DBSCAN and HDBSCAN spatial clustering in Python: finding Glasgow's dining districts
Cluster GPS and point-of-interest data in Python with DBSCAN and HDBSCAN: use the haversine metric on latitude and longitude or plain metres on a projected grid, choose eps with a k-distance plot, handle variable density with HDBSCAN, draw convex and concave hull polygons, treat noise properly, read silhouette and DBCV with care, and scale up with a BallTree. Uses 3,950 real Overture Maps restaurants, cafés and bars in Glasgow.