alteryx/featuretools
An open source python library for automated feature engineering
This tool helps data professionals prepare their datasets for machine learning by automatically creating meaningful features from raw, structured data. You feed it multiple related tables, like customer details, transactions, and sessions, and it outputs a single, wide table of new features that can directly be used to train predictive models. It's designed for data scientists, analysts, and machine learning engineers who need to quickly generate rich features without extensive manual coding.
7,622 stars. Used by 3 other packages. Available on PyPI.
Use this if you have relational data spread across multiple tables (e.g., customer details, transactions, product logs) and need to create a consolidated feature set for machine learning efficiently.
Not ideal if your primary goal is to perform basic data cleaning, transformation, or analysis on a single, flat dataset without the need for advanced feature generation across relationships.
Stars
7,622
Forks
907
Language
Python
License
BSD-3-Clause
Category
Last pushed
Feb 03, 2026
Commits (30d)
0
Dependencies
9
Reverse dependents
3
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/alteryx/featuretools"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related frameworks
feature-engine/feature_engine
Feature engineering and selection open-source Python library compatible with sklearn.
cod3licious/autofeat
Linear Prediction Model with Automated Feature Engineering and Selection Capabilities
abess-team/abess
Fast Best-Subset Selection Library
rodrigo-arenas/Sklearn-genetic-opt
ML hyperparameters tuning and features selection, using evolutionary algorithms.
abhayspawar/featexp
Feature exploration for supervised learning