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Matplotlib — Visualization with Python

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.

Try Matplotlib (on Binder) 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.

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.

Short questions related to contributing to Matplotlib may be posted on the gitter channel.

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

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

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

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

WCSAxes is a framework for making plots of Astronomical data in Matplotlib.

WCSAxes Support Matplotlib#

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