This analysis focused on understanding crime patterns across Montgomery County using a structured data science workflow. My role involved preparing the dataset for deeper analysis by conducting data quality checks, identifying and handling missing values, removing duplicates, correcting data types, and resolving inconsistencies in key columns such as city names and timestamps.

Once the dataset was cleaned, I performed extensive Exploratory Data Analysis (EDA) to uncover trends across cities, police districts, crime types, seasons, and hours of the day. Using Python (Pandas, Matplotlib, Seaborn), I generated visualisations including heatmaps, line charts, bar charts, and distribution plots, each designed to answer specific research questions from the report.

These visual insights formed the foundation for the group’s findings on crime hotspots, unsolved case patterns, seasonal behaviour, and police response times, helping shape the final recommendations.