Make working with "relational" or "labeled" data both easy and intuitive
pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. It aims to be the fundamental high-level building block for
doing practical, real world data analysis in Python. Additionally, it has the broader goal of becoming the most powerful and flexible open source data analysis / manipulation tool available in any language.
- Sources inherited from project devel:languages:python:numeric
- Devel package for openSUSE:Factory
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16
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- Links to openSUSE:Factory / python-pandas
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Source Files (show unmerged sources)
Filename | Size | Changed |
---|---|---|
_constraints | 0000000163 163 Bytes | |
_multibuild | 0000000123 123 Bytes | |
_service | 0000000605 605 Bytes | |
pandas-2.2.2.tar.gz | 0050782448 48.4 MB | |
pandas-pr58269-pyarrow16xpass.patch | 0000001537 1.5 KB | |
python-pandas.changes | 0000226878 222 KB | |
python-pandas.spec | 0000022601 22.1 KB |
Latest Revision
Dirk Mueller (dirkmueller)
accepted
request 1171775
from
Benjamin Greiner (bnavigator)
(revision 114)
- 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
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