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forked from pool/python-pandas

Accepting request 1171775 from home:bnavigator:branches:devel:languages:python:numeric

- Update 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)
- Remove obsolete python39 multibuild
- Add pandas-pr58269-pyarrow16xpass.patch
  gh#pandas-dev/pandas#58269

OBS-URL: https://build.opensuse.org/request/show/1171775
OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-pandas?expand=0&rev=114
This commit is contained in:
2024-05-06 08:07:03 +00:00
committed by Git OBS Bridge
parent 38bd51831f
commit 1654daaf58
7 changed files with 102 additions and 16 deletions

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Tue Apr 30 18:08:56 UTC 2024 - Ben Greiner <code@bnavigator.de>
- Update 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 2.0s new StringDtype
will convert to object dtyped arrays upon Series/DataFrame
creation. Full support for numpy 2.0s 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 columns type was a pandas nullable on with missing
values (GH 56702)
* DataFrame.__dataframe__() was producing incorrect data buffers
when the a columns 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 columns 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)
- Remove obsolete python39 multibuild
- Add pandas-pr58269-pyarrow16xpass.patch
gh#pandas-dev/pandas#58269
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Mon Mar 4 20:44:10 UTC 2024 - Ben Greiner <code@bnavigator.de>