Log message:
py-pandas: update to 2.2.3.

Pandas 2.2.3 is the first version of pandas that is generally
compatible with the upcoming Python 3.13, and both wheels for
free-threaded and normal Python 3.13 will be uploaded for this
release.

Log message:
*: clean-up after python38 removal

Log message:
py-pandas: updated to 2.2.2

Pandas 2.2.2 is now compatible with numpy 2.0

Pandas 2.2.2 is the first version of pandas that is generally compatible with \ 
the upcoming numpy 2.0 release, and wheels for pandas 2.2.2 will work with both \ 
numpy 1.x and 2.x.

One major caveat is that arrays created with numpy 2.0’s new StringDtype will \ 
convert to object dtyped arrays upon Series/DataFrame creation. Full support for \ 
numpy 2.0’s StringDtype is expected to land in pandas 3.0.

As usual please report any bugs discovered to our issue tracker

Fixed regressions

DataFrame.__dataframe__() was producing incorrect data buffers when the a \ 
column’s type was a pandas nullable on with missing values (GH 56702)
DataFrame.__dataframe__() was producing incorrect data buffers when the a \ 
column’s type was a pyarrow nullable on with missing values (GH 57664)
Avoid issuing a spurious DeprecationWarning when a custom DataFrame or Series \ 
subclass method is called (GH 57553)
Fixed regression in precision of to_datetime() with string and unit input (GH 57051)
Bug fixes

DataFrame.__dataframe__() was producing incorrect data buffers when the \ 
column’s type was nullable boolean (GH 55332)
DataFrame.__dataframe__() was showing bytemask instead of bitmask for \ 
'string[pyarrow]' validity buffer (GH 57762)
DataFrame.__dataframe__() was showing non-null validity buffer (instead of None) \ 
'string[pyarrow]' without missing values (GH 57761)
DataFrame.to_sql() was failing to find the right table when using the schema \ 
argument (GH 57539)

Log message:
py-pandas: updated to 2.2.1

What’s new in 2.2.1 (February 22, 2024)

These are the changes in pandas 2.2.1. See Release notes for a full changelog \ 
including other versions of pandas.

Enhancements

Added pyarrow pip extra so users can install pandas and pyarrow with pip with \ 
pip install pandas[pyarrow] (GH 54466)
Fixed regressions

Fixed memory leak in read_csv() (GH 57039)
Fixed performance regression in Series.combine_first() (GH 55845)
Fixed regression causing overflow for near-minimum timestamps (GH 57150)
Fixed regression in concat() changing long-standing behavior that always sorted \ 
the non-concatenation axis when the axis was a DatetimeIndex (GH 57006)
Fixed regression in merge_ordered() raising TypeError for \ 
fill_method="ffill" and how="left" (GH 57010)
Fixed regression in pandas.testing.assert_series_equal() defaulting to \ 
check_exact=True when checking the Index (GH 57067)
Fixed regression in read_json() where an Index would be returned instead of a \ 
RangeIndex (GH 57429)
Fixed regression in wide_to_long() raising an AttributeError for string columns \ 
(GH 57066)
Fixed regression in DataFrameGroupBy.idxmin(), DataFrameGroupBy.idxmax(), \ 
SeriesGroupBy.idxmin(), SeriesGroupBy.idxmax() ignoring the skipna argument (GH \ 
57040)
Fixed regression in DataFrameGroupBy.idxmin(), DataFrameGroupBy.idxmax(), \ 
SeriesGroupBy.idxmin(), SeriesGroupBy.idxmax() where values containing the \ 
minimum or maximum value for the dtype could produce incorrect results (GH \ 
57040)
Fixed regression in CategoricalIndex.difference() raising KeyError when other \ 
contains null values other than NaN (GH 57318)
Fixed regression in DataFrame.groupby() raising ValueError when grouping by a \ 
Series in some cases (GH 57276)
Fixed regression in DataFrame.loc() raising IndexError for non-unique, masked \ 
dtype indexes where result has more than 10,000 rows (GH 57027)
Fixed regression in DataFrame.loc() which was unnecessarily throwing \ 
“incompatible dtype warning” when expanding with partial row indexer and \ 
multiple columns (see PDEP6) (GH 56503)
Fixed regression in DataFrame.map() with na_action="ignore" not being \ 
respected for NumPy nullable and ArrowDtypes (GH 57316)
Fixed regression in DataFrame.merge() raising ValueError for certain types of \ 
3rd-party extension arrays (GH 57316)
Fixed regression in DataFrame.query() with all NaT column with object dtype (GH \ 
57068)
Fixed regression in DataFrame.shift() raising AssertionError for axis=1 and \ 
empty DataFrame (GH 57301)
Fixed regression in DataFrame.sort_index() not producing a stable sort for a \ 
index with duplicates (GH 57151)
Fixed regression in DataFrame.to_dict() with orient='list' and datetime or \ 
timedelta types returning integers (GH 54824)
Fixed regression in DataFrame.to_json() converting nullable integers to floats \ 
(GH 57224)
Fixed regression in DataFrame.to_sql() when method="multi" is passed \ 
and the dialect type is not Oracle (GH 57310)
Fixed regression in DataFrame.transpose() with nullable extension dtypes not \ 
having F-contiguous data potentially causing exceptions when used (GH 57315)
Fixed regression in DataFrame.update() emitting incorrect warnings about \ 
downcasting (GH 57124)
Fixed regression in DataFrameGroupBy.idxmin(), DataFrameGroupBy.idxmax(), \ 
SeriesGroupBy.idxmin(), SeriesGroupBy.idxmax() ignoring the skipna argument (GH \ 
57040)
Fixed regression in DataFrameGroupBy.idxmin(), DataFrameGroupBy.idxmax(), \ 
SeriesGroupBy.idxmin(), SeriesGroupBy.idxmax() where values containing the \ 
minimum or maximum value for the dtype could produce incorrect results (GH \ 
57040)
Fixed regression in ExtensionArray.to_numpy() raising for non-numeric masked \ 
dtypes (GH 56991)
Fixed regression in Index.join() raising TypeError when joining an empty index \ 
to a non-empty index containing mixed dtype values (GH 57048)
Fixed regression in Series.astype() introducing decimals when converting from \ 
integer with missing values to string dtype (GH 57418)
Fixed regression in Series.pct_change() raising a ValueError for an empty Series \ 
(GH 57056)
Fixed regression in Series.to_numpy() when dtype is given as float and the data \ 
contains NaNs (GH 57121)
Fixed regression in addition or subtraction of DateOffset objects with \ 
millisecond components to datetime64 Index, Series, or DataFrame (GH 57529)

Bug fixes

Fixed bug in pandas.api.interchange.from_dataframe() which was raising for \ 
Nullable integers (GH 55069)
Fixed bug in pandas.api.interchange.from_dataframe() which was raising for empty \ 
inputs (GH 56700)
Fixed bug in pandas.api.interchange.from_dataframe() which wasn’t converting \ 
columns names to strings (GH 55069)
Fixed bug in DataFrame.__getitem__() for empty DataFrame with Copy-on-Write \ 
enabled (GH 57130)
Fixed bug in PeriodIndex.asfreq() which was silently converting frequencies \ 
which are not supported as period frequencies instead of raising an error (GH \ 
56945)

Log message:
py-pandas: needs at least gcc 10 because of __has_builtin

Log message:
py-pandas: updated to 2.2.0

Pandas 2.2.0

This release includes some new features, bug fixes, and performance \ 
improvements. We recommend that all users upgrade to this version.
https://pandas.pydata.org/pandas-docs/version/2.2.0/whatsnew/v2.2.0.html

Log message:
py-pandas: updated to 2.1.4

What’s new in 2.1.4

Fixed regressions

Fixed regression when trying to read a pickled pandas DataFrame from pandas 1.3

Bug fixes

Bug in Series constructor raising DeprecationWarning when index is a list of Series
Bug in Series when trying to cast date-like string inputs to ArrowDtype of \ 
pyarrow.timestamp
Bug in DataFrame.apply() where passing raw=True ignored args passed to the \ 
applied function
Bug in Index.__getitem__() returning wrong result for Arrow dtypes and negative \ 
stepsize
Fixed bug in to_numeric() converting to extension dtype for \ 
string[pyarrow_numpy] dtype
Fixed bug in DataFrameGroupBy.min() and DataFrameGroupBy.max() not preserving \ 
extension dtype for empty object
Fixed bug in DataFrame.__setitem__() casting Index with object-dtype to PyArrow \ 
backed strings when infer_string option is set
Fixed bug in DataFrame.to_hdf() raising when columns have StringDtype
Fixed bug in Index.insert() casting object-dtype to PyArrow backed strings when \ 
infer_string option is set
Fixed bug in Series.__ne__() resulting in False for comparison between NA and \ 
string value for dtype="string[pyarrow_numpy]"
Fixed bug in Series.mode() not keeping object dtype when infer_string is set
Fixed bug in Series.reset_index() not preserving object dtype when infer_string \ 
is set
Fixed bug in Series.str.split() and Series.str.rsplit() when pat=None for \ 
ArrowDtype with pyarrow.string
Fixed bug in Series.str.translate() losing object dtype when string option is set

Log message:
py-pandas: updated to 2.1.3

Pandas 2.1.3

This is a patch release in the 2.1.x series and includes some regression and bug \ 
fixes, and a security fix. We recommend that all users upgrade to this version.

Log message:
py-pandas: updated to 2.1.2

2.1.2

Deprecations

Reverted deprecation of fill_method=None in DataFrame.pct_change(), \ 
Series.pct_change(), DataFrameGroupBy.pct_change(), and \ 
SeriesGroupBy.pct_change(); the values 'backfill', 'bfill', 'pad', and 'ffill' \ 
are still deprecated (GH 53491)

Fixed regressions

Fixed regression in DataFrame.join() where result has missing values and dtype \ 
is arrow backed string (GH 55348)
Fixed regression in rolling() where non-nanosecond index or on column would \ 
produce incorrect results (GH 55026, GH 55106, GH 55299)
Fixed regression in DataFrame.resample() which was extrapolating back to origin \ 
when origin was outside its bounds (GH 55064)
Fixed regression in DataFrame.sort_index() which was not sorting correctly when \ 
the index was a sliced MultiIndex (GH 55379)
Fixed regression in DataFrameGroupBy.agg() and SeriesGroupBy.agg() where if the \ 
option compute.use_numba was set to True, groupby methods not supported by the \ 
numba engine would raise a TypeError (GH 55520)
Fixed performance regression with wide DataFrames, typically involving methods \ 
where all columns were accessed individually (GH 55256, GH 55245)
Fixed regression in merge_asof() raising TypeError for by with datetime and \ 
timedelta dtypes (GH 55453)
Fixed regression in read_parquet() when reading a file with a string column \ 
consisting of more than 2 GB of string data and using the "string" \ 
dtype (GH 55606)
Fixed regression in DataFrame.to_sql() not roundtripping datetime columns \ 
correctly for sqlite when using detect_types (GH 55554)
Fixed regression in construction of certain DataFrame or Series subclasses (GH 54922)

Bug fixes

Fixed bug in DataFrameGroupBy reductions not preserving object dtype when \ 
infer_string is set (GH 55620)
Fixed bug in SeriesGroupBy.value_counts() returning incorrect dtype for string \ 
columns (GH 55627)
Fixed bug in Categorical.equals() if other has arrow backed string dtype (GH 55364)
Fixed bug in DataFrame.__setitem__() not inferring string dtype for \ 
zero-dimensional array with infer_string=True (GH 55366)
Fixed bug in DataFrame.idxmin() and DataFrame.idxmax() raising for arrow dtypes \ 
(GH 55368)
Fixed bug in DataFrame.interpolate() raising incorrect error message (GH 55347)
Fixed bug in Index.insert() raising when inserting None into Index with \ 
dtype="string[pyarrow_numpy]" (GH 55365)
Fixed bug in Series.all() and Series.any() not treating missing values correctly \ 
for dtype="string[pyarrow_numpy]" (GH 55367)
Fixed bug in Series.floordiv() for ArrowDtype (GH 55561)
Fixed bug in Series.mode() not sorting values for arrow backed string dtype (GH \ 
55621)
Fixed bug in Series.rank() for string[pyarrow_numpy] dtype (GH 55362)
Fixed bug in Series.str.extractall() for ArrowDtype dtype being converted to \ 
object (GH 53846)
Fixed bug where PDEP-6 warning about setting an item of an incompatible dtype \ 
was being shown when creating a new conditional column (GH 55025)
Silence Period[B] warnings introduced by GH 53446 during normal plotting \ 
activity (GH 55138)
Fixed bug in Series constructor not inferring string dtype when NA is the first \ 
value and infer_string is set (:issue:` 55655`)

Other

Fixed non-working installation of optional dependency group output_formatting. \ 
Replacing underscore _ with a dash - fixes broken dependency resolution. A \ 
correct way to use now is pip install pandas[output-formatting].

Log message:
python/wheel.mk: simplify a lot, and switch to 'installer' for installation

This follows the recommended bootstrap method (flit_core, build, installer).

However, installer installs different files than pip, so update PLISTs
for all packages using wheel.mk and bump their PKGREVISIONs.