Fatal Police Shootings Data Analysis
This project is a comprehensive data analysis study of fatal interactions between law enforcement and citizens in the USA. The analysis covers data from 2015 to 2024, examining fatal police shootings, law enforcement deaths, demographic patterns, geographic distributions, temporal trends, and statistical relationships. The project uses multiple datasets from Washington Post and other sources to provide insights into police-civilian interactions, mental health factors, racial disparities, and law enforcement agency involvement. It includes statistical hypothesis testing (t-tests, ANOVA, chi-square), linear regression for temporal trends, geographic visualization on USA maps, and comprehensive cross-analysis of multiple variables.
Overview
This project is a comprehensive data analysis study of fatal interactions between law enforcement and citizens in the USA. The analysis covers data from 2015 to 2024, examining fatal police shootings, law enforcement deaths, demographic patterns, geographic distributions, temporal trends, and statistical relationships. The project uses multiple datasets from Washington Post and other sources to provide insights into police-civilian interactions, mental health factors, racial disparities, and law enforcement agency involvement. It includes statistical hypothesis testing (t-tests, ANOVA, chi-square), linear regression for temporal trends, geographic visualization on USA maps, and comprehensive cross-analysis of multiple variables.
Key Features
Comprehensive analysis of fatal police shootings (2015-2024)
Geographic visualization on USA maps with GeoPandas
Statistical hypothesis testing (t-tests, ANOVA, chi-square)
Linear regression for temporal trends
Demographic analysis (age, gender, race) with statistical tests
Mental health factor analysis and cross-analysis
Law enforcement agency analysis and rankings
Temporal analysis (monthly trends, seasonal patterns)
State and county-level death count analysis
Comparative analysis of law enforcer vs. civilian deaths
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Technical Highlights
Analyzed multiple datasets from Washington Post and other sources
Created geographic visualizations on USA maps showing event locations
Performed comprehensive statistical hypothesis testing
Identified temporal trends using linear regression
Analyzed demographic patterns with proper statistical methods
Examined mental health factors and their relationships
Challenges and Solutions
Multiple Data Sources
Integrated data from multiple sources with different formats using standardized loading and cleaning procedures
Missing Data
Carefully analyzed and handled missing values in critical columns like oricodes and demographic data
Geographic Data
Converted location data to geographic coordinates using GeoPandas and Shapely
Statistical Testing Assumptions
Verified assumptions (normality, independence) before performing statistical tests
Large Dataset Processing
Optimized Pandas operations and used chunk processing for efficient handling of large datasets
Temporal Analysis
Implemented time series aggregation, linear regression, and temporal visualizations for trend analysis
Technologies
Data Processing
Visualization
Statistical Analysis
Geographic
Data
Project Information
- Status
- Completed
- Year
- 2024
- Architecture
- Comprehensive Data Analysis Pipeline with Statistical Testing and Visualization
- Category
- Data Science