Python tools for data visualization

Welcome to PyViz! The PyViz.org website is an open platform for helping users decide on the best open-source (OSS) Python data visualization tools for their purposes, with links, overviews, comparisons, and examples. Contents:

• Overviews of the OSS visualization packages available in Python, how they relate to each other, and the core concepts that underlie them.

• High-level tools for getting started with Python viz, creating powerful plots in just a few lines of code.

• All tools available for doing viz in Python OSS, as a live table for comparing maturity, popularity, and support.

• Dashboarding tools for sharing live Python-backed visualizations.

• SciVis tools for rendering data embedded in three-dimensional space.

• Tutorials showing how to use the available tools to accomplish various categories of tasks.

• Topic examples of using Python viz tools to analyze or describe specific datasets in a particular domain or field of research.

This site

If you are a part of the Python data visualization landscape, then this is your site! All content has been contributed by individual library authors and users, and you could be next! Please open an issue or PR on this GitHub repo to start a conversation. The goal is to make everyone doing viz in Python more productive, have more power, and make a greater impact from their work.

NOTE: The contents of PyViz.org from June 2019 or earlier, focusing on Datashader, HoloViews, GeoViews, Panel, Param, and hvPlot, are now at HoloViz.org. PyViz.org is now a fully open guide to all Python visualization tools. If you are looking for Brian Thomas’s PyViz smart-home visualization tool, check out his paper.