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Crime Data Analysis & Visualization (Dallas Police Dataset)
Analyzed a real-world policing dataset to uncover crime patterns, trends, and disparities using R and visualization techniques.
Dec 2023
Project Overview
This project explores a real-world policing dataset from Dallas, Texas (2016) using data visualization and statistical analysis techniques. The objective was to uncover hidden patterns, identify crime hotspots, and analyze disparities in policing outcomes. The dataset consists of 2,383 records with 47 variables.
Working of Project
The dataset was cleaned and transformed using R. Missing values and irrelevant columns were handled, followed by feature engineering such as extracting month, hour, and day from timestamps. Exploratory Data Analysis (EDA) was performed to identify patterns. Multiple visualizations including bar charts, time-series graphs, and geospatial maps were created using ggplot2, Plotly, and Leaflet.
Key Features
- Data Cleaning & Preprocessing
- Feature Engineering (Time-based analysis)
- Exploratory Data Analysis (EDA)
- Geospatial Crime Mapping
- Interactive Visualizations
Technologies Leveraged
- R
- ggplot2
- Plotly
- Leaflet
- dplyr