I thought for this post I would look into the Seaborn library – Seaborn is a statistical plotting library and is built on top of Matplotlib. It has really nice looking default plotting styles and also works really well with Pandas DataFrames – so we can leverage the work we have done with Pandas in previous blog posts and hopefully create some great plots.
Seaborn can be installed just like any other Python package by using “pip”. Go to your command line and run:
pip install seaborn
The official documentation page for Seaborn can be found here and a lovely looking gallery page showing examples of what is possible with Seabon can be found here. You can click on any of the images on the gallery page and it will present you with example code on how to produce that particular plot. Another important page is the API page, which references the various available plot types – this can be found here.
I am going to try to break the Seaborn capabilities down into various categories – and begin with the plots that allow us to visualise the distribition of a data set