Back to datasets
Dataset assetOpen Source CommunityData AnalysisGun Violence
United States of America Gun violence Dataset
This report provides a detailed analysis of US gun violence data collected from 2013 to 2018, aiming to better understand the hazards of US gun culture. The analysis integrates information on age groups, gender, states, locations, as well as socioeconomic data such as population, per‑capita income, and unemployment rates to predict the most dangerous and safest states. Additionally, the report attempts to forecast which months and weekdays are more dangerous or safer for citizens, generating a risk score to predict the safest month, day, and state.
Source
github
Created
Aug 6, 2020
Updated
Aug 7, 2020
Signals
159 views
Availability
Linked source ready
Overview
Dataset description and usage context
US Gun Violence Dataset Analysis
Dataset Overview
- Topic: US Gun Violence
- Time Span: 2013–2018
- Analysis Objective: Deeply understand US gun culture and predict which states are most dangerous and safest, as well as which months and weekdays are more dangerous or safer for citizens.
Data Content
- Basic Information: Age groups, gender, state, location, etc.
- Additional Parameters: Population, per‑capita income, unemployment rate
Analysis Methodology
- Detailed Analysis: In‑depth analysis combining basic information and additional parameters
- Predictive Model: Use socioeconomic data to predict state safety
- Risk Score: Assign appropriate weights to attributes to generate a risk score, forecasting safety for specific times (months, weekdays) and locations
Code Access Steps
- Clone the repository:
git clone <this-repo> - Open the
.ipyndfile: open it in any code editor to learn more about the predictive analysis code usage.
Need downstream help?
Pair the dataset with AI analysis and content workflows.
Once the source passes your review, move straight into summarization, transformation, report drafting, or presentation generation with the JuheAI toolchain.