I'm working on a project that seeks to identify clusters in urban development based on location (in lat/lon) and a categorical variable (what the particular site is zoned for). Ideally, the analysis would identify clusters of sites that are 1) near each other and 2) zoned the same. Below is a sample of what my data looks like:
lat lon zone
33.22320 -112.6741 R-43
33.45324 -113.0888 R-43
33.71800 -112.3885 R-43
33.45626 -111.9408 AG
33.45746 -111.9313 R-6
33.45747 -111.9309 R-6
I've seen methods that define distance on just lat/lons using great circle distances, but I haven't seen any mixed clustering of the sort I'm trying to implement. I'm fairly new to cluster analysis so any guidance on implementing something like this in R or Python would be greatly appreciated!
