Exploratory analysis of Bayesian models with Python
ArviZ (pronounced "AR-vees") is a Python package for exploratory analysis of Bayesian models. It includes functions for posterior analysis, data storage, model checking, comparison and diagnostics.
ArviZ in other languages
ArviZ also has a Julia wrapper available ArviZ.jl.
Documentation
The ArviZ documentation can be found in the official docs. Here are some quick links for common scenarios:
- First time Bayesian modelers and ArviZ users: EABM book
- First time ArviZ users, already familiar with Bayesian modeling: overview notebook or example gallery
- ArviZ 0.x user: migration guide
- ArviZ-verse documentation:
Installation
Stable
ArviZ is available for installation from PyPI. The latest stable version can be installed using pip:
pip install "arviz[preview]"
ArviZ is also available through conda-forge.
conda install -c conda-forge arviz arviz-plots
Development
The latest development version can be installed from the main branch using pip:
pip install git+https://github.com/arviz-devs/arviz.git
Another option is to clone the repository and install using git and setuptools:
git clone https://github.com/arviz-devs/arviz.git
cd arviz
python setup.py install
Gallery
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Citation
If you use ArviZ and want to cite it please use 
Here is the citation in BibTeX format
@article{Martin2026,
doi = {10.21105/joss.09889},
url = {https://doi.org/10.21105/joss.09889},
year = {2026},
publisher = {The Open Journal},
volume = {11},
number = {119},
pages = {9889},
author = {Martin, Osvaldo A. and Abril-Pla, Oriol and Deklerk, Jordan and Axen, Seth D. and Carroll, Colin and Hartikainen, Ari and Vehtari, Aki},
title = {ArviZ: a modular and flexible library for exploratory analysis of Bayesian models},
journal = {Journal of Open Source Software}}
Contributions
ArviZ is a community project and welcomes contributions. Additional information can be found in the contributing guide
Code of Conduct
ArviZ wishes to maintain a positive community. Additional details can be found in the Code of Conduct
Donations
ArviZ is a non-profit project under NumFOCUS umbrella. If you want to support ArviZ financially, you can donate here.
Sponsors and Institutional Partners
The ArviZ project website has more information about each sponsor and institutional partner and the support they provide.
Institutional partners
ArviZ is currently supported by the following institutional partners:
Sponsors
ArviZ currently has no Sponsors.