, pd.NA], dtype=object)
-        tm.assert_series_equal(result, expected)
-        assert result.dtype == object
-
-        # same thing but with None
-        result = ser.replace({np.nan: None})
-        expected = pd.Series([None, None], dtype=object)
+    @pytest.mark.parametrize("dtype", [object])
+    @pytest.mark.parametrize("to_replace, value", [(np.nan, pd.NA), (np.nan, None)])
+    def test_replace_numpy_nan(self, dtype, to_replace, value):
+        # GH#45725 ensure numpy.nan can be replaced with pandas.NA or None
+        ser = pd.Series([to_replace], dtype=dtype)
+        result = ser.replace({to_replace: value})
+        expected = pd.Series([value], dtype=dtype)
         tm.assert_series_equal(result, expected)
         assert result.dtype == object