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| Name: python310-sklearn-pandas | Distribution: openSUSE Tumbleweed |
| Version: 2.2.0 | Vendor: openSUSE |
| Release: 2.9 | Build date: Mon Feb 6 09:06:15 2023 |
| Group: Development/Languages/Python | Build host: reproducible |
| Size: 77810 | Source RPM: python-sklearn-pandas-2.2.0-2.9.src.rpm |
| Packager: https://bugs.opensuse.org | |
| Url: https://github.com/scikit-learn-contrib/sklearn-pandas | |
| Summary: Pandas integration with sklearn | |
This module provides a bridge between Scikit-Learn's machine learning methods and pandas-style Data Frames.
BSD-2-Clause AND Zlib
* Mon Feb 06 2023 Daniel Garcia <daniel.garcia@suse.com>
- Disable broken tests gh#scikit-learn-contrib/sklearn-pandas#248
* Sat Feb 12 2022 Arun Persaud <arun@gmx.de>
- update to version 2.2.0:
* Added an ability to provide callable functions instead of static
column list.
- changes from version 2.1.0:
* Removed test for Python 3.6 and added Python 3.9
* Added deprecation warning for NumericalTransformer
* Fixed pickling issue causing integration issues with Baikal.
* Started publishing package to conda repo
* Thu Jan 28 2021 Ben Greiner <code@bnavigator.de>
- update to version 2.0.4
* Explicitly handling serialization (#224)
* document fixes
* Making transform function thread safe (#194)
* Switched to nox for unit testing (#226)
- Changlog for 2.0.3
* Added elapsed time information for each feature.
- Skip python36 build because of SciPy 1.6.0
- Get the GitHub archive for the tests and run them
- No extra mock required
* Sat Oct 10 2020 Arun Persaud <arun@gmx.de>
- specfile:
* updated versions of required packages
- update to version 2.0.2:
* Fix DataFrameMapper drop_cols attribute naming consistency with
scikit-learn and initialization.
- changes from version 2.0.1:
* Added an option to explicitly drop columns.
- changes from version 2.0.0:
* Deprecated support for Python < 3.6.
* Deprecated support for old versions of scikit-learn, pandas and
numpy. Please check setup.py for minimum requirement.
* Removed CategoricalImputer, cross_val_score and GridSearchCV. All
these functionality now exists as part of scikit-learn. Please use
SimpleImputer instead of CategoricalImputer. Also Cross validation
from sklearn now supports dataframe so we don't need to use cross
validation wrapper provided over here.
* Added NumericalTransformer for common numerical
transformations. Currently it implements log and log1p
transformation.
* Added prefix and suffix options. See examples above. These are
usually helpful when using gen_features.
* Added drop_cols argument to DataframeMapper. This can be used to
explicitly drop columns
* Mon Jan 06 2020 Todd R <toddrme2178@gmail.com>
- Drop python2 subpackage due to dependencies dropping python2.
* Sat Dec 08 2018 Arun Persaud <arun@gmx.de>
- update to version 1.8.0:
* Add FunctionTransformer class (#117).
* Fix column names derivation for dataframes with multi-index or
non-string columns (#166).
* Change behaviour of DataFrameMapper's fit_transform method to
invoke each underlying transformers' native fit_transform if
implemented. (#150)
* Sun Sep 02 2018 arun@gmx.de
- specfile:
* remove devel from noarch
* be more specific in %files section
- update to version 1.7.0:
* Fix issues with unicode names in get_names (#160).
* Update to build using numpy==1.14 and python==3.6 (#154).
* Add strategy and fill_value parameters to CategoricalImputer to
allow imputing with values other than the mode (#144), (#161).
* Preserve input data types when no transform is supplied (#138).
* Thu May 24 2018 toddrme2178@gmail.com
- spec file cleanups
* Thu Nov 09 2017 arun@gmx.de
- update to version 1.6.0:
* Add column name to exception during fit/transform (#110).
* Add gen_feature helper function to help generating the same
transformation for multiple columns (#126).
* Fri Oct 20 2017 toddrme2178@gmail.com
- initial version
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