DoWhy documentation

Date: Sep 05, 2023 Version: v0.10.1

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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 wide variety of algorithms for effect estimation, causal structure learning, diagnosis of causal structures, root cause analysis, interventions and counterfactuals.

Getting started

New to DoWhy? Our Getting started guide will get you up to speed in minutes. It’ll help you install DoWhy and write your first lines of code. Once completed, you’ll be ready to the run examples and follow along in the User Guide.

User Guide

Complete newbie when it comes to causal inference and DoWhy? Then you probably want to read our comprehensive User Guide. It guides you through everything you need to know, including the concepts and science you need to know when trying to solve non-trivial problems.


If you prefer to learn by example, we recommend to browse the examples. It covers a wide variety of problems that you can use to liken to your own problem.

API Reference

The API reference contains a detailed description of the functions, modules, and objects included in DoWhy. It assumes that you have an understanding of the key concepts.