Skip to content
Branch: master
Go to file
Code

Latest commit

Files

Permalink
Failed to load latest commit information.
Type
Name
Latest commit message
Commit time
 
 
ci
 
 
doc
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

README.md

seaborn: statistical data visualization


PyPI Version License DOI Build Status Code Coverage

Seaborn is a Python visualization library based on matplotlib. It provides a high-level interface for drawing attractive statistical graphics.

Documentation

Online documentation is available at seaborn.pydata.org.

The docs include a tutorial, example gallery, API reference, and other useful information.

Dependencies

Seaborn supports Python 3.6+ and no longer supports Python 2.

Installation requires numpy, scipy, pandas, and matplotlib. Some functions will optionally use statsmodels if it is installed.

Installation

The latest stable release (and older versions) can be installed from PyPI:

pip install seaborn

You may instead want to use the development version from Github:

pip install git+https://github.com/mwaskom/seaborn.git#egg=seaborn

Testing

To test the code, run make test in the source directory. This will exercise both the unit tests and docstring examples (using pytest).

The doctests require a network connection (unless all example datasets are cached), but the unit tests can be run offline with make unittests. Run make coverage to generate a test coverage report and make lint to check code style consistency.

Development

Seaborn development takes place on Github: https://github.com/mwaskom/seaborn

Please submit bugs that you encounter to the issue tracker with a reproducible example demonstrating the problem. Questions about usage are more at home on StackOverflow, where there is a seaborn tag.

You can’t perform that action at this time.