* Added experimental support for multithreading in hashing encoder * Support for pandas >=0.24 * Removed support for missing values represented by None due to changes in Pandas 0.24. Use numpy.NaN * Changed the default setting of Helmert encoder for handle_missing and handle_unknown * Fixed wrong calculation in m-estimate encoder * Fixed missing value handling in CatBoost encoder
2.0.0
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* Added James-Stein, CatBoost and m-estimate encoders * Added get_feature_names method * Refactored treatment of missing and new values * Speed up the encoders with vectorization * Improved compatibility with Pandas Series and Numpy Arrays
1.3.0
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* Added Weight of Evidence encoder
1.2.8
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* Critical bugfix in hashing encoder
1.2.7
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* Bugfixes related to missing value imputation * Category names optionally added to encoded column names for some encoders * Documentation updates * Stats models pinned to avoid errors * Performance enhancements
1.2.6
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* Release for zenodo DOI * Inverse transform implemented for some encoders