For this project, I started with an anecdotal observation that Chinese restaurants seem to be everywhere, at least one in even the smallest towns.
I used Python to parse through Foursquare’s open source points of interest via the Huggingface transformers library. From 11GB of data, I isolated over 50,000 Chinese restaurants across Canada and the US. So far, my analysis covers the US and I’ll be adding Canada soon.
In ArcGIS I mapped populations by race and ethnicity for every census tract. I found a statistically significant spatial autocorrelation (p < 0.001) which shows that Chinese people tend to cluster in the most urban areas, cities and large suburbs.
Despite this, I found that unless you’re in some of the most far-flung places in the US, there’s a Chinese restaurant nearby for you, probably no longer than a five minute drive. It turns out that Chinese restaurants are more correlated with the presence of White populations than Chinese populations.
I determined this by calculating an urban/rural classifications for every census tract, then calculating the distance to the nearest Chinese restaurant from the centroid of each tract.
The full data story currently lives in an ArcGIS Storymap. I’ll be porting it over soon! In the meantime, please view it here. Thanks for your patience.