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.

Related packages: python3-seaborn


Maintainer information

This software package is maintained for (Neuro)Debian by the follow individuals and/or groups:

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NeuroDebian Maintainers
Maintainer avatar
Yaroslav Halchenko
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Michael Hanke

In order to get support, or to get in touch with a maintainer, please click the ‘Help’ button at the top of the page.

Advanced user information

Version control system available: Browse sources

Package availability chart
Distribution Base version Our version Architectures
Debian GNU/Linux 7.0 (wheezy)   0.6.0-1~nd70+1 i386, amd64, sparc
Debian GNU/Linux 8.0 (jessie) 0.4.0-3 0.6.0-1~nd80+1 i386, amd64, sparc
Debian testing (stretch) 0.6.0-1    
Debian unstable (sid) 0.6.0-1 0.6.0-1~nd+1 i386, amd64, sparc
Ubuntu 14.04 “Trusty Tahr” (trusty)   0.6.0-1~nd14.04+1 i386, amd64, sparc
Ubuntu 14.10 “Utopic Unicorn” (utopic)   0.6.0-1~nd14.10+1 i386, amd64, sparc
Ubuntu 15.04 “Vivid Vervet” (vivid) 0.4.0-3 0.6.0-1~nd15.04+1 i386, amd64, sparc
The source code for this portal is licensed under the GPL-3 and is available on GitHub.