This package provides the [computation] extra for python-pandas
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Requires
License
BSD-3-Clause
Changelog
* Mon Aug 24 2026 Markéta Machová <mmachova@suse.com>
- Add np25.patch to fix tests with numpy 2.5
- Hotfix dirty hack which broke with recent python-rpm-macros
* Tue Jul 28 2026 Ben Greiner <code@bnavigator.de>
- Update to 3.0.5
* Fixed a regression where the pandas 3.0.4 wheels could crash
with a segmentation fault on Python 3.14 (and other datetime
code paths), because they were built against an incompatible
numpy version (GH 66086)
- Re-enable xdist, the resource usage penalty when not used is too
high. Use --without xdist when troubleshooting.
* update constraints for increased job limit
* Tue Jul 21 2026 Dirk Müller <dmueller@suse.com>
- avoid xdist - makes troubleshooting testsuite failures quite hard
* Thu Jul 16 2026 Dirk Müller <dmueller@suse.com>
- revert to 3.0.3: 3.0.4 was yanked due to crashes in date-time
related functions
* Wed Jul 15 2026 Steve Kowalik <steven.kowalik@suse.com>
- Update to 3.0.4:
[#]# Core Architecture & Structural Enhancements
* String columns are now inferred as a dedicated str data type by default
instead of the generic NumPy object type.
* Columns with the new str dtype can only store strings or missing values,
entirely rejecting non-string inputs.
* Copy-on-Write (CoW) is now the default and only mode, ensuring
predictable data mutations across indexing operations.
* Because modifications now strictly return copies, traditional multi-step
chained assignments will no longer work.
* The option mode.copy_on_write no longer has an impact.
* Support for the pd.col() syntax simplifies referencing columns by name to
build expressions natively.
* The pd.col() syntax provides an elegant alternative to using complex
lambda functions inside DataFrame.assign().
* DataFrame and Series natively support the Arrow PyCapsule Interface for
efficient, zero-copy data exchanges.
* The default resolution for constructing datetime-like data shifts from
nanoseconds to microseconds.
* Version 3.0 explicitly requires Python 3.11 or higher.
[#]# Data Merging & Transformation Updates
* Added support for pd.col() expressions in Series.case_when()
* Merging methods now officially support left_anti and right_anti arguments
within the how parameter.
* The how parameter string inputs are now rigorously validated during a
merge operation.
* The pandas.merge() function now successfully propagates the attrs
dictionary when inputs contain identical tags.
* DataFrame.pivot_table() now accepts flexible, additional keyword
arguments forwarded to aggfunc.
* Passing ignore_index=True while simultaneously defining keys inside
concat() now throws a strict ValueError.
* Using DataFrame.agg() on axis=1 with a function that attempts to relabel
the index will raise a NotImplementedError.
[#]# Missing Value Handling & Styling Improvements
* The missing value sentinel for the new default string types is uniformly
set as NaN (np.nan).
* fillna() can accept a literal None, automatically resolving it to the
appropriate data-type-specific NA value.
* Users can now seamlessly execute DataFrame.fillna() along axis=1 using
dictionary or Series mappings.
* The Styler object introduces Styler.to_typst() to write formatted data
directly to Typst-compliant files.
* Users can now apply dedicated format treatments to index and column
header names using Styler.format_index_names().
* Frozenset elements contained within pandas data structures are now
natively recognized and printed cleanly.
[#]# Input / Output (I/O) Enhancements
* The errors.DtypeWarning is upgraded to include specific column names when
mixed types are caught.
* The merge_cells parameter in to_excel() accepts "columns" to target
MultiIndex header columns uniquely.
* A brand-new autofilter parameter within to_excel() automatically applies
native filters to columns.
* The if_exists parameter in to_sql() gains a "delete_rows" option to wipe
records prior to writing new entries.
[#]# Groupby & System Configurations
* DataFrameGroupBy.prod() now evaluates unobserved groups as 1 rather than
evaluating them as missing values.
* The all() and any() operations on DataFrameGroupBy now evaluate
unobserved groups as True and False.
* DataFrameGroupBy.groups() has been updated to fully include tracking data
for unobserved categorical groups.
* Configuring system configurations is streamlined as set_option() now
accepts a dictionary of multiple parameters.
[#]# Bug fixes
* Fixed a bug in Series.rank() with period dtype and missing values, always
sorting missing values at the top, regardless of the na_option value
* Fixed a bug in Series.var() computing the variance of complex numbers
incorrectly
* Fixed a bug in to_hdf() with string columns raising an error when using
compression
* Fixed a bug in the sum() method with python-backed string dtype returning
incorrect value for an empty Series and ignoring the min_count argument
* Fixed a bug when using col() with Python functions bool(), iter(),
copy(), and deepcopy() either failed or produced incorrect results; these
now all raise a TypeError
* Fixed a bug where col() and expressions derived from it failed with
power (**) and matrix multiplication (@) operators
* Fixed a bug where DataFrame.div() ignored the axis argument when used
with level for MultiIndex columns
* Fixed a bug in the DataFrame constructor when passed a Series or Index
correctly handling Copy-on-Write
* Allow ExtensionArray to have dtypes involving numpy.void
* Fixed a bug in col() where unary operators (-, +, abs) were not supported
* Prevent buffer overflow in Rolling.corr() and Rolling.cov() with variable
windows when passing other with a longer index than the original window
- The consortium-standard package is no longer built, since that extra has
been removed.
- Dropped patches, merged upstream:
* pandas-pr61132-dropna.patch
* pandas-pr62553-numexpr.patch
* pandas-pr63406-meson-types.patch
* pandas-pr62863.patch
* pandas-pr63143.patch
* Mon Jun 22 2026 Josef Melcr <josef.melcr@suse.com>
- Add upstream pandas-pr62863.patch and pandas-pr63143.patch to
fix testsuite failures with GCC 16
* Mon Jun 15 2026 Dirk Müller <dmueller@suse.com>
- skip testing for python 3.11
* Thu Apr 16 2026 Markéta Machová <mmachova@suse.com>
- Add upstream pandas-pr63406-meson-types.patch to fix build with
meson 1.11
- Refresh test python flavors
* Thu Dec 18 2025 Markéta Machová <mmachova@suse.com>
- update to 2.3.3
* compatibility with Python 3.14
* Improvements and fixes for the StringDtype
* Fix bug in Series.str methods
* Fix bug in groupby() with sum() and unobserved categories
resulting in 0 instead of the empty string
- Add upstream pandas-pr62553-numexpr.patch to fix compatibility
with numexpr 2.13
* Sun Sep 14 2025 Dirk Müller <dmueller@suse.com>
- update to 2.3.2:
* Fix to_json() with orient="table" to correctly use the
“string” type in the JSON Table Schema for StringDtype columns
* Boolean operations (|, &, ^) with bool-dtype objects on the
left and StringDtype objects on the right now cast the string
to bool, with a deprecation warning
* Fixed match(), fullmatch() and contains() string methods with
compiled regex for the Arrow-backed string dtype
* Bug in Series.replace() and DataFrame.replace() inconsistently
replacing matching values when missing values are present
for string dtypes
* Fri Jul 11 2025 Ben Greiner <code@bnavigator.de>
- Update to 2.3.1
* This release includes some improvements and fixes to the future
string data type (preview feature for the upcoming pandas 3.0)
[#]# Improvements and fixes for the StringDtype
* Comparisons between different string dtypes
* Index set operations ignore empty RangeIndex and object dtype
Index
[#]# Bug fixes
* Bug in DataFrameGroupBy.min(), DataFrameGroupBy.max(),
Resampler.min(), Resampler.max() where all NA values of string
dtype would return float instead of string dtype (GH 60810)
* Bug in DataFrame.join() incorrectly downcasting object-dtype
indexes (GH 61771)
* Bug in DataFrame.sum() with axis=1, DataFrameGroupBy.sum() or
SeriesGroupBy.sum() with skipna=True, and Resampler.sum() with
all NA values of StringDtype resulted in 0 instead of the empty
string "" (GH 60229)
* Fixed bug in DataFrame.explode() and Series.explode() where
methods would fail with dtype="str" (GH 61623)
* Fixed bug in unpickling objects pickled in pandas versions
pre-2.3.0 that used StringDtype (GH 61763)
- Release 2.3.0
[#]# Enhancements
* The semantics for the copy keyword in __array__ methods (i.e.
called when using np.array() or np.asarray() on pandas objects)
has been updated to work correctly with NumPy >= 2 (GH 57739)
* Series.str.decode() result now has StringDtype when
future.infer_string is True (GH 60709)
* to_hdf() and to_hdf() now round-trip with StringDtype (GH
60663)
* Improved repr of NumpyExtensionArray to account for NEP51 (GH
61085)
* The Series.str.decode() has gained the argument dtype to
control the dtype of the result (GH 60940)
* The cumsum(), cummin(), and cummax() reductions are now
implemented for StringDtype columns (GH 60633)
* The sum() reduction is now implemented for StringDtype columns
(GH 59853)
[#]# Deprecations
* Deprecated allowing non-bool values for na in str.contains(),
str.startswith(), and str.endswith() for dtypes that do not
already disallow these (GH 59615)
* Deprecated the "pyarrow_numpy" storage option for StringDtype
(GH 60152)
* The deprecation of setting the argument include_groups to True
in DataFrameGroupBy.apply() has been promoted from a
DeprecationWarning to FutureWarning; only False will be allowed
(GH 7155)
[#]# Bug fixes
[#]## Numeric
* Bug in Series.mode() and DataFrame.mode() with dropna=False
where not all dtypes would sort in the presence of NA values
(GH 60702)
* Bug in Series.round() where a TypeError would always raise with
object dtype (GH 61206)
[#]## Strings
* Bug in Series.__pos__() and DataFrame.__pos__() where an
Exception was not raised for StringDtype with storage="pyarrow"
(GH 60710)
* Bug in Series.rank() for StringDtype with storage="pyarrow"
that incorrectly returned integer results with method="average"
and raised an error if it would truncate results (GH 59768)
* Bug in Series.replace() with StringDtype when replacing with a
non-string value was not upcasting to object dtype (GH 60282)
* Bug in Series.str.center() with StringDtype with
storage="pyarrow" not matching the python behavior in corner
cases with an odd number of fill characters (GH 54792)
* Bug in Series.str.replace() when n < 0 for StringDtype with
storage="pyarrow" (GH 59628)
* Bug in Series.str.slice() with negative step with ArrowDtype
and StringDtype with storage="pyarrow" giving incorrect results
(GH 59710)
[#]## Indexing
Bug in Index.get_indexer() round-tripping through string dtype
when infer_string is enabled (GH 55834)
[#]## I/O
* Bug in DataFrame.to_excel() which stored decimals as strings
instead of numbers (GH 49598)
[#]## Other
* Fixed usage of inspect when the optional dependencies pyarrow
or jinja2 are not installed (GH 60196)
- Drop patches:
* timedelta.patch
* pandas-pr60545-arrow-exception.patch
* pandas-pr60584-60586-mpl-vert.patch
- Refresh dropna.patch to pandas-pr61132-dropna.patch
* gh#pandas-dev/pandas#61132
* Thu Mar 20 2025 Markéta Machová <mmachova@suse.com>
- Add dropna.patch and timedelta.patch to fix tests with Numpy 2.2
* Thu Feb 20 2025 Ben Greiner <code@bnavigator.de>
- Support pyarrow 19
* Add pandas-pr60545-arrow-exception.patch
gh#pandas-dev/pandas#60545
* Skip TestParquetPyArrow.test_roundtrip_decimal: Would require
gh#pandas-dev/pandas#60755 and all other backports of the new
string type system.
* Fri Feb 07 2025 Ben Greiner <code@bnavigator.de>
- Add pandas-pr60584-60586-mpl-vert.patch
* Fixes matplotlib deprecation errors in the test suite
* gh#pandas-dev/pandas#60584
* backported in gh#pandas-dev/pandas#60586
* Fri Dec 13 2024 Steve Kowalik <steven.kowalik@suse.com>
- Change skipped tests to also support Python 3.13.
* Wed Nov 27 2024 Markéta Machová <mmachova@suse.com>
- Drop tests-nomkl.patch and tests-wasm.patch, not needed anymore
- Skip a test failing with new xarray
* Fri Oct 25 2024 Steve Kowalik <steven.kowalik@suse.com>
- Skip two tests that fail with Numpy 2.1.
* Fri Oct 11 2024 Steve Kowalik <steven.kowalik@suse.com>
- Prepare for Python 3.13, by skipping it if we aren't building for it.
* Tue Oct 01 2024 John Paul Adrian Glaubitz <adrian.glaubitz@suse.com>
- Update to 2.2.3
* Bug in eval() on complex including division /
discards imaginary part. (GH 21374)
* Minor fixes for numpy 2.1 compatibility. (GH 59444)
* Missing licenses for 3rd party dependencies were
added back into the wheels. (GH 58632)
- Drop pandas-pr58269-pyarrow16xpass.patch, merged upstream
- Drop pandas-pr58484-matplotlib.patch, merged upstream
- Drop pandas-pr59175-matplotlib.patch, merged upstream
- Drop pandas-pr59353-np2eval.patch, merged upstream
- Drop tests-npdev.patch, merged upstream
- Drop tests-timedelta.patch, merged upstream
- Refresh tests-nomkl.patch
- Renumber remaining patches
* Mon Sep 16 2024 Markéta Machová <mmachova@suse.com>
- Add bunch of patches to fix the testsuite with NumPy 2.1
* tests-wasm.patch
* tests-nomkl.patch
* tests-timedelta.patch
* tests-npdev.patch
- Skip one test failing with new timezone, the patch would be too big
* Sun Sep 08 2024 Ben Greiner <code@bnavigator.de>
- Drop pandas-pr58720-xarray-dp.patch: It does no longer xfail
* Wed Aug 28 2024 Ben Greiner <code@bnavigator.de>
- Skip overflowing tests on 32-bit
* Sun Aug 25 2024 Ben Greiner <code@bnavigator.de>
- Add pandas-pr59353-np2eval.patch
* gh#pandas-dev/pandas#59353
* gh#pandas-dev/pandas#58548
* Thu Jul 11 2024 Ben Greiner <code@bnavigator.de>
- Add pandas-pr59175-matplotlib.patch -- gh#pandas-dev/pandas#59175
* Sun May 12 2024 Matej Cepl <mcepl@cepl.eu>
- Add pandas-pr58269-pyarrow16xpass.patch
(gh#pandas-dev/pandas!58269)
- Add pandas-pr58720-xarray-dp.patch
(gh#pandas-dev/pandas!58720), which makes pandas compatible
with the modern xarray
- Add pandas-pr58484-matplotlib.patch
(gh#pandas-dev/pandas!58484), which makes pandas compatible
with the modern matplotlib
- Skip also test_plot_scatter_shape (gh#pandas-dev/pandas#58851)
* Thu May 09 2024 Matej Cepl <mcepl@cepl.eu>
- Skip build on Python 3.10 ... too many dependencies are missing.
* Tue Apr 30 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 2.0’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-nul