scikit-learn-contrib/sklearn-pandas

Health v2 · maintenance only

Flags: no_license

Adoption not part of the score

2842 stars · 421 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A Python library that bridges pandas DataFrames and scikit-learn by mapping DataFrame columns to sklearn transformations. Its DataFrameMapper lets you declare per-column transformers that are applied and recombined into feature matrices.

Use cases

• apply sklearn transformers to pandas dataframe columns
• build preprocessing pipelines for mixed numeric and categorical data
• map dataframe columns to feature transformations
• integrate pandas with scikit-learn workflows
• preprocess tabular data before model training
• handle categorical encoding in sklearn pipelines

When to choose

• you work with pandas DataFrames and want declarative column-wise sklearn transformations
• you need a mapper that predates or complements sklearn's ColumnTransformer with extra conveniences like feature naming

When to avoid

• you only use modern scikit-learn, where sklearn.compose.ColumnTransformer covers most needs natively
• your data is not in pandas DataFrames

Facets

library · maturity maintenance

machine-learning etl serialization machine-learning data-science python scikit-learn pandas dataframe feature-engineering data-preprocessing column-transformer data-engineering

Member repositories

For agents

markdown · JSON · MCP: product_card(name="scikit-learn-contrib/sklearn-pandas")