DoWhy: Python Library

Much like machine learning libraries have done for prediction, “DoWhy” is a Python library that aims to spark causal thinking and analysis. DoWhy provides a unified interface for causal inference methods and automatically tests many assumptions, thus making inference accessible to non-experts.

Check out our introductory blog post on DoWhy

Code: Github. Documentation:

Other packages we find useful

Once you have done the hard work of identifying the causal estimand, you can also try out this library by Adam Kelleher that implements non-parametric estimation methods.

For causal discovery, check out DAGitty, an excellent package that lets you reason with causal graphs.