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.
May 2, 2022Matplotlib 3.5.2 Released
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
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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
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.plotnine
WCSAxes is a framework for making plots of Astronomical data in Matplotlib.WCSAxes
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Matplotlib is the result of development efforts by John Hunter (1968–2012) and the project's many contributors.
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