merge with main

Author: litang99

.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/whatsnew/v3.0.0.rst

@@ -737,7 +737,9 @@ Other Deprecations
 - Deprecated allowing ``fill_value`` that cannot be held in the original dtype (excepting NA values for integer and bool dtypes) in :meth:`Series.shift` and :meth:`DataFrame.shift` (:issue:`53802`)
 - Deprecated backward-compatibility behavior for :meth:`DataFrame.select_dtypes` matching "str" dtype when ``np.object_`` is specified (:issue:`61916`)
 - Deprecated option "future.no_silent_downcasting", as it is no longer used. In a future version accessing this option will raise (:issue:`59502`)
+- Deprecated silent casting of non-datetime 'other' to datetime in :meth:`Series.combine_first` (:issue:`62931`)
 - Deprecated slicing on a :class:`Series` or :class:`DataFrame` with a :class:`DatetimeIndex` using a ``datetime.date`` object, explicitly cast to :class:`Timestamp` instead (:issue:`35830`)
+- Deprecated support for the Dataframe Interchange Protocol (:issue:`56732`)
 - Deprecated the 'inplace' keyword from :meth:`Resampler.interpolate`, as passing ``True`` raises ``AttributeError`` (:issue:`58690`)
 
 .. ---------------------------------------------------------------------------
@@ -960,6 +962,7 @@ Categorical
 ^^^^^^^^^^^
 - Bug in :class:`Categorical` where constructing from a pandas :class:`Series` or :class:`Index` with ``dtype='object'`` did not preserve the categories' dtype as ``object``; now the ``categories.dtype`` is preserved as ``object`` for these cases, while numpy arrays and Python sequences with ``dtype='object'`` continue to infer the most specific dtype (for example, ``str`` if all elements are strings) (:issue:`61778`)
 - Bug in :func:`Series.apply` where ``nan`` was ignored for :class:`CategoricalDtype` (:issue:`59938`)
+- Bug in :func:`bdate_range` raising ``ValueError`` with frequency ``freq="cbh"`` (:issue:`62849`)
 - Bug in :func:`testing.assert_index_equal` raising ``TypeError`` instead of ``AssertionError`` for incomparable ``CategoricalIndex`` when ``check_categorical=True`` and ``exact=False`` (:issue:`61935`)
 - Bug in :meth:`Categorical.astype` where ``copy=False`` would still trigger a copy of the codes (:issue:`62000`)
 - Bug in :meth:`DataFrame.pivot` and :meth:`DataFrame.set_index` raising an ``ArrowNotImplementedError`` for columns with pyarrow dictionary dtype (:issue:`53051`)
@@ -974,13 +977,15 @@ Datetimelike
 - Bug in :class:`Timestamp` constructor failing to raise when given a ``np.datetime64`` object with non-standard unit (:issue:`25611`)
 - Bug in :func:`date_range` where the last valid timestamp would sometimes not be produced (:issue:`56134`)
 - Bug in :func:`date_range` where using a negative frequency value would not include all points between the start and end values (:issue:`56147`)
+- Bug in :func:`infer_freq` with a :class:`Series` with :class:`ArrowDtype` timestamp dtype incorrectly raising ``TypeError`` (:issue:`58403`)
 - Bug in :func:`to_datetime` where passing an ``lxml.etree._ElementUnicodeResult`` together with ``format`` raised  ``TypeError``. Now subclasses of ``str`` are handled. (:issue:`60933`)
 - Bug in :func:`tseries.api.guess_datetime_format` would fail to infer time format when "%Y" == "%H%M" (:issue:`57452`)
 - Bug in :func:`tseries.frequencies.to_offset` would fail to parse frequency strings starting with "LWOM" (:issue:`59218`)
 - Bug in :meth:`DataFrame.fillna` raising an ``AssertionError`` instead of ``OutOfBoundsDatetime`` when filling a ``datetime64[ns]`` column with an out-of-bounds timestamp. Now correctly raises ``OutOfBoundsDatetime``. (:issue:`61208`)
 - Bug in :meth:`DataFrame.min` and :meth:`DataFrame.max` casting ``datetime64`` and ``timedelta64`` columns to ``float64`` and losing precision (:issue:`60850`)
 - Bug in :meth:`Dataframe.agg` with df with missing values resulting in IndexError (:issue:`58810`)
 - Bug in :meth:`DateOffset.rollback` (and subclass methods) with ``normalize=True`` rolling back one offset too long (:issue:`32616`)
+- Bug in :meth:`DatetimeIndex.asof` with a string key giving incorrect results (:issue:`50946`)
 - Bug in :meth:`DatetimeIndex.is_year_start` and :meth:`DatetimeIndex.is_quarter_start` does not raise on Custom business days frequencies bigger then "1C" (:issue:`58664`)
 - Bug in :meth:`DatetimeIndex.is_year_start` and :meth:`DatetimeIndex.is_quarter_start` returning ``False`` on double-digit frequencies (:issue:`58523`)
 - Bug in :meth:`DatetimeIndex.union` and :meth:`DatetimeIndex.intersection` when ``unit`` was non-nanosecond (:issue:`59036`)
@@ -1177,16 +1182,20 @@ Groupby/resample/rolling
 - Bug in :meth:`Rolling.apply` for ``method="table"`` where column order was not being respected due to the columns getting sorted by default. (:issue:`59666`)
 - Bug in :meth:`Rolling.apply` where the applied function could be called on fewer than ``min_period`` periods if ``method="table"``. (:issue:`58868`)
 - Bug in :meth:`Series.resample` could raise when the date range ended shortly before a non-existent time. (:issue:`58380`)
+- Bug in :meth:`Series.resample` raising error when resampling non-nanosecond resolutions out of bounds for nanosecond precision (:issue:`57427`)
 
 Reshaping
 ^^^^^^^^^
 - Bug in :func:`concat` with mixed integer and bool dtypes incorrectly casting the bools to integers (:issue:`45101`)
 - Bug in :func:`qcut` where values at the quantile boundaries could be incorrectly assigned (:issue:`59355`)
 - Bug in :meth:`DataFrame.combine_first` not preserving the column order (:issue:`60427`)
+- Bug in :meth:`DataFrame.combine_first` with non-unique columns incorrectly raising (:issue:`29135`)
+- Bug in :meth:`DataFrame.combine` with non-unique columns incorrectly raising (:issue:`51340`)
 - Bug in :meth:`DataFrame.explode` producing incorrect result for :class:`pyarrow.large_list` type (:issue:`61091`)
 - Bug in :meth:`DataFrame.join` inconsistently setting result index name (:issue:`55815`)
 - Bug in :meth:`DataFrame.join` when a :class:`DataFrame` with a :class:`MultiIndex` would raise an ``AssertionError`` when :attr:`MultiIndex.names` contained ``None``. (:issue:`58721`)
 - Bug in :meth:`DataFrame.merge` where merging on a column containing only ``NaN`` values resulted in an out-of-bounds array access (:issue:`59421`)
+- Bug in :meth:`Series.combine_first` incorrectly replacing ``None`` entries with ``NaN`` (:issue:`58977`)
 - Bug in :meth:`DataFrame.unstack` producing incorrect results when ``sort=False`` (:issue:`54987`, :issue:`55516`)
 - Bug in :meth:`DataFrame.unstack` raising an error with indexes containing ``NaN`` with ``sort=False`` (:issue:`61221`)
 - Bug in :meth:`DataFrame.merge` when merging two :class:`DataFrame` on ``intc`` or ``uintc`` types on Windows (:issue:`60091`, :issue:`58713`)

pandas/_libs/tslibs/offsets.pyx

@@ -5688,18 +5688,27 @@ def shift_month(stamp: datetime, months: int, day_opt: object = None) -> datetim
     cdef:
         int year, month, day
         int days_in_month, dy
+        npy_datetimestruct dts
+
+    if isinstance(stamp, _Timestamp):
+        creso = (<_Timestamp>stamp)._creso
+        val = (<_Timestamp>stamp)._value
+        pandas_datetime_to_datetimestruct(val, creso, &dts)
+    else:
+        # Plain datetime/date
+        pydate_to_dtstruct(stamp, &dts)
 
-    dy = (stamp.month + months) // 12
-    month = (stamp.month + months) % 12
+    dy = (dts.month + months) // 12
+    month = (dts.month + months) % 12
 
     if month == 0:
         month = 12
         dy -= 1
-    year = stamp.year + dy
+    year = dts.year + dy
 
     if day_opt is None:
         days_in_month = get_days_in_month(year, month)
-        day = min(stamp.day, days_in_month)
+        day = min(dts.day, days_in_month)
     elif day_opt == "start":
         day = 1
     elif day_opt == "end":

pandas/conftest.py

@@ -135,12 +135,14 @@ def pytest_collection_modifyitems(items, config) -> None:
     # Warnings from doctests that can be ignored; place reason in comment above.
     # Each entry specifies (path, message) - see the ignore_doctest_warning function
     ignored_doctest_warnings = [
+        ("api.interchange.from_dataframe", ".*Interchange Protocol is deprecated"),
         ("is_int64_dtype", "is_int64_dtype is deprecated"),
         ("is_interval_dtype", "is_interval_dtype is deprecated"),
         ("is_period_dtype", "is_period_dtype is deprecated"),
         ("is_datetime64tz_dtype", "is_datetime64tz_dtype is deprecated"),
         ("is_categorical_dtype", "is_categorical_dtype is deprecated"),
         ("is_sparse", "is_sparse is deprecated"),
+        ("DataFrame.__dataframe__", "Interchange Protocol is deprecated"),
         ("DataFrameGroupBy.fillna", "DataFrameGroupBy.fillna is deprecated"),
         ("DataFrameGroupBy.corrwith", "DataFrameGroupBy.corrwith is deprecated"),
         ("NDFrame.replace", "Series.replace without 'value'"),