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Paket: python-seaborn (0.8.0-1)

statistical visualization library for Python

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.

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  • dep: python
    interactive high-level object-oriented language (default version)
  • dep: python-matplotlib
    Python based plotting system in a style similar to Matlab
  • dep: python-numpy
    Numerical Python adds a fast array facility to the Python language
  • dep: python-pandas
    data structures for "relational" or "labeled" data
  • dep: python-scipy
    scientific tools for Python
  • rec: python-bs4
    error-tolerant HTML parser for Python
  • rec: python-patsy
    statistical models in Python using symbolic formulas
  • rec: python-statsmodels
    Python module for the estimation of statistical models

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