Matplotlib: Visualization with Python

Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. Matplotlib makes easy things easy and hard things possible.

• Create publication quality plots.
• Make interactive figures that can zoom, pan, update.
• Customize visual style and layout.
• Export to many file formats.
• Embed in JupyterLab and Graphical User Interfaces.
• Use a rich array of third-party packages built on Matplotlib.

Try Matplotlib (on Binder)

• Getting Started
• Examples
• Reference
• Cheat Sheets
• Documentation

News

May 30, 2024

GSOC 2024: Bivariate Colormaps

A warm welcome to Trygve Magnus Ræder, who is working on bivariate colormapping.

May 16, 2024

Matplotlib 3.9.0 Released

We thank the 175 authors for the 450 pull requests that comprise the 3.9.0 release.

Older Announcements

Resources

Be sure to check the Users guide and the API docs. The full text search is a good way to discover the docs including the many examples.

Join our community at discourse.matplotlib.org to get help, share your work, and discuss contributing & development.

Check out the Matplotlib tag on StackOverflow.

Meet us at our monthly call for new contributors to the Matplotlib project. Subscribe to our community calendar at Scientific Python to get access to all our community meetings.

Short questions related to contributing to Matplotlib may be posted on the gitter channel.

Domain Specific Tools

A large number of third party packages extend and build on Matplotlib functionality, including several higher-level plotting interfaces (seaborn, HoloViews, ggplot, ...), and a projection and mapping toolkit (Cartopy).

More Domain-Specific Tools

seaborn Cartopy DNA Features Viewer plotnine WCS Axes

seaborn

seaborn is a high level interface for drawing statistical graphics with Matplotlib. It aims to make visualization a central part of exploring and understanding complex datasets.

statistical data visualization

Support Matplotlib

• Contribute

  Matplotlib is a community project maintained for and by its users

  You can help by answering questions on discourse, reporting a bug or requesting a feature on GitHub, or improving the documentation and code!

  Join us on Discourse Join us on GitHub

• Cite

  Matplotlib is the result of development efforts by John Hunter (1968–2012) and the project's many contributors.

  If Matplotlib contributes to a project that leads to a scientific publication, please acknowledge this work by citing the project!

  Ready made citation

• Donate

  If you would like to support Matplotlib financially you can donate by sponsoring Matplotlib on GitHub or making a (USA) tax-deductible donation through NumFOCUS.

  Sponsor on GitHub Donate to Matplotlib