ENH: Allow dictionaries to be passed to pandas.Series.str.replace

doc/source/whatsnew/v2.2.0.rst

@@ -193,6 +193,7 @@ Other enhancements
 - :meth:`ExtensionArray._explode` interface method added to allow extension type implementations of the ``explode`` method (:issue:`54833`)
 - :meth:`ExtensionArray.duplicated` added to allow extension type implementations of the ``duplicated`` method (:issue:`55255`)
 - Allow passing ``read_only``, ``data_only`` and ``keep_links`` arguments to openpyxl using ``engine_kwargs`` of :func:`read_excel` (:issue:`55027`)
+- Allow passing ``repl_kwargs`` argument to :meth:`pandas.Series.str.replace` (:issue:`51748`)
 - DataFrame.apply now allows the usage of numba (via ``engine="numba"``) to JIT compile the passed function, allowing for potential speedups (:issue:`54666`)
 - Implement masked algorithms for :meth:`Series.value_counts` (:issue:`54984`)
 - Improved error message when constructing :class:`Period` with invalid offsets such as "QS" (:issue:`55785`)

pandas/core/strings/accessor.py

@@ -1394,12 +1394,13 @@ def fullmatch(self, pat, case: bool = True, flags: int = 0, na=None):
     @forbid_nonstring_types(["bytes"])
     def replace(
         self,
-        pat: str | re.Pattern,
-        repl: str | Callable,
+        pat: str | re.Pattern | None = None,
+        repl: str | Callable | None = None,
         n: int = -1,
         case: bool | None = None,
         flags: int = 0,
         regex: bool = False,
+        repl_kwargs: dict | None = None,
     ):
         r"""
         Replace each occurrence of pattern/regex in the Series/Index.
@@ -1434,6 +1435,9 @@ def replace(
             - If False, treats the pattern as a literal string
             - Cannot be set to False if `pat` is a compiled regex or `repl` is
               a callable.
+        repl_kwargs : dict, default None
+            <key : value> pairs representing strings to be replaced, and their
+            updated values.
 
         Returns
         -------
@@ -1447,6 +1451,8 @@ def replace(
             * if `regex` is False and `repl` is a callable or `pat` is a compiled
               regex
             * if `pat` is a compiled regex and `case` or `flags` is set
+            * if `pat` and `repl_kwargs` both equal None
+            * if `pat` and `repl_kwargs` are both specified
 
         Notes
         -----
@@ -1456,6 +1462,15 @@ def replace(
 
         Examples
         --------
+        When `repl_kwargs` is a dictionary, every key in `repl_kwargs` is replaced
+        with its corresponding value:
+
+        >>> pd.Series(['A', 'B', np.nan]).str.replace(repl_kwargs={'A': 'a', 'B': 'b'})
+        0    a
+        1    b
+        2    NaN
+        dtype: object
+
         When `pat` is a string and `regex` is True, the given `pat`
         is compiled as a regex. When `repl` is a string, it replaces matching
         regex patterns as with :meth:`re.sub`. NaN value(s) in the Series are
@@ -1518,8 +1533,19 @@ def replace(
         2    NaN
         dtype: object
         """
+        if pat is None and repl_kwargs is None:
+            raise ValueError(
+                "Cannot replace a string without specifying a string to be modified."
+            )
+
+        if pat is not None and repl_kwargs is not None:
+            raise ValueError(
+                "Cannot replace a string using both a pattern and <key : value> "
+                "combination."
+            )
+
         # Check whether repl is valid (GH 13438, GH 15055)
-        if not (isinstance(repl, str) or callable(repl)):
+        if pat and not (isinstance(repl, str) or callable(repl)):
             raise TypeError("repl must be a string or callable")
 
         is_compiled_re = is_re(pat)
@@ -1539,10 +1565,21 @@ def replace(
         if case is None:
             case = True
 
-        result = self._data.array._str_replace(
-            pat, repl, n=n, case=case, flags=flags, regex=regex
-        )
-        return self._wrap_result(result)
+        if repl_kwargs:
+            res_output = self._data
+            for key, value in repl_kwargs.items():
+                result = res_output.array._str_replace(
+                    key, str(value), n=n, case=case, flags=flags, regex=regex
+                )
+                res_output = self._wrap_result(result)
+
+        else:
+            result = self._data.array._str_replace(
+                pat, repl, n=n, case=case, flags=flags, regex=regex
+            )
+            res_output = self._wrap_result(result)
+
+        return res_output
 
     @forbid_nonstring_types(["bytes"])
     def repeat(self, repeats):

pandas/tests/strings/test_find_replace.py

@@ -354,6 +354,31 @@ def test_endswith_nullable_string_dtype(nullable_string_dtype, na):
 # --------------------------------------------------------------------------------------
 # str.replace
 # --------------------------------------------------------------------------------------
+@pytest.mark.parametrize(
+    "msg, kwargs",
+    [
+        ("Cannot replace a string without specifying a string to be modified.", {}),
+        (
+            "Cannot replace a string using both a pattern and <key : value> "
+            "combination.",
+            {"pat": "A*", "repl_kwargs": {"A": "a"}, "regex": True},
+        ),
+    ],
+)
+def test_replace_dict_invalid(any_string_dtype, msg, kwargs):
+    # GH 51914
+    series = Series(data=["A", "B_junk", "C_gunk"], name="my_messy_col")
+
+    with pytest.raises(ValueError, match=msg):
+        series.str.replace(**kwargs)
+
+
+def test_replace_dict(any_string_dtype):
+    # GH 51914
+    series = Series(data=["A", "B", "C"], name="my_messy_col")
+    new_series = series.str.replace(repl_kwargs={"A": "a", "B": "b"})
+    expected = Series(data=["a", "b", "C"], name="my_messy_col")
+    tm.assert_series_equal(new_series, expected)
 
 
 def test_replace(any_string_dtype):