We used the Python pandas library to read a .csv file containing active addresses in New York City, then used selenium to input (webScrape) those addresses into a query tool made by New York HRSA to obtain information on health infrastructure needed in the area. We plotted points on a map corresponding to the level of needed health infrastructure using folium, green being the best (primary, dental, mental, and MUA/P infrastructure are unneeded) red being the worst (every form infrastructure needed) and there was yellow orange and pink in between respectively.

New York City yielded a very homogenous data set of mostly green points indicating that health infrastructure is not needed there. However, this program could be easily expanded cross country with access to a few more .csv files to visualize where infrastructure is needed and what kind is needed where. This could be useful for the federal government in planning infrastructure development or for the aspiring owner of a much needed medical practice.