This Story Map project investigates the spatial relationship between race and cannabis possession arrests in New York City from 2020 to 2023, testing the hypothesis that arrests are spatially correlated with the ethnic composition of neighborhoods across Brooklyn, Queens, and Manhattan. As the sole analyst, I designed a comprehensive geoprocessing workflow using ArcGIS, including clipping, spatial joins, projection, tessellation, and Getis-Ord Gi hotspot analysis, to quantify patterns and transform raw arrest data into an interactive web map that visualizes statistically significant clusters alongside census tract ethnicity data. The final deliverable demonstrates my ability to work across the full lifecycle of a spatial data project, from data acquisition and geoprocessing to the creation of a narrative-driven Story Map that makes complex spatial patterns accessible to diverse audiences. The analysis revealed that hotspots with 99% confidence, including Harlem, Bedford-Stuyvesant, and Jamaica, align predominantly with Black-majority neighborhoods, while cold spots correspond to predominantly White or Asian areas, illustrating how spatial analysis can reveal patterns that merit deeper examination within broader discussions of equity and policing.