Crime Rates in Washington, D.C.
Data visualization project analyzing 8 years of crime trends and socioeconomic correlations.
Project Snapshot
Visualized and compared crime trends across multiple offense categories over an 8-year period in Washington, D.C. Analyzed relationships between crime rates, student population, and housing prices using comparative visualizations built in R.
Problem
Understanding long-term crime patterns in urban areas requires effective visualization of multi-dimensional temporal data and correlation analysis with socioeconomic factors such as student populations and housing markets.
Approach
- Collected and cleaned 8 years of D.C. crime data across multiple offense categories
- Built comparative time-series visualizations for trend analysis
- Analyzed correlations between crime rates, student population, and housing prices
- Used layered R visualizations for multi-variable comparison
Tech Stack
R, ggplot2, dplyr, tidyverse
Results
- Identified clear temporal trends across offense categories
- Revealed correlations between socioeconomic factors and crime patterns
- Produced publication-quality comparative visualizations