ArviZ

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Overview

HEALTH SCORE

Excellent

86out of 100

Strong maintainer coverage and security posture. Development cadence is the only remaining gap.

LIFECYCLE

Active

Consistent commits, responsive maintainers, regular releases, and healthy issue triage.

Display your project Health score on your GitHub page.

Health breakdown

Excellent(86/100)

Maintainer availability, known risks and supply chain posture, and whether the project is actively developed or appropriately stable.

Maintainer responsiveness

Median response time is 2 days.

Bus factor

7 active maintainers currently have merge rights.

Organization Diversity

Contributors span 47 organizations.

Project Achievements

Leaderboards

About

ArviZ is a Python library for exploratory analysis of Bayesian models that provides visualization and statistical tools for working with posterior samples from probabilistic models. It supports multiple statistical backends and offers unified interfaces for diagnostics, statistics, and plotting of Bayesian inference results.

First commit

July 2015

Software value

$882K