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Top 14 Python causal-inference Projects
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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.
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WorkOS
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pgmpy
Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.
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causalnex
A Python library that helps data scientists to infer causation rather than observing correlation.
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causal-learn
Causal Discovery in Python. It also includes (conditional) independence tests and score functions.
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tfcausalimpact
Python Causal Impact Implementation Based on Google's R Package. Built using TensorFlow Probability.
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InfluxDB
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auton-survival
Auton Survival - an open source package for Regression, Counterfactual Estimation, Evaluation and Phenotyping with Censored Time-to-Events
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trimmed_match
This Python library implements Trimmed Match for analyzing randomized paired geo experiments and also implements Trimmed Match Design for designing randomized paired geo experiments.
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genome_integration
MR-link and genome integration. genome_integration is a repository for the analysis of genomic data. Specifically, the repository implements the causal inference method MR-link, as well as other Mendelian randomization methods.
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cdci-causality
Python implementation of CDCI, a method to identify causal direction between two variables
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SaaSHub
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I'm a fan of the Do Why library out of Microsoft. Even as a novice in the field of causal modeling it can get you up and running by estimating the causal graph based on your data. https://github.com/py-why/dowhy
Project mention: CausalPy: A Python package for causal inference in quasi-experimental settings | news.ycombinator.com | 2023-11-07
i found this library https://github.com/WillianFuks/tfcausalimpact which seems to be a python port of the R library
The worked example 'Prison construction and Black male incarceration' from the last chapter of 'Causal Inference: The Mixtape' by Scott Cunningham, (notebook here).
Python causal-inference related posts
- CausalPy: A Python package for causal inference in quasi-experimental settings
- Python package for the synthetic control method
- Python package for the synthetic control method
- [S] Python package for the synthetic control method
- Acceptable data formats for Predictive Stepwise Logistic Regression
- uber/causalml: Uplift modeling and causal inference with machine learning algorithms
- Do you use any specific framework when it comes to causal inference?
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Index
What are some of the best open-source causal-inference projects in Python? This list will help you:
Project | Stars | |
---|---|---|
1 | dowhy | 6,722 |
2 | causalml | 4,747 |
3 | pgmpy | 2,617 |
4 | causalnex | 2,140 |
5 | causal-learn | 978 |
6 | CausalPy | 767 |
7 | tfcausalimpact | 573 |
8 | causallift | 333 |
9 | auton-survival | 292 |
10 | dodiscover | 57 |
11 | trimmed_match | 55 |
12 | pysyncon | 29 |
13 | genome_integration | 11 |
14 | cdci-causality | 3 |
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