1.4.0 Release Organization

[wdm0006]

Hey all, been away from the project for a bit, but I'm going back through all of the issues and PRs worked on recently (looks like a bunch of good progress!). Special thanks to @janmotl for all of the work as primary maintainer over the past months.

Our last release was 1.3.0 on October 14th. Since then ya'll have:

• Sped up the TargetEncoder and LeaveOneOutEncoder w/ vectorization (significantly)
• Added support for Categorical types in many encoders
• Implemented get_feature_names in remaining transformers
• Improved testing coverage and quality
• Solved edge cases in repeated column names for some transformers
• Added support for transforming pandas Series as well as DataFrames and numpy Arrays
• Fixed inverse transform for many encoders
• Lots of smaller performance enhancements and code cleanups

Which I think is a quite full set of features to constitute a release. I will be opening a separate issue to discuss how we as a community can improve our release cycle, but for now will be going through open issues and tagging anything that should be included before the v1.4.0 release. Any input on what should or shouldn't be completed prior to release is welcome.

Thank you all for the work and support this year, and Happy Holidays.

[wdm0006]

So currently I have 3 bugs and one WIP PR that may be good to get resolved before a v1.4.0 release, but need to dig into them a bit further.

Bugs:

• Intercept column does not work properly with truncated indexes #152
• OrdinalEncoder imputes missing values with 0 instead of -1 #144
• All encoders should be recyclable #122

WIP PR:

• Ordinal encoder support new handle unknown handle missing #153

[janmotl]

It has to be noted that v1.4.0 also introduces braking changes: arguments impute_missing and handle_unknown are now called handle_missing and handle_unknown. And their possible values have changed.

[wdm0006]

Hm good point, probably should be a major release then.

[amueller]

have you run check_estimator on these or is that not possible right now?

[janmotl]

It would be nice to pass 'check_estimator'.

[gammadistribution]

Hey @janmotl, do you happen to know when the new version would be released?

If there are remaining tasks, I can help to close them if desired.

[janmotl]

@JohnnyC08 , don't you know how to deal with "errors" like:

======================================================================
ERROR: test_inverse_transform_BothFieldsAreReturnNanWithNan_ExpectValueError (category_encoders.tests.test_basen.TestBaseNEncoder)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/travis/build/scikit-learn-contrib/categorical-encoding/category_encoders/tests/test_basen.py", line 116, in test_inverse_transform_BothFieldsAreReturnNanWithNan_ExpectValueError
    enc.inverse_transform(result)
  File "/home/travis/build/scikit-learn-contrib/categorical-encoding/category_encoders/basen.py", line 287, in inverse_transform
    "the unknown category nan when encode %s" % (col,))
UserWarning: inverse_transform is not supported because transform impute the unknown category nan when encode city

as reported at: https://travis-ci.org/scikit-learn-contrib/categorical-encoding/jobs/491609594 ?

[JohnnyC08]

@janmotl I will pull the latest master and see if I can reproduce locally

[janmotl]

Beside the failing Travis CI (I didn't manage to reproduce the error with nosetest on my local computer), the code should be ready for release 2.0.0.

[wdm0006]

@janmotl sorry for the delay, I'll take a look at a 2.0.0 release here shortly.

[wdm0006]

@janmotl actually, to avoid delays like this in the future, it'd probably make sense to add you as a collaborator on PyPI.org right? If you send me your PyPI username I can add you to the project there.

[janmotl]

Good. My PyPI username: janmotl