Merge remote-tracking branch 'upstream/main' into bug-cov-nat

Author: fbourgey

.github/workflows/wheels.yml

@@ -99,6 +99,7 @@ jobs:
         # Note: M1 images on Github Actions start from macOS 14
         - [macos-14, macosx_arm64]
         - [windows-2022, win_amd64]
+        - [windows-11-arm, win_arm64]
         # TODO: support PyPy?
         python: [["cp310", "3.10"], ["cp311", "3.11"], ["cp312", "3.12"], ["cp313", "3.13"], ["cp313t", "3.13"]]
         include:
@@ -108,6 +109,12 @@ jobs:
         - buildplat: [ubuntu-24.04, pyodide_wasm32]
           python: ["cp312", "3.12"]
           cibw_build_frontend: 'build'
+        exclude:
+          - buildplat: [windows-11-arm, win_arm64]
+            python: ["cp310", "3.10"]
+        # BackendUnavailable: Cannot import 'mesonpy'
+          - buildplat: [windows-11-arm, win_arm64]
+            python: ["cp313t", "3.13"]
 
     env:
       IS_PUSH: ${{ github.event_name == 'push' && startsWith(github.ref, 'refs/tags/v') }}
@@ -118,6 +125,12 @@ jobs:
         with:
           fetch-depth: 0
 
+      - name: Set up MSVC environment for ARM64
+        if: matrix.buildplat[1] == 'win_arm64'
+        uses: ilammy/msvc-dev-cmd@v1
+        with:
+          arch: arm64
+
       # TODO: Build wheels from sdist again
       # There's some sort of weird race condition?
       # within Github that makes the sdist be missing files
@@ -155,9 +168,13 @@ jobs:
         env:
           CIBW_BUILD: ${{ matrix.python[0] }}-${{ matrix.buildplat[1] }}
           CIBW_BUILD_FRONTEND: ${{ matrix.cibw_build_frontend || 'pip' }}
-          CIBW_PLATFORM: ${{ matrix.buildplat[1] == 'pyodide_wasm32' && 'pyodide' || 'auto' }}
+          CIBW_PLATFORM: ${{ (matrix.buildplat[1] == 'pyodide_wasm32' && 'pyodide') || (matrix.buildplat[1] == 'win_arm64' && 'windows') || 'auto' }}
+          CIBW_ARCHS: ${{ matrix.buildplat[1] == 'win_arm64' && 'ARM64' || 'auto' }}
+          CIBW_BEFORE_BUILD_WINDOWS: 'python -m pip install delvewheel'
 
-      - name: Set up Python
+      - name: Set up Python for validation/upload (non-ARM64 Windows & other OS)
+        # micromamba is not available for ARM64 Windows
+        if: matrix.buildplat[1] != 'win_arm64'
         uses: mamba-org/setup-micromamba@v2
         with:
           environment-name: wheel-env
@@ -170,6 +187,12 @@ jobs:
           cache-downloads: true
           cache-environment: true
 
+      - name: Install wheel for win_arm64
+        # installing wheel here because micromamba step was skipped
+        if: matrix.buildplat[1] == 'win_arm64'
+        shell: bash -el {0}
+        run: python -m pip install wheel
+
       - name: Validate wheel RECORD
         shell: bash -el {0}
         run: for whl in $(ls wheelhouse); do wheel unpack wheelhouse/$whl -d /tmp; done

.pre-commit-config.yaml

@@ -140,7 +140,7 @@ repos:
         pass_filenames: false
         types: [python]
         stages: [manual]
-    -   id: mypy
+    -   id: stubtest
         # note: assumes python env is setup and activated
         # note: requires pandas dev to be installed
         name: mypy (stubtest)

doc/source/user_guide/10min.rst

@@ -178,12 +178,26 @@ Getitem (``[]``)
 ~~~~~~~~~~~~~~~~
 
 For a :class:`DataFrame`, passing a single label selects a column and
-yields a :class:`Series` equivalent to ``df.A``:
+yields a :class:`Series`:
 
 .. ipython:: python
 
    df["A"]
 
+If the label only contains letters, numbers, and underscores, you can
+alternatively use the column name attribute:
+
+.. ipython:: python
+
+   df.A
+
+Passing a list of column labels selects multiple columns, which can be useful
+for getting a subset/rearranging:
+
+.. ipython:: python
+
+   df[["B", "A"]]
+
 For a :class:`DataFrame`, passing a slice ``:`` selects matching rows:
 
 .. ipython:: python

doc/source/user_guide/index.rst

@@ -78,6 +78,7 @@ Guides
     boolean
     visualization
     style
+    user_defined_functions
     groupby
     window
     timeseries

doc/source/user_guide/missing_data.rst

@@ -258,9 +258,6 @@ will convert your data to use the nullable data types supporting :class:`NA`,
 such as :class:`Int64Dtype` or :class:`ArrowDtype`. This is especially helpful after reading
 in data sets from IO methods where data types were inferred.
 
-In this example, while the dtypes of all columns are changed, we show the results for
-the first 10 columns.
-
 .. ipython:: python
 
    import io
@@ -434,7 +431,7 @@ where the index and column aligns between the original object and the filled obj
 
 .. note::
 
-   :meth:`DataFrame.where` can also be used to fill NA values.Same result as above.
+   :meth:`DataFrame.where` can also be used to fill NA values. Same result as above.
 
    .. ipython:: python