mr-robot369/indian-road-accident-dashboard

🚦 Indian Road Accident Dashboard 🇮🇳

🔗 Live Demo:\ https://mr-robot369-indian-road-accident-dashboard.hf.space/ <p align="center"> <img src="assets/dashboard.png" alt="Dashboard Preview" width="95%" height="100%"> </p> ------------------------------------------------------------------------

📌 Overview

The Indian Road Accident Dashboard is an interactive data visualization application built using Plotly Dash to analyze and explore road accident statistics across India.\ It provides state-wise, temporal, and trend-based insights into road accidents through dynamic charts and maps.

The dashboard is deployed for free on Hugging Face Spaces using Docker, ensuring public accessibility and reproducibility.

🎯 Objectives

• —Analyze road accident patterns in India\
• —Visualize state-wise accident distribution\
• —Study year-wise and trend-based variations\
• —Provide an interactive, user-friendly dashboard for analysis and awareness

🧩 Key Features

• —Interactive Plotly charts with hover, zoom, and filters\
• —State-wise road accident analysis\
• —Year-wise and trend-based visualizations\
• —Choropleth map of India showing accident intensity\
• —Optimized performance using modular chart functions\
• —Plotly and Dash assets served locally\
• —Clean, scalable, and modular codebase\
• —Public deployment on Hugging Face Spaces

🛠️ Tech Stack

• —Frontend / Visualization: Plotly, Dash\
• —Backend: Python\
• —Data Handling: Pandas, NumPy\
• —Deployment: Docker, Hugging Face Spaces\
• —Version Control: Git

📂 Project Structure

indian-road-accident-dashboard/ │ ├── app.py ├── charts.py ├── data/ │ └── accident_preprocessed.csv │ ├── assets/ │ └── styles.css │ ├── requirements.txt ├── Dockerfile └── README.md

🚀 Deployment Details

• —Platform: Hugging Face Spaces\
• —Deployment Type: Docker-based\
• —Hosting Cost: Free\
• —Public URL:\ https://mr-robot369-indian-road-accident-dashboard.hf.space/

🧠 Performance Optimizations

• —Local serving of Plotly and Dash assets to avoid CDN latency\
• —Lazy-loaded charts using callback-based rendering\
• —Modularized chart generation logic\
• —Pinned dependencies for stable and reproducible builds

📈 Use Cases

• —Academic projects and research\
• —Data visualization demonstrations\
• —Road safety analysis and awareness\
• —Resume and portfolio showcase

🔮 Future Enhancements

• —Accident severity and cause-based analysis\
• —District-level visualizations\
• —Predictive analytics using Machine Learning\
• —Downloadable reports (CSV / PDF)

👨‍💻 Author

Anubhav Shukla\ M.Sc. Data Science\ Python \| Data Science \| Visualization \| Dash

⭐ Acknowledgements

• —Government open datasets on road accidents\
• —Plotly & Dash community\
• —Hugging Face Spaces for free hosting

📌 Note

This project is created for educational and analytical purposes using publicly available data.