Recently our ability to gather large amounts of complex data has far outstripped our ability to analyze them. Although our human brains can process data in complex ways but it does not scale when it comes to large volumes of data. Clustering is one way to distill data to some groups and understand relationships within the dataset. Clustering is used in many scientific research fields such as natural science, genetics, politics and of course in sales and marketing. I recently published a blog on analysis performed using euclid distance and clustering at my work SEI for cybersecurity- link here. Here I am going to simply explore the mechanics of using Euclid distance for clustering using some simple Python code and examples. Don't worry, it is simple Math hopefully once you walk through this sample.
