REGR: Fix regression RecursionError when replacing numeric scalar with None

doc/source/whatsnew/v1.5.1.rst

@@ -73,6 +73,7 @@ Fixed regressions
 - Fixed Regression in :meth:`DataFrame.loc` when setting values as a :class:`DataFrame` with all ``True`` indexer (:issue:`48701`)
 - Regression in :func:`.read_csv` causing an ``EmptyDataError`` when using an UTF-8 file handle that was already read from (:issue:`48646`)
 - Regression in :func:`to_datetime` when ``utc=True`` and ``arg`` contained timezone naive and aware arguments raised a ``ValueError`` (:issue:`48678`)
+- Fixed regression in :meth:`Series.replace` raising ``RecursionError`` with numeric dtype and when specifying ``value=None`` (:issue:`45725`)
 - Fixed regression in :meth:`DataFrame.loc` raising ``FutureWarning`` when setting an empty :class:`DataFrame` (:issue:`48480`)
 - Fixed regression in :meth:`DataFrame.describe` raising ``TypeError`` when result contains ``NA`` (:issue:`48778`)
 - Fixed regression in :meth:`DataFrame.plot` ignoring invalid ``colormap`` for ``kind="scatter"`` (:issue:`48726`)

pandas/core/internals/blocks.py

@@ -573,7 +573,6 @@ def replace(
         # Note: the checks we do in NDFrame.replace ensure we never get
         #  here with listlike to_replace or value, as those cases
         #  go through replace_list
-
         values = self.values
 
         if isinstance(values, Categorical):
@@ -612,7 +611,10 @@ def replace(
             return blocks
 
         elif self.ndim == 1 or self.shape[0] == 1:
-            blk = self.coerce_to_target_dtype(value)
+            if value is None:
+                blk = self.astype(np.dtype(object))
+            else:
+                blk = self.coerce_to_target_dtype(value)
             return blk.replace(
                 to_replace=to_replace,
                 value=value,

pandas/tests/frame/methods/test_replace.py

@@ -1496,6 +1496,18 @@ def test_replace_list_with_mixed_type(
         result = obj.replace(box(to_replace), value)
         tm.assert_equal(result, expected)
 
+    @pytest.mark.parametrize("val", [2, np.nan, 2.0])
+    def test_replace_value_none_dtype_numeric(self, val):
+        # GH#48231
+        df = DataFrame({"a": [1, val]})
+        result = df.replace(val, None)
+        expected = DataFrame({"a": [1, None]}, dtype=object)
+        tm.assert_frame_equal(result, expected)
+
+        df = DataFrame({"a": [1, val]})
+        result = df.replace({val: None})
+        tm.assert_frame_equal(result, expected)
+
 
 class TestDataFrameReplaceRegex:
     @pytest.mark.parametrize(

pandas/tests/series/methods/test_replace.py

@@ -667,3 +667,11 @@ def test_replace_different_int_types(self, any_int_numpy_dtype):
         result = labs.replace(map_dict)
         expected = labs.replace({0: 0, 2: 1, 1: 2})
         tm.assert_series_equal(result, expected)
+
+    @pytest.mark.parametrize("val", [2, np.nan, 2.0])
+    def test_replace_value_none_dtype_numeric(self, val):
+        # GH#48231
+        ser = pd.Series([1, val])
+        result = ser.replace(val, None)
+        expected = pd.Series([1, None], dtype=object)
+        tm.assert_series_equal(result, expected)