A set of scikit-learn-style transformers for encoding categorical variables into numeric with different techniques. While ordinal, one-hot, and hashing encoders have similar equivalents in the existing scikit-learn version, the transformers in this library all share a few useful properties:

First-class support for pandas dataframes as an input (and optionally as output)
Can explicitly configure which columns in the data are encoded by name or index, or infer non-numeric columns regardless of input type
Can drop any columns with very low variance based on training set optionally
Portability: train a transformer on data, pickle it, reuse it later and get the same thing out.
Full compatibility with sklearn pipelines, input an array-like dataset like any other transformer