Crime Analysis Project eMindGuard

Project Aim: Analyze crime data from the Chicago Crime Data Portal from October 1, 2024, to November 14, 2024.

Focus area: Six major crime types: ROBBERY, HOMICIDE, CRIMINAL SEXUAL ASSAULT, BURGLARY, MOTOR VEHICLE THEFT, ASSAULT

Data Processing Techniques:

• Normalization
• Principal Component Analysis (PCA)

Key Outcome: Visualized crime distribution across Chicago neighborhoods.

Methodology:

1. Data Preprocessing: Datetime formats, null value and empty row removal, and data type adjustment
2. Geolocation and Zip Codes: Geocoding API to retrieve Census-tracts based on latitude and longitude, FIPS to census tracts for GeoID
3. Data Analysis: Normalized crime frequencies using Min-Max normalization, (PCA) to summarize crime data into a single normalized value
4. Visualization: Heatmap (Choropleth map) using GeoPandas to visualize normalized summary values across census tracts

Plan to integrate findings into the eMindguard project for:

• Enhancing community awareness.
• Supporting informed decision-making.

Heatmap:

Sample Frequencies for 3 census tracts:

References:

1. Department, C. P . (2022, January 10). Crimes - 2022: City of chicago: Data Portal. Chicago Data Portal. https://data.cityofchicago.org/Public-Safety/Crimes-2001-to-Present/ijzp-q8t2