Seaborn is a library of high-level functions that facilitate making informative and attractive plots of statistical data using matplotlib. It also provides concise control over the aesthetics of the plots, improving on matplotlib's default look.
Online documentation is available here.
There are a few tutorial notebooks that offer some thoughts on visualizing statistical data in a general sense and show how to do it using the tools that are provided in seaborn. They also serve as the primary test suite for the package. The notebooks are meant to be fairly, but not completely comprehensive; hopefully the docstrings for the specific functions will answer any additional questions.
- Python 2.7 or 3.3
To install the released version, just do
pip install seaborn
You may instead want to use the development version from Github, by running
pip install git+git://github.com/mwaskom/seaborn.git#egg=seaborn
To test seaborn, run
make test in the source directory. This will run the
unit-test suite (using
nose). It will also execute the example notebooks and
compare the outputs of each cell to the data in the stored versions.
Please submit any bugs you encounter to the Github issue tracker.
Released under a BSD (3-clause) license
"Those are nice plots" -Hadley Wickham