Merge branch 'main' into cibuildwheel_2.20.0

Author: mroeschke

.circleci/config.yml

@@ -16,6 +16,7 @@ jobs:
       - run:
           name: Install Environment and Run Tests
           shell: /bin/bash -exo pipefail
+          # https://pytest-qt.readthedocs.io/en/latest/troubleshooting.html#github-actions-azure-pipelines-travis-ci-and-gitlab-ci-cd
           command: |
             MINI_URL="https://github.com/conda-forge/miniforge/releases/download/24.3.0-0/Miniforge3-24.3.0-0-Linux-aarch64.sh"
             wget -q $MINI_URL -O Miniforge3.sh
@@ -33,6 +34,7 @@ jobs:
             fi
             python -m pip install --no-build-isolation -ve . --config-settings=setup-args="--werror"
             PATH=$HOME/miniconda3/envs/pandas-dev/bin:$HOME/miniconda3/condabin:$PATH
+            sudo apt-get update && sudo apt-get install -y libegl1 libopengl0
             ci/run_tests.sh
   test-linux-musl:
     docker:

.github/workflows/code-checks.yml

@@ -51,6 +51,11 @@ jobs:
     # TODO: The doctests have to be run first right now, since the Cython doctests only work
     # with pandas installed in non-editable mode
     # This can be removed once pytest-cython doesn't require C extensions to be installed inplace
+
+    - name: Extra installs
+      # https://pytest-qt.readthedocs.io/en/latest/troubleshooting.html#github-actions-azure-pipelines-travis-ci-and-gitlab-ci-cd
+      run: sudo apt-get update && sudo apt-get install -y libegl1 libopengl0
+
     - name: Run doctests
       run: cd ci && ./code_checks.sh doctests
       if: ${{ steps.build.outcome == 'success' && always() }}

.github/workflows/docbuild-and-upload.yml

@@ -46,6 +46,10 @@ jobs:
     - name: Build Pandas
       uses: ./.github/actions/build_pandas
 
+    - name: Extra installs
+      # https://pytest-qt.readthedocs.io/en/latest/troubleshooting.html#github-actions-azure-pipelines-travis-ci-and-gitlab-ci-cd
+      run: sudo apt-get update && sudo apt-get install -y libegl1 libopengl0
+
     - name: Test website
       run: python -m pytest web/
 

.github/workflows/unit-tests.yml

@@ -134,8 +134,8 @@ jobs:
         fetch-depth: 0
 
     - name: Extra installs
-      run: sudo apt-get update && sudo apt-get install -y ${{ matrix.extra_apt }}
-      if: ${{ matrix.extra_apt }}
+      # https://pytest-qt.readthedocs.io/en/latest/troubleshooting.html#github-actions-azure-pipelines-travis-ci-and-gitlab-ci-cd
+      run: sudo apt-get update && sudo apt-get install -y libegl1 libopengl0 ${{ matrix.extra_apt || ''}}
 
     - name: Generate extra locales
       # These extra locales will be available for locale.setlocale() calls in tests

ci/code_checks.sh

@@ -70,7 +70,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         --format=actions \
         -i ES01 `# For now it is ok if docstrings are missing the extended summary` \
         -i "pandas.Series.dt PR01" `# Accessors are implemented as classes, but we do not document the Parameters section` \
-        -i "pandas.MultiIndex.get_level_values SA01" \
         -i "pandas.MultiIndex.get_loc_level PR07" \
         -i "pandas.MultiIndex.names SA01" \
         -i "pandas.MultiIndex.reorder_levels RT03,SA01" \
@@ -165,9 +164,7 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.Series.str.center RT03,SA01" \
         -i "pandas.Series.str.decode PR07,RT03,SA01" \
         -i "pandas.Series.str.encode PR07,RT03,SA01" \
-        -i "pandas.Series.str.find RT03" \
         -i "pandas.Series.str.fullmatch RT03" \
-        -i "pandas.Series.str.get RT03,SA01" \
         -i "pandas.Series.str.index RT03" \
         -i "pandas.Series.str.ljust RT03,SA01" \
         -i "pandas.Series.str.lower RT03" \
@@ -177,7 +174,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.Series.str.partition RT03" \
         -i "pandas.Series.str.repeat SA01" \
         -i "pandas.Series.str.replace SA01" \
-        -i "pandas.Series.str.rfind RT03" \
         -i "pandas.Series.str.rindex RT03" \
         -i "pandas.Series.str.rjust RT03,SA01" \
         -i "pandas.Series.str.rpartition RT03" \
@@ -267,9 +263,7 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.api.extensions.ExtensionArray.tolist RT03,SA01" \
         -i "pandas.api.extensions.ExtensionArray.unique RT03,SA01" \
         -i "pandas.api.extensions.ExtensionArray.view SA01" \
-        -i "pandas.api.indexers.VariableOffsetWindowIndexer PR01,SA01" \
         -i "pandas.api.interchange.from_dataframe RT03,SA01" \
-        -i "pandas.api.types.is_any_real_numeric_dtype SA01" \
         -i "pandas.api.types.is_bool PR01,SA01" \
         -i "pandas.api.types.is_bool_dtype SA01" \
         -i "pandas.api.types.is_categorical_dtype SA01" \
@@ -296,7 +290,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.api.types.is_period_dtype SA01" \
         -i "pandas.api.types.is_re PR07,SA01" \
         -i "pandas.api.types.is_re_compilable PR07,SA01" \
-        -i "pandas.api.types.is_sparse SA01" \
         -i "pandas.api.types.is_timedelta64_ns_dtype SA01" \
         -i "pandas.api.types.pandas_dtype PR07,RT03,SA01" \
         -i "pandas.arrays.ArrowExtensionArray PR07,SA01" \

doc/source/user_guide/basics.rst

@@ -155,16 +155,6 @@ speedups. ``numexpr`` uses smart chunking, caching, and multiple cores. ``bottle
 a set of specialized cython routines that are especially fast when dealing with arrays that have
 ``nans``.
 
-Here is a sample (using 100 column x 100,000 row ``DataFrames``):
-
-.. csv-table::
-    :header: "Operation", "0.11.0 (ms)", "Prior Version (ms)", "Ratio to Prior"
-    :widths: 25, 25, 25, 25
-
-    ``df1 > df2``, 13.32, 125.35,  0.1063
-    ``df1 * df2``, 21.71,  36.63,  0.5928
-    ``df1 + df2``, 22.04,  36.50,  0.6039
-
 You are highly encouraged to install both libraries. See the section
 :ref:`Recommended Dependencies <install.recommended_dependencies>` for more installation info.
 

pandas/core/dtypes/common.py

@@ -187,6 +187,10 @@ def is_sparse(arr) -> bool:
     bool
         Whether or not the array-like is a pandas sparse array.
 
+    See Also
+    --------
+    api.types.SparseDtype : The dtype object for pandas sparse arrays.
+
     Examples
     --------
     Returns `True` if the parameter is a 1-D pandas sparse array.
@@ -1181,6 +1185,12 @@ def is_any_real_numeric_dtype(arr_or_dtype) -> bool:
     boolean
         Whether or not the array or dtype is of a real number dtype.
 
+    See Also
+    --------
+    is_numeric_dtype : Check if a dtype is numeric.
+    is_complex_dtype : Check if a dtype is complex.
+    is_bool_dtype : Check if a dtype is boolean.
+
     Examples
     --------
     >>> from pandas.api.types import is_any_real_numeric_dtype

pandas/core/indexers/objects.py

@@ -167,6 +167,31 @@ class VariableOffsetWindowIndexer(BaseIndexer):
     """
     Calculate window boundaries based on a non-fixed offset such as a BusinessDay.
 
+    Parameters
+    ----------
+    index_array : np.ndarray, default 0
+        Array-like structure specifying the indices for data points.
+        This parameter is currently not used.
+
+    window_size : int, optional, default 0
+        Specifies the number of data points in each window.
+        This parameter is currently not used.
+
+    index : DatetimeIndex, optional
+        ``DatetimeIndex`` of the labels of each observation.
+
+    offset : BaseOffset, optional
+        ``DateOffset`` representing the size of the window.
+
+    **kwargs
+        Additional keyword arguments passed to the parent class ``BaseIndexer``.
+
+    See Also
+    --------
+    api.indexers.BaseIndexer : Base class for all indexers.
+    DataFrame.rolling : Rolling window calculations on DataFrames.
+    offsets : Module providing various time offset classes.
+
     Examples
     --------
     >>> from pandas.api.indexers import VariableOffsetWindowIndexer

pandas/core/indexes/multi.py

@@ -1783,6 +1783,16 @@ def get_level_values(self, level) -> Index:  # type: ignore[override]
         Return vector of label values for requested level.
 
         Length of returned vector is equal to the length of the index.
+        The `get_level_values` method is a crucial utility for extracting
+        specific level values from a `MultiIndex`. This function is particularly
+        useful when working with multi-level data, allowing you to isolate
+        and manipulate individual levels without having to deal with the
+        complexity of the entire `MultiIndex` structure. It seamlessly handles
+        both integer and string-based level access, providing flexibility in
+        how you can interact with the data. Additionally, this method ensures
+        that the returned `Index` maintains the integrity of the original data,
+        even when missing values are present, by appropriately casting the
+        result to a suitable data type.
 
         Parameters
         ----------
@@ -1796,6 +1806,13 @@ def get_level_values(self, level) -> Index:  # type: ignore[override]
             Values is a level of this MultiIndex converted to
             a single :class:`Index` (or subclass thereof).
 
+        See Also
+        --------
+        MultiIndex : A multi-level, or hierarchical, index object for pandas objects.
+        Index : Immutable sequence used for indexing and alignment.
+        MultiIndex.remove_unused_levels : Create new MultiIndex from current that
+            removes unused levels.
+
         Notes
         -----
         If the level contains missing values, the result may be casted to

pandas/core/strings/accessor.py

@@ -1085,6 +1085,13 @@ def get(self, i):
         Returns
         -------
         Series or Index
+            Series or Index where each value is the extracted element from
+            the corresponding input component.
+
+        See Also
+        --------
+        Series.str.extract : Extract capture groups in the regex as columns
+            in a DataFrame.
 
         Examples
         --------
@@ -2971,6 +2978,9 @@ def extractall(self, pat, flags: int = 0) -> DataFrame:
     Returns
     -------
     Series or Index of int.
+        A Series (if the input is a Series) or an Index (if the input is an
+        Index) of the %(side)s indexes corresponding to the positions where the
+        substring is found in each string of the input.
 
     See Also
     --------
@@ -2980,9 +2990,9 @@ def extractall(self, pat, flags: int = 0) -> DataFrame:
     --------
     For Series.str.find:
 
-    >>> ser = pd.Series(["cow_", "duck_", "do_ve"])
+    >>> ser = pd.Series(["_cow_", "duck_", "do_v_e"])
     >>> ser.str.find("_")
-    0   3
+    0   0
     1   4
     2   2
     dtype: int64