My project focuses on the difference in accessibility to health related resources (supermarkets, hospitals, parks, community gardens) in richer and poorer neighborhoods. The problem is that poorer neighborhoods generally have less accesability to these resources because they are not commonly available or there is limited transportation to these places and my recommended solution is to improve the infrastructure- that is utilize empty lots to make more clinics, supermarkets and community gardens, and create new bus routes that allow easier access to these places. Using pandas, numpy, seaborn and SQL, I plan on creating graphs and scatter plots that demonstrate the relationship between income per zipcode, the number of health related resources per zipcode, and the number of bus stops and train stops per zipcode.
