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PyWhy’s mission is to build an open-source ecosystem for causal machine learning that moves forward the state-of-the-art and makes it available to practitioners and researchers. We build and host interoperable libraries, tools, and other resources spanning a variety of causal tasks and applications, connected through a common API on foundational causal operations and a focus on the end-to-end analysis process.

PyWhy Homepage: Learn about the PyWhy ecosystem, including libraries and tutorials.

PyWhy Governance: Learn about PyWhy's governance.

PyWhy Discord: We use Discord to communicate and meet regularly.

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  1. dowhy Public

    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 graphic…

    Python 7.4k 950

  2. EconML Public

    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 go…

    Jupyter Notebook 4k 742

  3. causal-learn Public

    Causal Discovery in Python. It also includes (conditional) independence tests and score functions.

    Python 1.3k 209

Repositories

Showing 10 of 14 repositories
  • EconML Public

    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 …

    Jupyter Notebook 4,015 742 354 (2 issues need help) 23 Updated Mar 21, 2025
  • pywhy-graphs Public

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

    Python 52 MIT 8 19 (1 issue needs help) 5 Updated Mar 21, 2025
  • dowhy Public

    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 7,362 MIT 950 133 (9 issues need help) 2 Updated Mar 19, 2025
  • causal-learn Public

    Causal Discovery in Python. It also includes (conditional) independence tests and score functions.

    Python 1,303 MIT 209 51 2 Updated Mar 18, 2025
  • pywhyllm Public

    Experimental library integrating LLM capabilities to support causal analyses

    Python 120 MIT 19 7 3 Updated Mar 18, 2025
  • dodiscover Public

    [Experimental] Global causal discovery algorithms

    Python 98 MIT 18 52 (6 issues need help) 7 Updated Mar 3, 2025
  • pywhy-stats Public

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

    Python 27 MIT 4 6 3 Updated Jan 1, 2025
  • causaltune Public

    AutoML for causal inference.

    Jupyter Notebook 220 Apache-2.0 31 21 4 Updated Dec 18, 2024
  • py-why.github.io Public

    Contains the code for https://py-why.github.io/

    HTML 8 8 1 0 Updated Sep 5, 2024
  • .github Public
    0 0 0 0 Updated Jan 2, 2024