Thanks to visit codestin.com
Credit goes to github.com

Skip to content

WindDAnalytics/seattlecrisis

Folders and files

NameName
Last commit message
Last commit date

Latest commit

Β 

History

7 Commits
Β 
Β 
Β 
Β 
Β 
Β 

Repository files navigation

πŸ“Š Seattle Crisis Dashboard

A data visualization and analysis dashboard built in Kaggle to explore public safety incidents reported to Seattle police. This project leverages real-world data to uncover trends, analyze call types, and display incident locations across the city.


πŸ“ Dataset Overview

  • Source: Seattle Open Data Portal
  • Records: ~99,000+ incidents
  • Date Range: May 15, 2015 – April 12, 2025
  • Columns: 25 attributes including:
    • Reported Date, Call Type, Disposition, Precinct, Sector, Beat
    • Officer demographics and classification of incidents

πŸ”§ Tools & Libraries Used

  • Pandas – data manipulation
  • Matplotlib – static chart visualization
  • Plotly – interactive charting (converted to matplotlib for compatibility)
  • Folium – interactive mapping of recent incident locations
  • NumPy – numerical operations

πŸ“Œ Key Visualizations

πŸ”Ή Incident Trends Over Time

  • Line and bar plots of daily and weekly incidents
  • Stacked visualizations by Precinct and Sector

πŸ”Ή Call Type & Precinct Analysis

  • Top 5 call types by count and precinct
  • Bar charts colored by trend (increase or decrease)

πŸ”Ή Sector Heat Trends

  • Calculated recent 3-day average vs. 30-day average
  • Colored bar plot to show rising or falling sectors

πŸ—ΊοΈ Interactive Map

  • The latest 100 incidents mapped using Folium
  • Dispositions shown as popups

🌍 Geolocation Mapping

Each police beat was manually mapped with latitude and longitude values for accurate visualization. These coordinates were cleaned and merged into the dataset to support spatial plots.


πŸ“ˆ Sample Analysis Outputs

  • Incidents Per Day: Line graph of counts over time
  • Precinct Breakdown: Stacked bar for the last 30 days
  • Disposition Types: Horizontal bar chart
  • Sector Trends: 3-day vs. 30-day trend comparison
  • Call Type Frequency: Top 5 visualized in grouped bars

πŸš€ How to Use

This dashboard is hosted and runs on Kaggle. To replicate or explore:

  1. Download the dataset
  2. Open in a Kaggle notebook or local Jupyter environment
  3. Run through the cells sequentially to view insights

🧠 Future Improvements

  • Add interactive filters by time, sector, and disposition
  • Incorporate severity or urgency scoring
  • Enable time-lapse animations using Plotly or Kepler.gl
  • Deploy on Streamlit or Flask for public use

πŸ“ Contact

Created by: Damarcus Thomas
Kaggle Notebook: [Link to your Kaggle notebook] Email: [email protected]


This project demonstrates how public datasets can be used to surface critical insights around mental health, policing, and resource allocation across urban environments.

About

Kaggle NB

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published