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.
November 23, 2022Sunden hired as Research Software Engineer We are happy to announce that Kyle Sunden has joined Matplotlib as a Research Software Engineer supported by a grant from NASA.
September 16, 2022Matplotlib 3.6.0 Released
May 2, 2022Matplotlib 3.5.2 Released
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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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