In my analysis of a crime dataset, I initially identified the top three streets with the highest number of shootings, including “WASHINGTON ST,” “BOYLSTON ST,” and “BLUE HILL AVE,” along with the most prevalent offenses in these areas. I then determined the most common time for shootings, finding that incidents were most frequent in June, on Saturdays, and at midnight. Further investigation into UCR categories revealed that “Part Three” crimes were predominant, with variations in top offenses across UCR parts. Examining streets associated with UCR parts, “WASHINGTON ST” consistently appeared prominently. Additionally, I explored district-level data, highlighting the districts with the highest occurrences for different UCR parts. Finally, I identified the top five streets with the most diverse range of crimes, such as “CENTRE ST” and “WASHINGTON ST,” and visualized the findings through insightful bar graphs. Overall, the analysis provided a comprehensive understanding of the dataset’s crime patterns, street occurrences, and UCR categories.
