Visualization in Python

Python has several visualization libraries that offer various plot types and customization options. Some are focused on general plotting, while others are built for specific purposes, such as statistical data visualization. In this workshop, we'll cover both Matplotlib and Seaborn.

We'll begin with an introduction to visualization principles and theories. We'll then create several plots, mostly based on data from Gapminder, showing attendees how to use each library. Attendees will also learn how to customize plots, size figures, add plot elements, changing colors, etc.

Basic familiarity with Python is assumed. Please have installed:

1. BCE Summer 2015;
2. Anaconda; or  
3. Python 3.3+ (2.7 okay), IPython version 2.0+ (with notebook support), pandas 0.15+, Matplotlib 1.3+, Seaborn 0.6.