Merge branch 'main' into scott/bodo_udf_engine

Author: datapythonista

.github/workflows/wheels.yml

@@ -94,7 +94,7 @@ jobs:
         buildplat:
         - [ubuntu-22.04, manylinux_x86_64]
         - [ubuntu-22.04, musllinux_x86_64]
-        - [macos-12, macosx_x86_64]
+        - [macos-13, macosx_x86_64]
         # Note: M1 images on Github Actions start from macOS 14
         - [macos-14, macosx_arm64]
         - [windows-2022, win_amd64]

.pre-commit-config.yaml

@@ -19,7 +19,7 @@ ci:
     skip: [pyright, mypy]
 repos:
 -   repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.8.1
+    rev: v0.8.6
     hooks:
     -   id: ruff
         args: [--exit-non-zero-on-fix]
@@ -34,7 +34,7 @@ repos:
     -   id: ruff-format
         exclude: ^scripts|^pandas/tests/frame/test_query_eval.py
 -   repo: https://github.com/jendrikseipp/vulture
-    rev: 'v2.13'
+    rev: 'v2.14'
     hooks:
       - id: vulture
         entry: python scripts/run_vulture.py
@@ -74,7 +74,7 @@ repos:
     hooks:
     -   id: isort
 -   repo: https://github.com/asottile/pyupgrade
-    rev: v3.19.0
+    rev: v3.19.1
     hooks:
     -   id: pyupgrade
         args: [--py310-plus]
@@ -95,12 +95,17 @@ repos:
     - id: sphinx-lint
       args: ["--enable", "all", "--disable", "line-too-long"]
 -   repo: https://github.com/pre-commit/mirrors-clang-format
-    rev: v19.1.4
+    rev: v19.1.6
     hooks:
     - id: clang-format
       files: ^pandas/_libs/src|^pandas/_libs/include
       args: [-i]
       types_or: [c, c++]
+-   repo: https://github.com/trim21/pre-commit-mirror-meson
+    rev: v1.6.1
+    hooks:
+    - id: meson-fmt
+      args: ['--inplace']
 -   repo: local
     hooks:
     -   id: pyright

LICENSE

@@ -3,7 +3,7 @@ BSD 3-Clause License
 Copyright (c) 2008-2011, AQR Capital Management, LLC, Lambda Foundry, Inc. and PyData Development Team
 All rights reserved.
 
-Copyright (c) 2011-2024, Open source contributors.
+Copyright (c) 2011-2025, Open source contributors.
 
 Redistribution and use in source and binary forms, with or without
 modification, are permitted provided that the following conditions are met:

asv_bench/benchmarks/io/csv.py

@@ -594,7 +594,7 @@ def setup(self):
         self.StringIO_input = StringIO(data)
 
     def time_read_csv_index_col(self):
-        read_csv(self.StringIO_input, index_col="a")
+        read_csv(self.data(self.StringIO_input), index_col="a")
 
 
 class ReadCSVDatePyarrowEngine(StringIORewind):
@@ -605,7 +605,7 @@ def setup(self):
 
     def time_read_csv_index_col(self):
         read_csv(
-            self.StringIO_input,
+            self.data(self.StringIO_input),
             parse_dates=["a"],
             engine="pyarrow",
             dtype_backend="pyarrow",

ci/code_checks.sh

@@ -81,19 +81,11 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.Timestamp.resolution PR02" \
         -i "pandas.Timestamp.tzinfo GL08" \
         -i "pandas.arrays.ArrowExtensionArray PR07,SA01" \
-        -i "pandas.arrays.NumpyExtensionArray SA01" \
         -i "pandas.arrays.TimedeltaArray PR07,SA01" \
         -i "pandas.core.groupby.DataFrameGroupBy.plot PR02" \
         -i "pandas.core.groupby.SeriesGroupBy.plot PR02" \
-        -i "pandas.core.resample.Resampler.max PR01,RT03,SA01" \
-        -i "pandas.core.resample.Resampler.mean SA01" \
-        -i "pandas.core.resample.Resampler.min PR01,RT03,SA01" \
-        -i "pandas.core.resample.Resampler.prod SA01" \
         -i "pandas.core.resample.Resampler.quantile PR01,PR07" \
-        -i "pandas.core.resample.Resampler.std SA01" \
         -i "pandas.core.resample.Resampler.transform PR01,RT03,SA01" \
-        -i "pandas.core.resample.Resampler.var SA01" \
-        -i "pandas.errors.ValueLabelTypeMismatch SA01" \
         -i "pandas.plotting.andrews_curves RT03,SA01" \
         -i "pandas.tseries.offsets.BDay PR02,SA01" \
         -i "pandas.tseries.offsets.BQuarterBegin.is_on_offset GL08" \

doc/cheatsheet/Pandas_Cheat_Sheet_FA.pdf

@@ -6,10 +6,12 @@ and pick "PDF" as the format.
 
 This cheat sheet, originally written by Irv Lustig, [Princeton Consultants](https://www.princetonoptimization.com/), was inspired by the [RStudio Data Wrangling Cheatsheet](https://www.rstudio.com/wp-content/uploads/2015/02/data-wrangling-cheatsheet.pdf).
 
-| Topic                  | PDF                                                                                                                                                                                                                                     | PPT                                                                                                                                                                                                                                               |
-|------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
-| Pandas_Cheat_Sheet     | <a href="https://github.com/pandas-dev/pandas/blob/main/doc/cheatsheet/Pandas_Cheat_Sheet.pdf" target="_parent"><img src="https://img.shields.io/badge/Open in PDF-%23FF0000.svg?style=flat-square&logo=adobe&logoColor=white"/></a>    | <a href="https://github.com/pandas-dev/pandas/blob/main/doc/cheatsheet/Pandas_Cheat_Sheet.pptx" target="_parent"><img src="https://img.shields.io/badge/Open in PPT-B7472A?style=flat-square&logo=microsoft-powerpoint&logoColor=white"/></a>     |
-| Pandas_Cheat_Sheet_JA  | <a href="https://github.com/pandas-dev/pandas/blob/main/doc/cheatsheet/Pandas_Cheat_Sheet_JA.pdf" target="_parent"><img src="https://img.shields.io/badge/Open in PDF-%23FF0000.svg?style=flat-square&logo=adobe&logoColor=white"/></a> | <a href="https://github.com/pandas-dev/pandas/blob/main/doc/cheatsheet/Pandas_Cheat_Sheet_JA.pptx" target="_parent"><img  src="https://img.shields.io/badge/Open in PPT-B7472A?style=flat-square&logo=microsoft-powerpoint&logoColor=white"/></a> |
+| Topic                  | Language    | PDF                                                                                                                                                                                                                                     | PPT                                                                                                                                                                                                                                               |
+|------------------------|-------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Pandas_Cheat_Sheet     | English     | <a href="https://github.com/pandas-dev/pandas/blob/main/doc/cheatsheet/Pandas_Cheat_Sheet.pdf" target="_parent"><img src="https://img.shields.io/badge/Open in PDF-%23FF0000.svg?style=flat-square&logo=adobe&logoColor=white"/></a>    | <a href="https://github.com/pandas-dev/pandas/blob/main/doc/cheatsheet/Pandas_Cheat_Sheet.pptx" target="_parent"><img src="https://img.shields.io/badge/Open in PPT-B7472A?style=flat-square&logo=microsoft-powerpoint&logoColor=white"/></a>     |
+| Pandas_Cheat_Sheet_JA  | Japanese    | <a href="https://github.com/pandas-dev/pandas/blob/main/doc/cheatsheet/Pandas_Cheat_Sheet_JA.pdf" target="_parent"><img src="https://img.shields.io/badge/Open in PDF-%23FF0000.svg?style=flat-square&logo=adobe&logoColor=white"/></a> | <a href="https://github.com/pandas-dev/pandas/blob/main/doc/cheatsheet/Pandas_Cheat_Sheet_JA.pptx" target="_parent"><img  src="https://img.shields.io/badge/Open in PPT-B7472A?style=flat-square&logo=microsoft-powerpoint&logoColor=white"/></a> |
+| Pandas_Cheat_Sheet_FA  | Persian     | <a href="https://github.com/pandas-dev/pandas/blob/main/doc/cheatsheet/Pandas_Cheat_Sheet_FA.pdf" target="_parent"><img src="https://img.shields.io/badge/Open in PDF-%23FF0000.svg?style=flat-square&logo=adobe&logoColor=white"/></a> | <a href="https://github.com/pandas-dev/pandas/blob/main/doc/cheatsheet/Pandas_Cheat_Sheet_FA.pptx" target="_parent"><img  src="https://img.shields.io/badge/Open in PPT-B7472A?style=flat-square&logo=microsoft-powerpoint&logoColor=white"/></a> |
+
 
 
 **Alternative**

doc/cheatsheet/Pandas_Cheat_Sheet_FA.pptx

@@ -35,6 +35,7 @@ Rolling window functions
    Rolling.skew
    Rolling.kurt
    Rolling.apply
+   Rolling.pipe
    Rolling.aggregate
    Rolling.quantile
    Rolling.sem
@@ -76,6 +77,7 @@ Expanding window functions
    Expanding.skew
    Expanding.kurt
    Expanding.apply
+   Expanding.pipe
    Expanding.aggregate
    Expanding.quantile
    Expanding.sem

doc/cheatsheet/README.md

@@ -858,9 +858,10 @@ and :ref:`Advanced Indexing <advanced>` you may select along more than one axis
 
 .. warning::
 
-   ``iloc`` supports two kinds of boolean indexing. If the indexer is a boolean ``Series``,
-   an error will be raised. For instance, in the following example, ``df.iloc[s.values, 1]`` is ok.
-   The boolean indexer is an array. But ``df.iloc[s, 1]`` would raise ``ValueError``.
+   While ``loc`` supports two kinds of boolean indexing, ``iloc`` only supports indexing with a
+   boolean array. If the indexer is a boolean ``Series``, an error will be raised. For instance,
+   in the following example, ``df.iloc[s.values, 1]`` is ok. The boolean indexer is an array.
+   But ``df.iloc[s, 1]`` would raise ``ValueError``.
 
    .. ipython:: python
 

doc/source/reference/window.rst

@@ -2340,6 +2340,7 @@ Read a URL with no options:
 .. code-block:: ipython
 
    In [320]: url = "https://www.fdic.gov/resources/resolutions/bank-failures/failed-bank-list"
+
    In [321]: pd.read_html(url)
    Out[321]:
    [                         Bank NameBank           CityCity StateSt  ...              Acquiring InstitutionAI Closing DateClosing FundFund
@@ -2366,6 +2367,7 @@ Read a URL while passing headers alongside the HTTP request:
 .. code-block:: ipython
 
    In [322]: url = 'https://www.sump.org/notes/request/' # HTTP request reflector
+
    In [323]: pd.read_html(url)
    Out[323]:
    [                   0                    1
@@ -2378,14 +2380,16 @@ Read a URL while passing headers alongside the HTTP request:
     1              Host:         www.sump.org
     2        User-Agent:    Python-urllib/3.8
     3        Connection:                close]
+
    In [324]: headers = {
-   In [325]:    'User-Agent':'Mozilla Firefox v14.0',
-   In [326]:    'Accept':'application/json',
-   In [327]:    'Connection':'keep-alive',
-   In [328]:    'Auth':'Bearer 2*/f3+fe68df*4'
-   In [329]: }
-   In [340]: pd.read_html(url, storage_options=headers)
-   Out[340]:
+      .....:    'User-Agent':'Mozilla Firefox v14.0',
+      .....:    'Accept':'application/json',
+      .....:    'Connection':'keep-alive',
+      .....:    'Auth':'Bearer 2*/f3+fe68df*4'
+      .....: }
+
+   In [325]: pd.read_html(url, storage_options=headers)
+   Out[325]:
    [                   0                    1
     0     Remote Socket:  51.15.105.256:51760
     1  Protocol Version:             HTTP/1.1

doc/source/user_guide/indexing.rst

@@ -1210,11 +1210,6 @@ You may set the ``xlabel`` and ``ylabel`` arguments to give the plot custom labe
 for x and y axis. By default, pandas will pick up index name as xlabel, while leaving
 it empty for ylabel.
 
-.. ipython:: python
-   :suppress:
-
-   plt.figure();
-
 .. ipython:: python
 
    df.plot();

doc/source/user_guide/io.rst

@@ -35,8 +35,8 @@ Other enhancements
 - The semantics for the ``copy`` keyword in ``__array__`` methods (i.e. called
   when using ``np.array()`` or ``np.asarray()`` on pandas objects) has been
   updated to work correctly with NumPy >= 2 (:issue:`57739`)
+- 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`)
--
 
 .. ---------------------------------------------------------------------------
 .. _whatsnew_230.notable_bug_fixes:

doc/source/user_guide/visualization.rst

@@ -30,6 +30,7 @@ Other enhancements
 ^^^^^^^^^^^^^^^^^^
 - :class:`pandas.api.typing.FrozenList` is available for typing the outputs of :attr:`MultiIndex.names`, :attr:`MultiIndex.codes` and :attr:`MultiIndex.levels` (:issue:`58237`)
 - :class:`pandas.api.typing.SASReader` is available for typing the output of :func:`read_sas` (:issue:`55689`)
+- :class:`pandas.api.typing.NoDefault` is available for typing ``no_default``
 - :func:`DataFrame.to_excel` now raises an ``UserWarning`` when the character count in a cell exceeds Excel's limitation of 32767 characters (:issue:`56954`)
 - :func:`pandas.merge` now validates the ``how`` parameter input (merge type) (:issue:`59435`)
 - :func:`read_spss` now supports kwargs to be passed to pyreadstat (:issue:`56356`)
@@ -44,22 +45,26 @@ Other enhancements
 - Users can globally disable any ``PerformanceWarning`` by setting the option ``mode.performance_warnings`` to ``False`` (:issue:`56920`)
 - :meth:`Styler.format_index_names` can now be used to format the index and column names (:issue:`48936` and :issue:`47489`)
 - :class:`.errors.DtypeWarning` improved to include column names when mixed data types are detected (:issue:`58174`)
+- :class:`Rolling` and :class:`Expanding` now support ``pipe`` method (:issue:`57076`)
 - :class:`Series` now supports the Arrow PyCapsule Interface for export (:issue:`59518`)
 - :func:`DataFrame.to_excel` argument ``merge_cells`` now accepts a value of ``"columns"`` to only merge :class:`MultiIndex` column header header cells (:issue:`35384`)
 - :meth:`DataFrame.corrwith` now accepts ``min_periods`` as optional arguments, as in :meth:`DataFrame.corr` and :meth:`Series.corr` (:issue:`9490`)
 - :meth:`DataFrame.cummin`, :meth:`DataFrame.cummax`, :meth:`DataFrame.cumprod` and :meth:`DataFrame.cumsum` methods now have a ``numeric_only`` parameter (:issue:`53072`)
 - :meth:`DataFrame.ewm` now allows ``adjust=False`` when ``times`` is provided (:issue:`54328`)
 - :meth:`DataFrame.fillna` and :meth:`Series.fillna` can now accept ``value=None``; for non-object dtype the corresponding NA value will be used (:issue:`57723`)
 - :meth:`DataFrame.pivot_table` and :func:`pivot_table` now allow the passing of keyword arguments to ``aggfunc`` through ``**kwargs`` (:issue:`57884`)
+- :meth:`DataFrame.to_json` now encodes ``Decimal`` as strings instead of floats (:issue:`60698`)
 - :meth:`Series.cummin` and :meth:`Series.cummax` now supports :class:`CategoricalDtype` (:issue:`52335`)
 - :meth:`Series.plot` now correctly handle the ``ylabel`` parameter for pie charts, allowing for explicit control over the y-axis label (:issue:`58239`)
 - :meth:`DataFrame.plot.scatter` argument ``c`` now accepts a column of strings, where rows with the same string are colored identically (:issue:`16827` and :issue:`16485`)
 - :func:`read_parquet` accepts ``to_pandas_kwargs`` which are forwarded to :meth:`pyarrow.Table.to_pandas` which enables passing additional keywords to customize the conversion to pandas, such as ``maps_as_pydicts`` to read the Parquet map data type as python dictionaries (:issue:`56842`)
+- :meth:`.DataFrameGroupBy.transform`, :meth:`.SeriesGroupBy.transform`, :meth:`.DataFrameGroupBy.agg`, :meth:`.SeriesGroupBy.agg`, :meth:`.SeriesGroupBy.apply`, :meth:`.DataFrameGroupBy.apply` now support ``kurt`` (:issue:`40139`)
 - :meth:`DataFrameGroupBy.transform`, :meth:`SeriesGroupBy.transform`, :meth:`DataFrameGroupBy.agg`, :meth:`SeriesGroupBy.agg`, :meth:`RollingGroupby.apply`, :meth:`ExpandingGroupby.apply`, :meth:`Rolling.apply`, :meth:`Expanding.apply`, :meth:`DataFrame.apply` with ``engine="numba"`` now supports positional arguments passed as kwargs (:issue:`58995`)
 - :meth:`Rolling.agg`, :meth:`Expanding.agg` and :meth:`ExponentialMovingWindow.agg` now accept :class:`NamedAgg` aggregations through ``**kwargs`` (:issue:`28333`)
 - :meth:`Series.map` can now accept kwargs to pass on to func (:issue:`59814`)
 - :meth:`pandas.concat` will raise a ``ValueError`` when ``ignore_index=True`` and ``keys`` is not ``None`` (:issue:`59274`)
 - :meth:`str.get_dummies` now accepts a  ``dtype`` parameter to specify the dtype of the resulting DataFrame (:issue:`47872`)
+- Implemented :meth:`Series.str.isascii` and :meth:`Series.str.isascii` (:issue:`59091`)
 - Multiplying two :class:`DateOffset` objects will now raise a ``TypeError`` instead of a ``RecursionError`` (:issue:`59442`)
 - Restore support for reading Stata 104-format and enable reading 103-format dta files (:issue:`58554`)
 - Support passing a :class:`Iterable[Hashable]` input to :meth:`DataFrame.drop_duplicates` (:issue:`59237`)
@@ -684,6 +689,7 @@ MultiIndex
 - :meth:`DataFrame.melt` would not accept multiple names in ``var_name`` when the columns were a :class:`MultiIndex` (:issue:`58033`)
 - :meth:`MultiIndex.insert` would not insert NA value correctly at unified location of index -1 (:issue:`59003`)
 - :func:`MultiIndex.get_level_values` accessing a :class:`DatetimeIndex` does not carry the frequency attribute along (:issue:`58327`, :issue:`57949`)
+- Bug in :class:`DataFrame` arithmetic operations in case of unaligned MultiIndex columns (:issue:`60498`)
 -
 
 I/O
@@ -797,6 +803,7 @@ Other
 - Bug in :meth:`Series.dt` methods in :class:`ArrowDtype` that were returning incorrect values. (:issue:`57355`)
 - Bug in :meth:`Series.rank` that doesn't preserve missing values for nullable integers when ``na_option='keep'``. (:issue:`56976`)
 - Bug in :meth:`Series.replace` and :meth:`DataFrame.replace` inconsistently replacing matching instances when ``regex=True`` and missing values are present. (:issue:`56599`)
+- Bug in :meth:`Series.replace` and :meth:`DataFrame.replace` throwing ``ValueError`` when ``regex=True`` and all NA values. (:issue:`60688`)
 - Bug in :meth:`Series.to_string` when series contains complex floats with exponents (:issue:`60405`)
 - Bug in :meth:`read_csv` where chained fsspec TAR file and ``compression="infer"`` fails with ``tarfile.ReadError`` (:issue:`60028`)
 - Bug in Dataframe Interchange Protocol implementation was returning incorrect results for data buffers' associated dtype, for string and datetime columns (:issue:`54781`)