python-seaborn – statistical visualization library

Seaborn is a library for making attractive and informative statistical graphics in Python. It is built on top of matplotlib and tightly integrated with the PyData stack, including support for numpy and pandas data structures and statistical routines from scipy and statsmodels.

Some of the features that seaborn offers are

  • Several built-in themes that improve on the default matplotlib aesthetics
  • Tools for choosing color palettes to make beautiful plots that reveal patterns in your data
  • Functions for visualizing univariate and bivariate distributions or for comparing them between subsets of data
  • Tools that fit and visualize linear regression models for different kinds of independent and dependent variables
  • A function to plot statistical timeseries data with flexible estimation and representation of uncertainty around the estimate
  • High-level abstractions for structuring grids of plots that let you easily build complex visualizations

This is the Python 2 version of the package.

Package availability chart
Distribution Base version Our version Architectures
Debian GNU/Linux 10.0 (buster) 0.9.0-1    
Debian GNU/Linux 11.0 (bullseye) 0.11.1-1    
Debian GNU/Linux 9.0 (stretch) 0.7.1-4 0.7.1-2~nd90+1 i386, amd64, sparc, armel
Debian testing (bookworm) 0.11.2-3    
Debian unstable (sid) 0.12.0-1 0.7.1-2~nd+1 i386, amd64, sparc, armel
Ubuntu 16.04 “Xenial Xerus” (xenial) 0.6.0-1 0.7.1-2~nd16.04+1 i386, amd64, sparc
Ubuntu 18.04 “Bionic Beaver” (bionic) 0.8.0-1    
Ubuntu 20.04 “Focal Fossa” (focal) 0.10.0-1    
Ubuntu 21.10 “Impish Indri” (impish) 0.11.1-1    
Ubuntu 22.04 “Jammy Jellyfish” (jammy) 0.11.2-3    


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