D
dowhy
py-why/dowhy
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
★8.2kstars
Python
MIT
Updated: 1d ago
📋 Project at a Glance
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What's this?A , built with Python open-source project in the Data & Infrastructure category, core strengths: bayesian-networks/causal-inference
Who made it?Maintained by py-why team, 8.2K⭐ on GitHub, #241 out of 3133 in Data & Infrastructure
Why does it exist?With the growing demand for bayesian-networks and causal-inference in Data & Infrastructure, py-why created dowhy as a streamlined solution.
What can it do?Key use cases: causal-machine-learning, causal-models, causality
How to install with AI?Use an AI coding assistant (Claude Code, Cursor, Copilot) to automatically set up pip dependencies and virtual env. Follow the README — the AI handles the rest.
🔗 github.com/py-why/dowhy | 官网 https://www.pywhy.org/dowhy
🔗 github.com/py-why/dowhy | 官网 https://www.pywhy.org/dowhy
Topics
bayesian-networkscausal-inferencecausal-machine-learningcausal-modelscausalitydata-sciencedo-calculusgraphical-modelsmachine-learningpython3treatment-effects