Merge remote-tracking branch 'upstream/main' into ref/memoryviews

doc/source/development/contributing_gitpod.rst

@@ -109,7 +109,7 @@ development experience:
 
 *  `VSCode rst extension <https://marketplace.visualstudio.com/items?itemName=lextudio.restructuredtext>`_
 *  `Markdown All in One <https://marketplace.visualstudio.com/items?itemName=yzhang.markdown-all-in-one>`_
-*  `VSCode Gitlens extension <https://marketplace.visualstudio.com/items?itemName=eamodio.gitlens>`_
+*  `VSCode GitLens extension <https://marketplace.visualstudio.com/items?itemName=eamodio.gitlens>`_
 *  `VSCode Git Graph extension <https://marketplace.visualstudio.com/items?itemName=mhutchie.git-graph>`_
 
 Development workflow with Gitpod

doc/source/whatsnew/v2.3.0.rst

@@ -37,6 +37,7 @@ Other enhancements
   updated to work correctly with NumPy >= 2 (:issue:`57739`)
 - :meth:`Series.str.decode` result now has ``StringDtype`` when ``future.infer_string`` is True (:issue:`60709`)
 - :meth:`~Series.to_hdf` and :meth:`~DataFrame.to_hdf` now round-trip with ``StringDtype``  (:issue:`60663`)
+- The :meth:`Series.str.decode` has gained the argument ``dtype`` to control the dtype of the result (:issue:`60940`)
 - The :meth:`~Series.cumsum`, :meth:`~Series.cummin`, and :meth:`~Series.cummax` reductions are now implemented for ``StringDtype`` columns when backed by PyArrow (:issue:`60633`)
 - The :meth:`~Series.sum` reduction is now implemented for ``StringDtype`` columns (:issue:`59853`)
 

pandas/core/strings/accessor.py

@@ -34,6 +34,7 @@
     is_numeric_dtype,
     is_object_dtype,
     is_re,
+    is_string_dtype,
 )
 from pandas.core.dtypes.dtypes import (
     ArrowDtype,
@@ -2102,7 +2103,9 @@ def slice_replace(self, start=None, stop=None, repl=None):
         result = self._data.array._str_slice_replace(start, stop, repl)
         return self._wrap_result(result)
 
-    def decode(self, encoding, errors: str = "strict"):
+    def decode(
+        self, encoding, errors: str = "strict", dtype: str | DtypeObj | None = None
+    ):
         """
         Decode character string in the Series/Index using indicated encoding.
 
@@ -2116,6 +2119,12 @@ def decode(self, encoding, errors: str = "strict"):
         errors : str, optional
             Specifies the error handling scheme.
             Possible values are those supported by :meth:`bytes.decode`.
+        dtype : str or dtype, optional
+            The dtype of the result. When not ``None``, must be either a string or
+            object dtype. When ``None``, the dtype of the result is determined by
+            ``pd.options.future.infer_string``.
+
+            .. versionadded:: 2.3.0
 
         Returns
         -------
@@ -2137,6 +2146,10 @@ def decode(self, encoding, errors: str = "strict"):
         2   ()
         dtype: object
         """
+        if dtype is not None and not is_string_dtype(dtype):
+            raise ValueError(f"dtype must be string or object, got {dtype=}")
+        if dtype is None and get_option("future.infer_string"):
+            dtype = "str"
         # TODO: Add a similar _bytes interface.
         if encoding in _cpython_optimized_decoders:
             # CPython optimized implementation
@@ -2146,7 +2159,6 @@ def decode(self, encoding, errors: str = "strict"):
             f = lambda x: decoder(x, errors)[0]
         arr = self._data.array
         result = arr._str_map(f)
-        dtype = "str" if get_option("future.infer_string") else None
         return self._wrap_result(result, dtype=dtype)
 
     @forbid_nonstring_types(["bytes"])

pandas/tests/strings/test_strings.py

@@ -601,6 +601,30 @@ def test_decode_errors_kwarg():
     tm.assert_series_equal(result, expected)
 
 
+def test_decode_string_dtype(string_dtype):
+    # https://github.com/pandas-dev/pandas/pull/60940
+    ser = Series([b"a", b"b"])
+    result = ser.str.decode("utf-8", dtype=string_dtype)
+    expected = Series(["a", "b"], dtype=string_dtype)
+    tm.assert_series_equal(result, expected)
+
+
+def test_decode_object_dtype(object_dtype):
+    # https://github.com/pandas-dev/pandas/pull/60940
+    ser = Series([b"a", rb"\ud800"])
+    result = ser.str.decode("utf-8", dtype=object_dtype)
+    expected = Series(["a", r"\ud800"], dtype=object_dtype)
+    tm.assert_series_equal(result, expected)
+
+
+def test_decode_bad_dtype():
+    # https://github.com/pandas-dev/pandas/pull/60940
+    ser = Series([b"a", b"b"])
+    msg = "dtype must be string or object, got dtype='int64'"
+    with pytest.raises(ValueError, match=msg):
+        ser.str.decode("utf-8", dtype="int64")
+
+
 @pytest.mark.parametrize(
     "form, expected",
     [