In analyzing national law enforcement data, I sought to better understand geographic trends in police shootings across US states over the past decade. My analysis aims to inform positive community-policing policy changes. Rather than rely on static statistics alone, I decided to leverage geospatial modelling to visualize and dynamically explore shooting locations Using a dataset spanning recent years with over 5,000 incidents geocoded to the county level, I plotted past shootings on a national map. Adding a heat map layer helped spotlight states seeing disproportionate cases historically. I also ran a spatial cluster detection algorithm to identify hot spots ranked by significance.
Visual inspection and computational pattern recognition converged to illuminate three states repeatedly ranked as top high-risk areas for fatal police shootings. Seeing these spatial relationships come alive interactively enabled more rigorous location-based insights than using traditional metrics.