REGR: Replace changes the dtype of other columns

doc/source/whatsnew/v1.4.3.rst

@@ -14,6 +14,7 @@ including other versions of pandas.
 
 Fixed regressions
 ~~~~~~~~~~~~~~~~~
+- Fixed regression in :meth:`DataFrame.replace` when the replacement value was explicitly ``None`` when passed in a dictionary to ``to_replace`` also casting other columns to object dtype even when there were no values to replace (:issue:`46634`)
 - Fixed regression in :meth:`DataFrame.nsmallest` led to wrong results when ``np.nan`` in the sorting column (:issue:`46589`)
 - Fixed regression in :func:`read_fwf` raising ``ValueError`` when ``widths`` was specified with ``usecols`` (:issue:`46580`)
 -

pandas/core/internals/blocks.py

@@ -781,12 +781,14 @@ def _replace_coerce(
             )
         else:
             if value is None:
-                # gh-45601, gh-45836
-                nb = self.astype(np.dtype(object), copy=False)
-                if nb is self and not inplace:
-                    nb = nb.copy()
-                putmask_inplace(nb.values, mask, value)
-                return [nb]
+                # gh-45601, gh-45836, gh-46634
+                if mask.any():
+                    nb = self.astype(np.dtype(object), copy=False)
+                    if nb is self and not inplace:
+                        nb = nb.copy()
+                    putmask_inplace(nb.values, mask, value)
+                    return [nb]
+                return [self] if inplace else [self.copy()]
             return self.replace(
                 to_replace=to_replace, value=value, inplace=inplace, mask=mask
             )

pandas/tests/frame/methods/test_replace.py

@@ -675,6 +675,25 @@ def test_replace_NAT_with_None(self):
         expected = DataFrame([None, None])
         tm.assert_frame_equal(result, expected)
 
+    def test_replace_with_None_keeps_categorical(self):
+        # gh-46634
+        cat_series = Series(["b", "b", "b", "d"], dtype="category")
+        df = DataFrame(
+            {
+                "id": Series([5, 4, 3, 2], dtype="float64"),
+                "col": cat_series,
+            }
+        )
+        result = df.replace({3: None})
+
+        expected = DataFrame(
+            {
+                "id": Series([5.0, 4.0, None, 2.0], dtype="object"),
+                "col": cat_series,
+            }
+        )
+        tm.assert_frame_equal(result, expected)
+
     def test_replace_value_is_none(self, datetime_frame):
         orig_value = datetime_frame.iloc[0, 0]
         orig2 = datetime_frame.iloc[1, 0]