Search Packages

causallib

A Python package for modular causal inference analysis and model evaluations

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.

causal-learn

Causal Discovery in Python. Learning causality from data.

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.

eliot

Eliot: the logging system that tells you *why* it happened

scikit-uplift

:exclamation: uplift modeling in scikit-learn style in python :snake:

lingam

Python package for causal discovery based on LiNGAM.

cdt

Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.

gcastle

Trustworthy AI related projects

dependence-forecastability

General-purpose Python toolkit for horizon-wise forecastability analysis using interchangeable dependence scorers, with AMI/pAMI support, rolling-origin benchmarking, and reproducible reporting.

syntheticcontrolmethods

A Python package for causal inference using Synthetic Controls

pyphi

A toolbox for integrated information theory.

causalegm

A General Causal Inference Framework by Encoding Generative Modeling

pybbn

Inference in Bayesian Belief Networks using Probability Propagation in Trees of Clusters (PPTC) and Gibbs sampling

causallift

CausalLift: Python package for causality-based Uplift Modeling in real-world business

ylearn

YLearn, a pun of "learn why", is a python package for causal inference

esa-2scm

ESA-2SCM Python Package for Causal Discovery

copent

Estimating Copula Entropy (Mutual Information), Transfer Entropy (Conditional Mutual Information), and the statistics for multivariate normality test and two-sample test, and change point detection in Python

causeinfer

Machine learning based causal inference/uplift in Python

msapy

Multi-perturbation Shapley value Analysis (MSA)

scmopy

scmopy: Distribution-Agnostic Structural Causal Models Optimization in Python

avici

Amortized Inference for Causal Structure Learning, NeurIPS 2022

pytrad

Causal Discovery in Python. Learning causality from data.

rdd

Python tools for regression discontinuity designs