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
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Tue Apr 30 18:08:56 UTC 2024 - Ben Greiner <code@bnavigator.de>
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- Update to 2.2.2
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* Pandas 2.2.2 is now compatible with numpy 2.0
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* Pandas 2.2.2 is the first version of pandas that is generally
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compatible with the upcoming numpy 2.0 release, and wheels for
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pandas 2.2.2 will work with both numpy 1.x and 2.x. One major
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caveat is that arrays created with numpy 2.0’s new StringDtype
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will convert to object dtyped arrays upon Series/DataFrame
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creation. Full support for numpy 2.0’s StringDtype is expected
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to land in pandas 3.0.
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* As usual please report any bugs discovered to our issue tracker
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## Fixed regressions
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* DataFrame.__dataframe__() was producing incorrect data buffers
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when the a column’s type was a pandas nullable on with missing
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values (GH 56702)
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* DataFrame.__dataframe__() was producing incorrect data buffers
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when the a column’s type was a pyarrow nullable on with missing
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values (GH 57664)
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* Avoid issuing a spurious DeprecationWarning when a custom
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DataFrame or Series subclass method is called (GH 57553)
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* Fixed regression in precision of to_datetime() with string and
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unit input (GH 57051)
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## Bug fixes
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* DataFrame.__dataframe__() was producing incorrect data buffers
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when the column’s type was nullable boolean (GH 55332)
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* DataFrame.__dataframe__() was showing bytemask instead of
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bitmask for 'string[pyarrow]' validity buffer (GH 57762)
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* DataFrame.__dataframe__() was showing non-null validity buffer
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(instead of None) 'string[pyarrow]' without missing values (GH
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57761)
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* DataFrame.to_sql() was failing to find the right table when
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using the schema argument (GH 57539)
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- Remove obsolete python39 multibuild
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- Add pandas-pr58269-pyarrow16xpass.patch
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gh#pandas-dev/pandas#58269
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-------------------------------------------------------------------
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Mon Mar 4 20:44:10 UTC 2024 - Ben Greiner <code@bnavigator.de>
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