The python script uncovers the well-known phenomenon of Banking Deserts. The concept is simple: many neighborhoods with predominantly low-income and elderly populations tend to have inadequate coverage of banking services. This leads such communities to be vulnerable to predatory loan and pricey check casher providers. In this script, I have retrieved and plotted data from the 2013 US Census and Google Places API to show the relationship between various socioeconomic parameters and bank count across 700 randomly selected zip codes.
Technologies used: Pandas, Numpy, Matplotlib, Requests, Census API, and Google API .