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.
We thank the 246 authors for the 936 pull requests that comprise the 3.11.0 release.
We thank the 128 authors for the 337 pull requests that comprise the 3.10.0 release.
A warm welcome to Trygve Magnus Ræder, who is working on bivariate colormapping.
We thank the 175 authors for the 450 pull requests that comprise the 3.9.0 release.
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.
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.
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).
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.
Cartopy is a Python package designed for geospatial data processing in order to produce maps and other geospatial data analyses.
DNA Features Viewer is a Python library to visualize DNA features, e.g. from GenBank or Gff files, or Biopython SeqRecords.
plotnine is an implementation of a grammar of graphics in Python. The grammar allows users to compose plots by explicitly mapping data to the visual objects that make up the plot.
WCSAxes is a framework for making plots of Astronomical data in Matplotlib.
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!
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!
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.
© 2012 – 2026 The Matplotlib development team