Feature Engine provides Python tools for feature engineering and selection that are compatible with scikit-learn.
Open source
24 alternativesFeaturetools
The Featuretools Python library supports automated feature engineering and is published as open source.
About Featuretools
Featuretools is an open source Python library for automated feature engineering. It uses Deep Feature Synthesis (DFS) to build a single feature table from multi-table datasets, such as timestamped customer transactions, for a selected target dataframe.
Key features
- Applies Deep Feature Synthesis to multi-table datasets
- Creates single feature table for target dataframe
- Provides built-in primitives for feature creation
- Allows definition of custom primitives
- Offers NLP primitives as separate installable add-on
- Uses Dask to run DFS with njobs greater than 1
Best for: Python users preparing multi-table or transactional data for machine learning.
Good for
- Open source Python library
- Installable via pip or Conda-forge
- Extensible with custom primitives and optional add-ons
Featuretools at a glance
- Category
- AI & Machine Learning › AI Data & Analytics
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
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Featuretools FAQ
How do I install Featuretools?
Install with python -m pip install featuretools or with conda install -c conda-forge featuretools.
How do I install add-ons?
Install all add-ons with python -m pip install "featuretools[complete]", or install individually with "featuretools[premium]", "featuretools[nlp]", or "featuretools[dask]".
Can I define my own features?
Yes, Featuretools includes built-in primitives and also allows you to define custom primitives.
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