Project Overview: Metropolitan Crime Data Analysis This project performs an exploratory data analysis (EDA) on metropolitan street crime data for January 2020. The objective was to transform raw data into actionable insights by identifying key trends and patterns in criminal activity.

Key Activities:

Data Ingestion & Validation: The dataset was programmatically loaded with robust error handling to manage file path issues.

Data Cleansing: Irrelevant columns were removed, missing critical identifiers were filled, and records without geospatial coordinates were dropped to ensure analysis integrity. The final cleaned dataset contained 90,435 records.

Trend Analysis: The analysis identified the most frequent crime types and common locations for incidents.

Data Visualization: Findings were communicated through clear visualizations, including a bar chart of top crime categories and a geospatial scatter plot to pinpoint crime hotspots.

Primary Insights: The analysis revealed that Violence and sexual offences and Anti-social behaviour were the most prevalent crime categories, constituting a significant portion of total incidents. Geospatial visualization successfully identified high-density crime areas.

Value Proposition: This analysis provides a data-driven foundation for resource allocation and strategic planning for law enforcement and urban policy teams, highlighting specific crime types and geographical areas that require targeted intervention.