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.
February 17, 2022Matplotlib is hiring!
December 11, 2021Matplotlib 3.5.1 Released
September 15, 2021Matplotlib selected for NASA ROSES funding
September 9, 2021Matplotlib awarded a CZI EOSS Cycle 4 grant
Join our community at discourse.matplotlib.org to get help, share your work, and discuss contributing & development.
Short questions may be posted on the gitter channel.
Check out the Matplotlib tag on stackoverflow.
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 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
Cartopy is a Python package designed for geospatial data processing in order to produce maps and other geospatial data analyses.Cartopy
DNA Features Viewer
DNA Features Viewer is a Python library to visualize DNA features, e.g. from GenBank or Gff files, or Biopython SeqRecords.DNA Features Viewer
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