Reflections from my Regression course and explaining the Hat matrix and its significance in determining outliers.

Last post I left off on getting the neighborhood regions and grocery markers on the map. This month was largely spent on getting the data set up for food desert calculations. I spent a bit of time on the theoretical aspect to create the algorithm. However, in practice doing a step like projections to XY coordinates took a long time. This blog post, I’m breaking down the methodology/theory of determining a food desert region and then I will be discussing the progress in my application.

Link to Github Link to Heroku Website I first started off by finding another dataset with grocery stores in Chicago because the first one was not all of the grocery stores. Then, I used Grocery Stores - 2013, however, this has convinience stores and liquor stores counting as Grocery stores. After searching for more, I decided to settle on this dataset for now since I needed to start coding. My first goal was loading the dataset as markers.