Merge branch '2.3.x' of https://github.com/pandas-dev/pandas into 2.3.x

Author: rhshadrach

.github/workflows/unit-tests.yml

@@ -392,7 +392,7 @@ jobs:
       - name: Set up Python Dev Version
         uses: actions/setup-python@v5
         with:
-          python-version: '3.13-dev'
+          python-version: '3.14-dev'
 
       - name: Build Environment
         run: |

.github/workflows/wheels.yml

@@ -13,6 +13,8 @@
 name: Wheel builder
 
 on:
+  release:
+    types: [published]
   schedule:
   # 3:27 UTC every day
   - cron: "27 3 * * *"
@@ -37,6 +39,7 @@ jobs:
     if: >-
       (github.event_name == 'schedule') ||
       github.event_name == 'workflow_dispatch' ||
+      github.event_name == 'release' ||
       (github.event_name == 'pull_request' &&
       contains(github.event.pull_request.labels.*.name, 'Build')) ||
       (github.event_name == 'push' && startsWith(github.ref, 'refs/tags/v') && ( ! endsWith(github.ref, 'dev0')))
@@ -82,6 +85,7 @@ jobs:
     if: >-
       (github.event_name == 'schedule') ||
       github.event_name == 'workflow_dispatch' ||
+      github.event_name == 'release' ||
       (github.event_name == 'pull_request' &&
       contains(github.event.pull_request.labels.*.name, 'Build')) ||
       (github.event_name == 'push' && startsWith(github.ref, 'refs/tags/v') && ( ! endsWith(github.ref, 'dev0')))
@@ -101,11 +105,13 @@ jobs:
         - [macos-14, macosx_arm64]
         - [windows-2022, win_amd64]
         # TODO: support PyPy?
-        python: [["cp39", "3.9"], ["cp310", "3.10"], ["cp311", "3.11"], ["cp312", "3.12"], ["cp313", "3.13"], ["cp313t", "3.13"]]
+        python: [["cp39", "3.9"], ["cp310", "3.10"], ["cp311", "3.11"], ["cp312", "3.12"], ["cp313", "3.13"], ["cp313t", "3.13"], ["cp314", "3.14"], ["cp314t", "3.14"]]
         # TODO: Build free-threaded wheels for Windows
         exclude:
         - buildplat: [windows-2022, win_amd64]
           python: ["cp313t", "3.13"]
+        - buildplat: [windows-2022, win_amd64]
+          python: ["cp314t", "3.14"]
 
     env:
       IS_PUSH: ${{ github.event_name == 'push' && startsWith(github.ref, 'refs/tags/v') }}
@@ -147,7 +153,7 @@ jobs:
         run: echo "sdist_name=$(cd ./dist && ls -d */)" >> "$GITHUB_ENV"
 
       - name: Build wheels
-        uses: pypa/cibuildwheel@v2.23.3
+        uses: pypa/cibuildwheel@v3.1.4
         with:
          package-dir: ./dist/${{ startsWith(matrix.buildplat[1], 'macosx') && env.sdist_name || needs.build_sdist.outputs.sdist_file }}
         env:
@@ -182,8 +188,8 @@ jobs:
           python -c `'import pandas as pd; pd.test(extra_args=[`\"--no-strict-data-files`\", `\"-m not clipboard and not single_cpu and not slow and not network and not db`\"])`';
           "@
           # add rc to the end of the image name if the Python version is unreleased
-          docker pull python:${{ matrix.python[1] == '3.13' && '3.13-rc' || format('{0}-windowsservercore', matrix.python[1]) }}
-          docker run --env PANDAS_CI='1' -v ${PWD}:C:\pandas python:${{ matrix.python[1] == '3.13' && '3.13-rc' || format('{0}-windowsservercore', matrix.python[1]) }} powershell -Command $TST_CMD
+          docker pull python:${{ matrix.python[1] == '3.14' && '3.14-rc' || format('{0}-windowsservercore', matrix.python[1]) }}
+          docker run --env PANDAS_CI='1' -v ${PWD}:C:\pandas python:${{ matrix.python[1] == '3.14' && '3.14-rc' || format('{0}-windowsservercore', matrix.python[1]) }} powershell -Command $TST_CMD
 
       - uses: actions/upload-artifact@v4
         with:
@@ -206,3 +212,41 @@ jobs:
           source ci/upload_wheels.sh
           set_upload_vars
           upload_wheels
+
+  publish:
+    if: >
+      github.repository == 'pandas-dev/pandas' &&
+      github.event_name == 'release' &&
+      startsWith(github.ref, 'refs/tags/v')
+
+    needs:
+      - build_sdist
+      - build_wheels
+
+    runs-on: ubuntu-latest
+
+    environment:
+      name: pypi
+    permissions:
+      id-token: write         # OIDC for Trusted Publishing
+      contents: read
+
+    steps:
+      - name: Download all artefacts
+        uses: actions/download-artifact@v4
+        with:
+          path: dist          # everything lands in ./dist/**
+
+      - name: Collect files
+        run: |
+          mkdir -p upload
+          # skip any wheel that contains 'pyodide'
+          find dist -name '*pyodide*.whl' -prune -o \
+                    -name '*.whl'   -exec mv {} upload/ \;
+          find dist -name '*.tar.gz' -exec mv {} upload/ \;
+
+      - name: Publish to **PyPI** (Trusted Publishing)
+        uses: pypa/gh-action-pypi-publish@release/v1
+        with:
+          packages-dir: upload
+          skip-existing: true

doc/source/development/maintaining.rst

@@ -467,9 +467,10 @@ which will be triggered when the tag is pushed.
    - Set as the latest release: Leave checked, unless releasing a patch release for an older version
      (e.g. releasing 1.4.5 after 1.5 has been released)
 
-5. Upload wheels to PyPI::
-
-    twine upload pandas/dist/pandas-<version>*.{whl,tar.gz} --skip-existing
+5. Verify wheels are uploaded automatically by GitHub Actions
+   via `**Trusted Publishing** <https://docs.pypi.org/trusted-publishers/>`__
+   when the GitHub `*Release* <https://docs.github.com/en/repositories/releasing-projects-on-github/about-releases>`__
+   is published. Do not run ``twine upload`` manually.
 
 6. The GitHub release will after some hours trigger an
    `automated conda-forge PR <https://github.com/conda-forge/pandas-feedstock/pulls>`_.

doc/source/user_guide/migration-3-strings.rst

@@ -188,6 +188,26 @@ let pandas do the inference. But if you want to be specific, you can specify the
 This is actually compatible with pandas 2.x as well, since in pandas < 3,
 ``dtype="str"`` was essentially treated as an alias for object dtype.
 
+.. attention::
+
+   While using ``dtype="str"`` in constructors is compatible with pandas 2.x,
+   specifying it as the dtype in :meth:`~Series.astype` runs into the issue
+   of also stringifying missing values in pandas 2.x. See the section
+   :ref:`string_migration_guide-astype_str` for more details.
+
+For selecting string columns with :meth:`~DataFrame.select_dtypes` in a pandas
+2.x and 3.x compatible way, it is not possible to use ``"str"``. While this
+works for pandas 3.x, it raises an error in pandas 2.x.
+As an alternative, you can select both ``object`` (for pandas 2.x) and
+``"string"`` (for pandas 3.x; which will also select the default ``str`` dtype
+and does not error on pandas 2.x):
+
+.. code-block:: python
+
+   # can use ``include=["str"]`` for pandas >= 3
+   >>> df.select_dtypes(include=["object", "string"])
+
+
 The missing value sentinel is now always NaN
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
@@ -307,55 +327,103 @@ the :meth:`~pandas.Series.str.decode` method now has a ``dtype`` parameter to be
 able to specify object dtype instead of the default of string dtype for this use
 case.
 
+:meth:`Series.values` now returns an :class:`~pandas.api.extensions.ExtensionArray`
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+With object dtype, using ``.values`` on a Series will return the underlying NumPy array.
+
+.. code-block:: python
+
+   >>> ser = pd.Series(["a", "b", np.nan], dtype="object")
+   >>> type(ser.values)
+   <class 'numpy.ndarray'>
+
+However with the new string dtype, the underlying ExtensionArray is returned instead.
+
+.. code-block:: python
+
+   >>> ser = pd.Series(["a", "b", pd.NA], dtype="str")
+   >>> ser.values
+   <ArrowStringArray>
+   ['a', 'b', nan]
+   Length: 3, dtype: str
+
+If your code requires a NumPy array, you should use :meth:`Series.to_numpy`.
+
+.. code-block:: python
+
+   >>> ser = pd.Series(["a", "b", pd.NA], dtype="str")
+   >>> ser.to_numpy()
+   ['a' 'b' nan]
+
+In general, you should always prefer :meth:`Series.to_numpy` to get a NumPy array or :meth:`Series.array` to get an ExtensionArray over using :meth:`Series.values`.
+
 Notable bug fixes
 ~~~~~~~~~~~~~~~~~
 
+.. _string_migration_guide-astype_str:
+
 ``astype(str)`` preserving missing values
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-This is a long standing "bug" or misfeature, as discussed in https://github.com/pandas-dev/pandas/issues/25353.
+The stringifying of missing values is a long standing "bug" or misfeature, as
+discussed in https://github.com/pandas-dev/pandas/issues/25353, but fixing it
+introduces a significant behaviour change.
 
-With pandas < 3, when using ``astype(str)`` (using the built-in :func:`str`, not
-``astype("str")``!), the operation would convert every element to a string,
-including the missing values:
+With pandas < 3, when using ``astype(str)`` or ``astype("str")``, the operation
+would convert every element to a string, including the missing values:
 
 .. code-block:: python
 
    # OLD behavior in pandas < 3
-   >>> ser = pd.Series(["a", np.nan], dtype=object)
+   >>> ser = pd.Series([1.5, np.nan])
    >>> ser
-   0      a
+   0    1.5
    1    NaN
-   dtype: object
-   >>> ser.astype(str)
-   0      a
+   dtype: float64
+   >>> ser.astype("str")
+   0    1.5
    1    nan
    dtype: object
-   >>> ser.astype(str).to_numpy()
-   array(['a', 'nan'], dtype=object)
+   >>> ser.astype("str").to_numpy()
+   array(['1.5', 'nan'], dtype=object)
 
 Note how ``NaN`` (``np.nan``) was converted to the string ``"nan"``. This was
 not the intended behavior, and it was inconsistent with how other dtypes handled
 missing values.
 
-With pandas 3, this behavior has been fixed, and now ``astype(str)`` is an alias
-for ``astype("str")``, i.e. casting to the new string dtype, which will preserve
-the missing values:
+With pandas 3, this behavior has been fixed, and now ``astype("str")`` will cast
+to the new string dtype, which preserves the missing values:
 
 .. code-block:: python
 
    # NEW behavior in pandas 3
    >>> pd.options.future.infer_string = True
-   >>> ser = pd.Series(["a", np.nan], dtype=object)
-   >>> ser.astype(str)
-   0      a
+   >>> ser = pd.Series([1.5, np.nan])
+   >>> ser.astype("str")
+   0    1.5
    1    NaN
    dtype: str
-   >>> ser.astype(str).values
-   array(['a', nan], dtype=object)
+   >>> ser.astype("str").to_numpy()
+   array(['1.5', nan], dtype=object)
 
 If you want to preserve the old behaviour of converting every object to a
-string, you can use ``ser.map(str)`` instead.
+string, you can use ``ser.map(str)`` instead. If you want do such conversion
+while preserving the missing values in a way that works with both pandas 2.x and
+3.x, you can use ``ser.map(str, na_action="ignore")`` (for pandas 3.x only, you
+can do ``ser.astype("str")``).
+
+If you want to convert to object or string dtype for pandas 2.x and 3.x,
+respectively, without needing to stringify each individual element, you will
+have to use a conditional check on the pandas version.
+For example, to convert a categorical Series with string categories to its
+dense non-categorical version with object or string dtype:
+
+.. code-block:: python
+
+   >>> import pandas as pd
+   >>> ser = pd.Series(["a", np.nan], dtype="category")
+   >>> ser.astype(object if pd.__version__ < "3" else "str")
 
 
 ``prod()`` raising for string data

doc/source/whatsnew/index.rst

@@ -16,6 +16,7 @@ Version 2.3
 .. toctree::
    :maxdepth: 2
 
+   v2.3.3
    v2.3.2
    v2.3.1
    v2.3.0

doc/source/whatsnew/v0.21.0.rst

@@ -635,22 +635,17 @@ Previous behavior:
 
 New behavior:
 
-.. code-block:: ipython
+.. ipython:: python
 
-   In [1]: pi = pd.period_range('2017-01', periods=12, freq='M')
+   pi = pd.period_range('2017-01', periods=12, freq='M')
 
-   In [2]: s = pd.Series(np.arange(12), index=pi)
+   s = pd.Series(np.arange(12), index=pi)
 
-   In [3]: resampled = s.resample('2Q').mean()
+   resampled = s.resample('2Q').mean()
 
-   In [4]: resampled
-   Out[4]:
-   2017Q1    2.5
-   2017Q3    8.5
-   Freq: 2Q-DEC, dtype: float64
+   resampled
 
-   In [5]: resampled.index
-   Out[5]: PeriodIndex(['2017Q1', '2017Q3'], dtype='period[2Q-DEC]')
+   resampled.index
 
 Upsampling and calling ``.ohlc()`` previously returned a ``Series``, basically identical to calling ``.asfreq()``. OHLC upsampling now returns a DataFrame with columns ``open``, ``high``, ``low`` and ``close`` (:issue:`13083`). This is consistent with downsampling and ``DatetimeIndex`` behavior.
 

doc/source/whatsnew/v2.2.0.rst

@@ -662,7 +662,7 @@ Other Deprecations
 - Deprecated :meth:`DatetimeArray.__init__` and :meth:`TimedeltaArray.__init__`, use :func:`array` instead (:issue:`55623`)
 - Deprecated :meth:`Index.format`, use ``index.astype(str)`` or ``index.map(formatter)`` instead (:issue:`55413`)
 - Deprecated :meth:`Series.ravel`, the underlying array is already 1D, so ravel is not necessary (:issue:`52511`)
-- Deprecated :meth:`Series.resample` and :meth:`DataFrame.resample` with a :class:`PeriodIndex` (and the 'convention' keyword), convert to :class:`DatetimeIndex` (with ``.to_timestamp()``) before resampling instead (:issue:`53481`)
+- Deprecated :meth:`Series.resample` and :meth:`DataFrame.resample` with a :class:`PeriodIndex` (and the 'convention' keyword), convert to :class:`DatetimeIndex` (with ``.to_timestamp()``) before resampling instead (:issue:`53481`). Note: this deprecation was later undone in pandas 2.3.3 (:issue:`57033`)
 - Deprecated :meth:`Series.view`, use :meth:`Series.astype` instead to change the dtype (:issue:`20251`)
 - Deprecated :meth:`offsets.Tick.is_anchored`, use ``False`` instead (:issue:`55388`)
 - Deprecated ``core.internals`` members ``Block``, ``ExtensionBlock``, and ``DatetimeTZBlock``, use public APIs instead (:issue:`55139`)

doc/source/whatsnew/v2.3.1.rst

@@ -73,4 +73,4 @@ Bug fixes
 Contributors
 ~~~~~~~~~~~~
 
-.. contributors:: v2.3.0..v2.3.1|HEAD
+.. contributors:: v2.3.0..v2.3.1

doc/source/whatsnew/v2.3.2.rst

@@ -1,6 +1,6 @@
 .. _whatsnew_232:
 
-What's new in 2.3.2 (August XX, 2025)
+What's new in 2.3.2 (August 21, 2025)
 -------------------------------------
 
 These are the changes in pandas 2.3.2. See :ref:`release` for a full changelog
@@ -25,10 +25,16 @@ Bug fixes
 - Fix :meth:`~DataFrame.to_json` with ``orient="table"`` to correctly use the
   "string" type in the JSON Table Schema for :class:`StringDtype` columns
   (:issue:`61889`)
-
+- Boolean operations (``|``, ``&``, ``^``) with bool-dtype objects on the left and :class:`StringDtype` objects on the right now cast the string to bool, with a deprecation warning (:issue:`60234`)
+- Fixed :meth:`~Series.str.match`, :meth:`~Series.str.fullmatch` and :meth:`~Series.str.contains`
+  string methods with compiled regex for the Arrow-backed string dtype (:issue:`61964`, :issue:`61942`)
+- Bug in :meth:`Series.replace` and :meth:`DataFrame.replace` inconsistently
+  replacing matching values when missing values are present for string dtypes (:issue:`56599`)
 
 .. ---------------------------------------------------------------------------
 .. _whatsnew_232.contributors:
 
 Contributors
 ~~~~~~~~~~~~
+
+.. contributors:: v2.3.1..v2.3.2