Merge branch 'main' into to_datetime-micros

Author: jbrockmendel

.github/workflows/unit-tests.yml

@@ -320,8 +320,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        # Separate out macOS 13 and 14, since macOS 14 is arm64 only
-        os: [ubuntu-24.04, macOS-13, macOS-14, windows-2025]
+        os: [ubuntu-24.04, macos-15-intel, macos-15, windows-2025]
 
     timeout-minutes: 90
 

.pre-commit-config.yaml

@@ -19,7 +19,7 @@ ci:
     skip: [pyright, mypy]
 repos:
 -   repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.13.3
+    rev: v0.14.3
     hooks:
     -   id: ruff
         args: [--exit-non-zero-on-fix]
@@ -46,7 +46,7 @@ repos:
     -   id: codespell
         types_or: [python, rst, markdown, cython, c]
 -   repo: https://github.com/MarcoGorelli/cython-lint
-    rev: v0.17.0
+    rev: v0.18.1
     hooks:
     -   id: cython-lint
     -   id: double-quote-cython-strings
@@ -67,11 +67,11 @@ repos:
     -   id: trailing-whitespace
         args: [--markdown-linebreak-ext=md]
 -   repo: https://github.com/PyCQA/isort
-    rev: 6.1.0
+    rev: 7.0.0
     hooks:
     -   id: isort
 -   repo: https://github.com/asottile/pyupgrade
-    rev: v3.20.0
+    rev: v3.21.0
     hooks:
     -   id: pyupgrade
         args: [--py311-plus]
@@ -87,7 +87,7 @@ repos:
         types: [text]  # overwrite types: [rst]
         types_or: [python, rst]
 -   repo: https://github.com/sphinx-contrib/sphinx-lint
-    rev: v1.0.0
+    rev: v1.0.1
     hooks:
     - id: sphinx-lint
       args: ["--enable", "all", "--disable", "line-too-long"]

README.md

@@ -179,7 +179,7 @@ If you are simply looking to start working with the pandas codebase, navigate to
 
 You can also triage issues which may include reproducing bug reports, or asking for vital information such as version numbers or reproduction instructions. If you would like to start triaging issues, one easy way to get started is to [subscribe to pandas on CodeTriage](https://www.codetriage.com/pandas-dev/pandas).
 
-Or maybe through using pandas you have an idea of your own or are looking for something in the documentation and thinking ‘this can be improved’...you can do something about it!
+Or maybe through using pandas you have an idea of your own or are looking for something in the documentation and thinking ‘this can be improved’... you can do something about it!
 
 Feel free to ask questions on the [mailing list](https://groups.google.com/forum/?fromgroups#!forum/pydata) or on [Slack](https://pandas.pydata.org/docs/dev/development/community.html?highlight=slack#community-slack).
 

doc/source/user_guide/groupby.rst

@@ -137,7 +137,7 @@ We could naturally group by either the ``A`` or ``B`` columns, or both:
 
    ``df.groupby('A')`` is just syntactic sugar for ``df.groupby(df['A'])``.
 
-The above GroupBy will split the DataFrame on its index (rows). To split by columns, first do
+DataFrame groupby always operates along axis 0 (rows). To split by columns, first do
 a transpose:
 
 .. ipython::

doc/source/user_guide/io.rst

@@ -303,8 +303,6 @@ compression : {``'infer'``, ``'gzip'``, ``'bz2'``, ``'zip'``, ``'xz'``, ``'zstd'
   As an example, the following could be passed for faster compression and to
   create a reproducible gzip archive:
   ``compression={'method': 'gzip', 'compresslevel': 1, 'mtime': 1}``.
-
-  .. versionchanged:: 1.2.0 Previous versions forwarded dict entries for 'gzip' to ``gzip.open``.
 thousands : str, default ``None``
   Thousands separator.
 decimal : str, default ``'.'``
@@ -1472,7 +1470,7 @@ rather than reading the entire file into memory, such as the following:
    table
 
 
-By specifying a ``chunksize`` to ``read_csv``, the return
+By specifying a ``chunksize`` to :func:`read_csv` as a context manager, the return
 value will be an iterable object of type ``TextFileReader``:
 
 .. ipython:: python
@@ -1482,10 +1480,6 @@ value will be an iterable object of type ``TextFileReader``:
        for chunk in reader:
            print(chunk)
 
-.. versionchanged:: 1.2
-
-  ``read_csv/json/sas`` return a context-manager when iterating through a file.
-
 Specifying ``iterator=True`` will also return the ``TextFileReader`` object:
 
 .. ipython:: python

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

@@ -115,6 +115,8 @@ through the ``str`` accessor will work the same:
    class. The dtype can be constructed as ``pd.StringDtype(na_value=np.nan)``,
    but for general usage we recommend to use the shorter ``"str"`` alias.
 
+.. _string_migration_guide-differences:
+
 Overview of behavior differences and how to address them
 ---------------------------------------------------------