ArviZ (pronounced "AR-vees") is a Python package for exploratory analysis of Bayesian models. 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.



ArviZ is available for installation from PyPI.

The latest stable version can be installed using pip:

pip install arviz

ArviZ is also available through conda-forge.

conda install -c conda-forge arviz


The latest development version can be installed from the main branch using pip:

pip install git+git://

Another option is to clone the repository and install using git and setuptools:

git clone
cd arviz
python install

Ridge plot

Parallel plot

Trace plot

Density plot

Posterior plot

Joint plot

Posterior predictive plot

Pair plot

Energy Plot

Violin Plot

Forest Plot

Autocorrelation Plot


ArviZ is tested on Python 3.6, 3.7 and 3.8, and depends on NumPy, SciPy, xarray, and Matplotlib.


If you use ArviZ and want to cite it please use DOI

Here is the citation in BibTeX format

  doi = {10.21105/joss.01143},
  url = {},
  year = {2019},
  publisher = {The Open Journal},
  volume = {4},
  number = {33},
  pages = {1143},
  author = {Ravin Kumar and Colin Carroll and Ari Hartikainen and Osvaldo Martin},
  title = {ArviZ a unified library for exploratory analysis of Bayesian models in Python},
  journal = {Journal of Open Source Software}