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.
Getting Started
Examples
Reference
Cheat Sheets
Documentation
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 on the forum and in chats.
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.
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 Toolsseaborn
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.
Support Matplotlib#
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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