Crime Hotspots

Quick overview of crime data. The dashboard highlights a high-level overview of crime by representing blocks and map data. For more information click here.

Explore the intriguing dynamics of crime in Chicago through our Python-based analysis, where advanced machine learning techniques like K-means clustering unveil geographical hotspots of criminal activities, offering a compelling and visually rich understanding of urban crime patterns. This code is a must-see for anyone interested in data-driven insights into public safety and law enforcement strategy.

R markdown highlights a quick exploratory analysis for reporting purposes. This was used as a quick analysis to mimic quick pulls that are sometimes assigned. The markdown provides a quick insight for typical criminal geo-locational questions.