REF: avoid object-dtype casting in Block.replace

pandas/core/internals/blocks.py

@@ -796,7 +796,6 @@ def replace(
         It is used in ObjectBlocks.  It is here for API compatibility.
         """
         inplace = validate_bool_kwarg(inplace, "inplace")
-        original_to_replace = to_replace
 
         if not self._can_hold_element(to_replace):
             # We cannot hold `to_replace`, so we know immediately that
@@ -814,17 +813,28 @@ def replace(
             return [self] if inplace else [self.copy()]
 
         if not self._can_hold_element(value):
-            blk = self.astype(object)
+            if self.ndim == 2 and self.shape[0] > 1:
+                # split so that we only upcast where necessary
+                nbs = self._split()
+                res_blocks = extend_blocks(
+                    [
+                        blk.replace(to_replace, value, inplace=inplace, regex=regex)
+                        for blk in nbs
+                    ]
+                )
+                return res_blocks
+
+            blk = self.coerce_to_target_dtype(value)
             return blk.replace(
-                to_replace=original_to_replace,
+                to_replace=to_replace,
                 value=value,
                 inplace=True,
                 regex=regex,
             )
 
         blk = self if inplace else self.copy()
         putmask_inplace(blk.values, mask, value)
-        blocks = blk.convert(numeric=False, copy=not inplace)
+        blocks = blk.convert(numeric=False, copy=False)
         return blocks
 
     @final
@@ -867,11 +877,7 @@ def _replace_regex(
         replace_regex(new_values, rx, value, mask)
 
         block = self.make_block(new_values)
-        if convert:
-            nbs = block.convert(numeric=False)
-        else:
-            nbs = [block]
-        return nbs
+        return [block]
 
     @final
     def _replace_list(

pandas/tests/frame/methods/test_fillna.py

@@ -265,12 +265,13 @@ def test_fillna_dtype_conversion(self):
         expected = DataFrame("nan", index=range(3), columns=["A", "B"])
         tm.assert_frame_equal(result, expected)
 
-        # equiv of replace
+    @td.skip_array_manager_not_yet_implemented  # TODO(ArrayManager) object upcasting
+    @pytest.mark.parametrize("val", ["", 1, np.nan, 1.0])
+    def test_fillna_dtype_conversion_equiv_replace(self, val):
         df = DataFrame({"A": [1, np.nan], "B": [1.0, 2.0]})
-        for v in ["", 1, np.nan, 1.0]:
-            expected = df.replace(np.nan, v)
-            result = df.fillna(v)
-            tm.assert_frame_equal(result, expected)
+        expected = df.replace(np.nan, val)
+        result = df.fillna(val)
+        tm.assert_frame_equal(result, expected)
 
     @td.skip_array_manager_invalid_test
     def test_fillna_datetime_columns(self):

pandas/tests/frame/methods/test_replace.py

@@ -783,6 +783,8 @@ def test_replace_mixed(self, float_string_frame):
         tm.assert_frame_equal(result, expected)
         tm.assert_frame_equal(result.replace(-1e8, np.nan), float_string_frame)
 
+    def test_replace_mixed_int_block_upcasting(self):
+
         # int block upcasting
         df = DataFrame(
             {
@@ -803,6 +805,8 @@ def test_replace_mixed(self, float_string_frame):
         assert return_value is None
         tm.assert_frame_equal(df, expected)
 
+    def test_replace_mixed_int_block_splitting(self):
+
         # int block splitting
         df = DataFrame(
             {
@@ -821,6 +825,8 @@ def test_replace_mixed(self, float_string_frame):
         result = df.replace(0, 0.5)
         tm.assert_frame_equal(result, expected)
 
+    def test_replace_mixed2(self):
+
         # to object block upcasting
         df = DataFrame(
             {
@@ -846,6 +852,7 @@ def test_replace_mixed(self, float_string_frame):
         result = df.replace([1, 2], ["foo", "bar"])
         tm.assert_frame_equal(result, expected)
 
+    def test_replace_mixed3(self):
         # test case from
         df = DataFrame(
             {"A": Series([3, 0], dtype="int64"), "B": Series([0, 3], dtype="int64")}