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

Author: roib20

doc/source/whatsnew/v1.5.0.rst

@@ -193,6 +193,7 @@ Other Deprecations
 - Deprecated :meth:`DataFrame.iteritems`, :meth:`Series.iteritems`, :meth:`HDFStore.iteritems` in favor of :meth:`DataFrame.items`, :meth:`Series.items`, :meth:`HDFStore.items`  (:issue:`45321`)
 - Deprecated :meth:`Series.is_monotonic` and :meth:`Index.is_monotonic` in favor of :meth:`Series.is_monotonic_increasing` and :meth:`Index.is_monotonic_increasing` (:issue:`45422`, :issue:`21335`)
 - Deprecated the ``__array_wrap__`` method of DataFrame and Series, rely on standard numpy ufuncs instead (:issue:`45451`)
+- Deprecated the behavior of :meth:`Series.fillna` and :meth:`DataFrame.fillna` with ``timedelta64[ns]`` dtype and incompatible fill value; in a future version this will cast to a common dtype (usually object) instead of raising, matching the behavior of other dtypes (:issue:`45746`)
 -
 
 
@@ -248,7 +249,6 @@ Conversion
 - Bug in :meth:`Series.astype` and :meth:`DataFrame.astype` from floating dtype to unsigned integer dtype failing to raise in the presence of negative values (:issue:`45151`)
 - Bug in :func:`array` with ``FloatingDtype`` and values containing float-castable strings incorrectly raising (:issue:`45424`)
 - Bug when comparing string and datetime64ns objects causing ``OverflowError`` exception. (:issue:`45506`)
-- Bug when attempting to replace ``numpy.nan`` values causing ``RecursionError``
 
 Strings
 ^^^^^^^

pandas/tests/frame/methods/test_replace.py

@@ -661,12 +661,19 @@ 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)
 
-    @pytest.mark.parametrize("to_replace, value", [(np.nan, pd.NA), (np.nan, None)])
-    def test_replace_numpy_nan(self, to_replace, value):
-        # GH#45725 ensure numpy.nan can be replaced with pandas.NA or None
-        df = DataFrame({"A": [to_replace]}, dtype=object)
-        result = df.replace({to_replace: value})
-        expected = DataFrame({"A": [value]}, dtype=object)
+    def test_replace_numpy_nan(self, nulls_fixture):
+        # GH#45725 ensure numpy.nan can be replaced with all other null types
+        to_replace = np.nan
+        value = nulls_fixture
+        dtype = object
+        df = DataFrame({"A": [to_replace]}, dtype=dtype)
+        expected = DataFrame({"A": [value]}, dtype=dtype)
+
+        result = df.replace({to_replace: value}).astype(dtype=dtype)
+        tm.assert_frame_equal(result, expected)
+
+        # same thing but different calling convention
+        result = df.replace(to_replace, value).astype(dtype=dtype)
         tm.assert_frame_equal(result, expected)
 
     def test_replace_value_is_none(self, datetime_frame):

pandas/tests/series/methods/test_replace.py

@@ -36,14 +36,22 @@ def test_replace_explicit_none(self):
         assert expected.iloc[-1] is None
         tm.assert_series_equal(result, expected)
 
-    @pytest.mark.parametrize("to_replace, value", [(np.nan, pd.NA), (np.nan, None)])
-    def test_replace_numpy_nan(self, to_replace, value):
-        # GH#45725 ensure numpy.nan can be replaced with pandas.NA or None
-        ser = pd.Series([to_replace], dtype=object)
-        result = ser.replace({to_replace: value})
-        expected = pd.Series([value], dtype=object)
+    def test_replace_numpy_nan(self, nulls_fixture):
+        # GH#45725 ensure numpy.nan can be replaced with all other null types
+        to_replace = np.nan
+        value = nulls_fixture
+        dtype = object
+        ser = pd.Series([to_replace], dtype=dtype)
+        expected = pd.Series([value], dtype=dtype)
+
+        result = ser.replace({to_replace: value}).astype(dtype=dtype)
         tm.assert_series_equal(result, expected)
-        assert result.dtype == object
+        assert result.dtype == dtype
+
+        # same thing but different calling convention
+        result = ser.replace(to_replace, value).astype(dtype=dtype)
+        tm.assert_series_equal(result, expected)
+        assert result.dtype == dtype
 
     def test_replace_noop_doesnt_downcast(self):
         # GH#44498