PyWhy (@py-why)
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py-why

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1

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.
Python
6,954
star
2

EconML

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
Jupyter Notebook
3,699
star
3

causal-learn

Causal Discovery in Python. It also includes (conditional) independence tests and score functions.
Python
1,100
star
4

causaltune

AutoML for causal inference.
Jupyter Notebook
191
star
5

dodiscover

[Experimental] Global causal discovery algorithms
Python
76
star
6

pywhy-graphs

[Experimental] Causal graphs that are networkx-compliant for the py-why ecosystem.
Python
45
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7

pywhy-stats

Python package for (conditional) independence testing and statistical functions related to causality.
Python
20
star
8

py-why.github.io

Contains the code for https://py-why.github.io/
HTML
8
star
9

pywhy-notes

Keep track of discussions and meeting minutes.
5
star
10

graphs

[Not used] Now, an open PR for mixed-edge graph support is open in networkx
Python
2
star
11

governance

This repository describes the governance model for the PyWhy org
1
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12

dowhy-example-notebooks-deps-dockerfile

Dockerfile
1
star