Data visualizations created for the University College London's course Quantitative Methods 2: Data Science and Visualization in the Depratment of Arts and Sciences.
Using Python partially directed through weekly module workshops and partially self-studied to create more dynamic visualizations, our group's aim was to address London's public transportation system - in particular, we sought to evalute it's accessibility throughout the city and determine how demographic factors such as income, population density, and ethnicity would play a role in how transportation was used and developed throughout London boroughs.
Created with Jupyter iPython Notebooks.