DataFrame support and feature traceability for scikit-learn.
Project description
sklearndf is an open source library designed to address a common need with scikit-learn: the outputs of transformers are numpy arrays, even when the input is a data frame. However, to inspect a model it is essential to keep track of the feature names.
To this end, sklearndf enhances scikit-learn’s estimators as follows:
- Preserve data frame structure:
Return data frames as results of transformations, preserving feature names as the column index.
- Feature name tracing:
Add additional estimator properties to enable tracing a feature name back to its original input feature; this is especially useful for transformers that create new features (e.g., one-hot encode), and for pipelines that include such transformers.
- Easy use:
Simply append DF at the end of your usual scikit-learn class names to get enhanced data frame support!
License
sklearndf is licensed under Apache 2.0 as described in the LICENSE file.
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