How to Install and Uninstall python-seaborn Package on Ubuntu 16.04 LTS (Xenial Xerus)

Last updated: December 25,2024

1. Install "python-seaborn" package

In this section, we are going to explain the necessary steps to install python-seaborn on Ubuntu 16.04 LTS (Xenial Xerus)


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                python-seaborn
            
                    
    
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2. Uninstall "python-seaborn" package

This is a short guide on how to uninstall python-seaborn on Ubuntu 16.04 LTS (Xenial Xerus):


    
        
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                sudo apt remove
            
                        
                python-seaborn
            
                    
    
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                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the python-seaborn package on Ubuntu 16.04 LTS (Xenial Xerus)

Package: python-seaborn
Priority: optional
Section: universe/python
Installed-Size: 719
Maintainer: Ubuntu Developers
Original-Maintainer: NeuroDebian Team
Architecture: all
Source: seaborn
Version: 0.6.0-1
Depends: python:any (<< 2.8), python:any (>= 2.7.5-5~), python-numpy, python-scipy, python-pandas, python-matplotlib
Recommends: python-statsmodels, python-patsy
Filename: pool/universe/s/seaborn/python-seaborn_0.6.0-1_all.deb
Size: 117996
MD5sum: b27a9f3a4b372e7a7f4e14ab14670da9
SHA1: 300146fffc2042fa457997a8bded85fd9cd1fb30
SHA256: 890b5d26f612a61976834963af309e3fc9672d3a0858a2a27b0c4b4ff797db5a
Description-en: 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.
Description-md5: 40d203cf2b427abe6a96b7717c90e133
Homepage: https://github.com/mwaskom/seaborn
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Origin: Ubuntu