Here's a simple, yet powerful, way to cluster GPS locations with Python.
I recently had a challenge while crunching some data which contained GPS latitudes and longitudes.
In an effort to squeeze as much information as I could out of the data I have, I had this idea. It’s not anything new, but definitely something exciting. Heat maps and clustered maps are nice, but what if we could do more with the GPS coordinates?
Let’s dream a little, what if there were relationships in the demographics and the other data points. e.g is customer churn influenced by region? Here’s a simple, yet powerful, way to cluster GPS locations with Python.
For this I’ve used data from kaggle‘s Zillow Prize: Zillow’s Home Value Prediction (Zestimate). I used ‘properties_2016.csv’. It’s large!
For a step by step guide for this, have a look at my article on medium Clustering GPS Coordinates and Forming Regions with Python.