BUG: pd.Series.replace does not preserve the original dtype

Author: kotamatsuoka

pandas/core/internals/blocks.py

@@ -1005,8 +1005,11 @@ def coerce_to_target_dtype(self, other):
         we can also safely try to coerce to the same dtype
         and will receive the same block
         """
-        # if we cannot then coerce to object
-        dtype, _ = infer_dtype_from(other, pandas_dtype=True)
+        if type(other) == str:
+            dtype = "string"
+        else:
+            # if we cannot then coerce to object
+            dtype, _ = infer_dtype_from(other, pandas_dtype=True)
 
         if is_dtype_equal(self.dtype, dtype):
             return self

pandas/tests/series/methods/test_replace.py

@@ -406,3 +406,19 @@ def test_replace_only_one_dictlike_arg(self):
         msg = "Series.replace cannot use dict-value and non-None to_replace"
         with pytest.raises(ValueError, match=msg):
             ser.replace(to_replace, value)
+
+    @pytest.mark.parametrize(
+        "series, to_replace, expected",
+        [
+            (
+                pd.Series(["one", "two"], dtype="string"),
+                {"one": "1", "two": "2"},
+                "string",
+            ),
+            (pd.Series([1, 2], dtype="int64"), {1: 10, 2: 20}, "int64"),
+            (pd.Series([True, False], dtype="bool"), {True: False}, "bool"),
+        ],
+    )
+    def test_replace_dtype(self, series, to_replace, expected):
+        result = str(series.replace(to_replace).dtype)
+        assert expected == result