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Third party packages

Several external packages that extend or build on Matplotlib functionality exist. Below we list a number of these. Note that they are each maintained and distributed separately from Matplotlib, and will need to be installed individually.

Please submit an issue or pull request on Github if you have created a package that you would like to have included. We are also happy to host third party packages within the Matplotlib Github Organization.

High-Level Plotting

Several projects provide higher-level interfaces for creating matplotlib plots.


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.



ggplot is a port of the R ggplot2 package to python based on matplotlib.



holoviews makes it easier to visualize data interactively, especially in a Jupyter notebook, by providing a set of declarative plotting objects that store your data and associated metadata. Your data is then immediately visualizable alongside or overlaid with other data, either statically or with automatically provided widgets for parameter exploration.


Mapping Toolkits

Two independent mapping toolkits are available.


Plots data on map projections, with continental and political boundaries. See basemap docs.



Cartopy builds on top of matplotlib to provide object oriented map projection definitions and close integration with Shapely for powerful yet easy-to-use vector data processing tools. An example plot from the Cartopy gallery:


Miscellaneous Toolkits


mpl-probscale is a small extension that allows matplotlib users to specify probabilty scales. Simply importing the probscale module registers the scale with matplotlib, making it accessible via e.g., ax.set_xscale('prob') or plt.yscale('prob').


iTerm2 terminal backend

matplotlib_iterm2 is an external matplotlib backend using iTerm2 nightly build inline image display feature.



MplDataCursor is a toolkit written by Joe Kington to provide interactive “data cursors” (clickable annotation boxes) for matplotlib.


mplcursors provides interactive data cursors for matplotlib.


mpl_toolkits.natgrid is an interface to natgrid C library for gridding irregularly spaced data. This requires a separate installation of the natgrid toolkit.


Matplotlib-Venn provides a set of functions for plotting 2- and 3-set area-weighted (or unweighted) Venn diagrams.


mplstereonet provides stereonets for plotting and analyzing orientation data in Matplotlib.


pyUpSet is a static Python implementation of the UpSet suite by Lex et al. to explore complex intersections of sets and data frames.


Windrose is a Python Matplotlib, Numpy library to manage wind data, draw windrose (also known as a polar rose plot), draw probability density function and fit Weibull distribution