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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!

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License

sklearndf is licensed under Apache 2.0 as described in the LICENSE file.

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