This project analyzes the patterns and trends in fatal police encounters in the United States. Focusing on data from various sources, the study examines how factors like race, age, socioeconomic status, mental health, and weapon accessibility influence the frequency of fatal police incidents. The research investigates whether certain demographic groups or external factors contribute to the higher occurrence of these encounters, with the goal of highlighting areas for policy intervention and societal change.
Fatal police encounters in the U.S. have been a topic of significant concern, and this study aims to answer the following questions:
- What trends and patterns can be identified in fatal police encounters?
- How do factors such as age, race, and socioeconomic status contribute to the likelihood of a fatal encounter?
- Can we identify significant correlations between mental health issues, weapon accessibility, and fatal encounters?
| Category | Tools/Skills |
|---|---|
| Programming Language | Python, R |
| Data Analysis | pandas, numpy, statsmodels |
| Data Visualization | matplotlib, seaborn, plotly |
| Data Wrangling | pandas, numpy, scikit-learn |
| Geospatial Analysis | geopandas, folium, shapely |
| Machine Learning | scikit-learn |
To answer the research questions, the project follows these steps:
- Data Collection: Datasets on fatal police encounters are gathered from The Washington Post.
- Data Cleaning and Wrangling: The data is preprocessed to ensure accuracy, consistency, and completeness.
- Analysis: Various trends, correlations, and patterns are explored, with a focus on the intersection of race, age, and socioeconomic status. Statistical techniques and visualizations are used to reveal insights.
- Insights: Observations about the demographic and socio-economic factors that contribute to fatal police encounters are drawn, with a special emphasis on how these insights could inform policy changes.
From the analysis, several key findings emerged:
- Age Demographics: Individuals aged 25–45 make up the majority of fatalities, with a significant proportion of victims being younger than 25, suggesting increased vulnerability among younger age groups.
- Racial Disparities: Black and Hispanic communities experience disproportionately high fatal police encounter rates. Racial disparities, compounded by socioeconomic factors, contribute to these higher risks.
- Socioeconomic Factors: Areas with high poverty rates exhibit a strong correlation with lower high school graduation rates, which may amplify the risk of fatal police encounters in those communities. Poverty exacerbates stress, crime rates, and the likelihood of police interactions.
- Mental Health and Weapon Accessibility: A significant proportion of fatal incidents involve individuals with mental health issues or who were armed at the time of the encounter, pointing to the need for improved crisis intervention and tighter regulations on weapon accessibility.
- Geographic Distribution: Urban centers such as Los Angeles, Phoenix, and Houston have some of the highest fatality rates. These cities face compounded challenges, including high population density and systemic inequality, highlighting the need for targeted interventions in urban settings.
- Data Source: The Washington Post (Police Shootings Database)
- GitHub Repository: Fatal Police Encounters Analysis Repository