{"categories":[{"label":"Libraries","url":"https://skillfed.io/packages/category/software-development-libraries/8"},{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/6"}],"enrichment":{"capability":"skrub prepares and transforms dataframes for machine learning by handling common data cleaning and feature engineering tasks that scikit-learn and pandas workflows typically require.","skillfed_tags":["data-preprocessing","sklearn-integration","tabular-ml"],"use_cases":["Prepare messy tabular data with missing values and mixed data types for supervised learning.","Encode categorical features and handle string columns in a sklearn-compatible way.","Join multiple dataframes and align them for feature engineering in a machine learning pipeline.","Transform raw CSV or database exports into clean feature matrices ready for model training.","Build reproducible data preprocessing workflows that integrate with sklearn Pipelines."],"what_it_does":"skrub is a Python library that bridges the gap between raw dataframes and machine learning models by providing transformers and utilities for common data preparation tasks. It sits in the scikit-learn ecosystem and works with pandas DataFrames and numpy arrays, offering tools for feature engineering, encoding, and data cleaning that are typically needed before training models.\n\nThe library depends on numpy, pandas, scikit-learn, scipy, and visualization tools (matplotlib, pydot) for its operations. It is actively maintained, supports Python 3.10 through 3.14, and has been in production use since late 2023. The package is designed to integrate with sklearn's Pipeline API and other standard ML workflows, making it a natural fit for teams already using those tools.","worth_installing":"Yes. skrub is actively maintained, has no known vulnerabilities, low install friction, and fills a genuine gap in the sklearn ecosystem for dataframe-native preprocessing. It is well-suited for teams doing tabular machine learning with pandas and scikit-learn. Install it if you regularly work with raw dataframes and want to avoid writing custom preprocessing code."},"id":"skrub","links":{"html":"https://skillfed.io/packages/skrub","md":"https://skillfed.io/packages/skrub.md","pypi":"https://pypi.org/project/skrub/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-07-06","license_spdx":"BSD-3-Clause","license_treatment":"permissive","name":"skrub","python_support":"supports_current","summary":"Machine learning with dataframes"},"popularity":{"monthly_downloads":153337,"position":10884,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.10.0"}