{"id":1910,"library":"arviz","title":"ArviZ","description":"ArviZ is a Python package for exploratory analysis of Bayesian models. It provides tools for diagnostics, visualization, and inference data management, working with various probabilistic programming frameworks. Version 1.0.0 is the current major release, and the project has a regular, active release cadence.","status":"active","version":"1.0.0","language":"en","source_language":"en","source_url":"https://github.com/arviz-devs/arviz","tags":["bayesian","statistics","data-analysis","visualization","probabilistic-programming"],"install":[{"cmd":"pip install arviz","lang":"bash","label":"Install ArviZ"}],"dependencies":[],"imports":[{"note":"Commonly imported with the alias `az` for brevity and convention.","symbol":"arviz","correct":"import arviz as az"},{"note":"The central data structure for ArviZ, usually accessed via `az` alias.","symbol":"InferenceData","correct":"import arviz as az\nidata = az.InferenceData(...)"}],"quickstart":{"code":"import arviz as az\nimport numpy as np\n\n# Simulate some data for demonstration\nnp.random.seed(42)\ndata = {\n    'theta': np.random.normal(0, 1, size=1000),\n    'phi': np.random.normal(5, 2, size=1000)\n}\n\n# Create a dummy InferenceData object (usually loaded from a model)\nid = az.InferenceData(\n    posterior=az.dict_to_dataset(data),\n    sample_stats=az.dict_to_dataset({'lp': np.random.normal(0, 1, size=1000)})\n)\n\n# Plot a trace of the posterior samples\naz.plot_trace(id, var_names=['theta'])\n\n# Print summary statistics\nprint(az.summary(id, var_names=['theta']))","lang":"python","description":"This quickstart demonstrates how to create a basic `InferenceData` object (often loaded from a model output) and use ArviZ to plot a trace and generate summary statistics. It uses `numpy` for data simulation and `arviz` for analysis and visualization."},"warnings":[{"fix":"Upgrade your Python environment to 3.12+ or use an older ArviZ version compatible with your Python (e.g., `pip install arviz<1.0`).","message":"ArviZ v1.0.0 and newer require Python 3.12 or higher. Users on older Python versions (e.g., 3.10, 3.11) must upgrade their Python environment to use ArviZ 1.x.","severity":"breaking","affected_versions":">=1.0.0"},{"fix":"Migrate any workflows relying on direct R-to-Python conversion via `from_rpy2` to alternative data transfer methods, or use an older ArviZ version if this functionality is critical.","message":"The `rpy2` dependency and the `az.from_rpy2` function were removed in ArviZ v1.0.0 due to the internal refactor into a meta-package structure.","severity":"breaking","affected_versions":">=1.0.0"},{"fix":"Review release notes for v0.13.0 and explicitly specify arguments like `combined`, `kind`, `pointwise` if you relied on previous default behaviors to ensure consistent output.","message":"Default values for several key plotting and analysis functions changed in ArviZ v0.13.0. For example, `az.plot_forest`'s `combined` argument, `az.plot_posterior`'s `kind` argument, and `az.loo`'s `pointwise` argument.","severity":"gotcha","affected_versions":">=0.13.0"}],"env_vars":null,"last_verified":"2026-04-09T00:00:00.000Z","next_check":"2026-07-08T00:00:00.000Z"}