File python-sklearn-pandas.changes of Package python-sklearn-pandas

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File python-sklearn-pandas.changes of Package python-sklearn-pandas (Revision 3b9b8ae41e5e1017fa144797807569b5)

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Sat Feb 12 23:37:31 UTC 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

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Thu Jan 28 19:44:35 UTC 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

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Sat Oct 10 19:08:06 UTC 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

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Mon Jan  6 15:11:42 UTC 2020 - Todd R <toddrme2178@gmail.com>

- Drop python2 subpackage due to dependencies dropping python2.

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Sat Dec  8 19:39:33 UTC 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)

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Sun Sep  2 16:30:43 UTC 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).

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Thu May 24 17:45:17 UTC 2018 - toddrme2178@gmail.com

- spec file cleanups

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Thu Nov  9 06:00:35 UTC 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).

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Fri Oct 20 16:18:41 UTC 2017 - toddrme2178@gmail.com

- initial version

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File python-sklearn-pandas.changes of Package python-sklearn-pandas (Revision 3b9b8ae41e5e1017fa144797807569b5)

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