A powerful and interactive analytics dashboard for historical aviation accident data (1908–2022)

The BUDDHA PROJECT (part of the History of All Flight Crash Map series) is a comprehensive aviation analytics dashboard that visualizes more than a century of aircraft crash data in a single, interactive platform.

It combines data visualization, geospatial mapping, and predictive analytics to help researchers, aviation analysts, and data enthusiasts explore global crash trends, causes, and consequences.

Developed using Streamlit, Plotly, and Folium, the project blends data science and UI design for a polished, responsive, and research-ready experience.

• Interactive 3D globe showing crash points across the world.
• Clickable markers display date, operator, location, and summary.

• Dual-colored animated bars (🟣 crashes vs 🔵 fatalities).
• Adjustable playback speed: Fast (0.8s), Normal (2s), Slow (4s).

• Categorized insights into crash causes: Mechanical, Weather, Human Error, Fire, Other.
• Dynamic pie, bar, and line charts.

• Time-series visualizations of fatalities per year.
• Identify peaks, recoveries, and improvement patterns in aviation safety.

• Financial impact model: $50M per crash + $1.5M per fatality.
• Airline-wise cost and risk assessment charts.

• Real-time filters, timeline slider, and hover tooltips.
• All visualizations update dynamically with user input.

🌐 Live App: Flight Crash Mapped
Explore the entire dataset interactively with animations, filters, and geospatial mapping!

Make sure you have the following installed:

• Python 3.8+
• pip (Python package manager)
• Git

git clone https://github.com/vinaysingh282006/History-of-all-flight-crash-map.git
cd History-of-all-flight-crash-map

pip install -r requirements.txt

streamlit run streamlit_app.py

Visit ➤ http://localhost:8501

History-of-all-flight-crash-map/
│
├── streamlit_app.py          # Main Streamlit application
├── dataset.csv.csv           # Aviation crash data (1908–2022)
├── requirements.txt          # Python dependencies
├── webpreview*.png           # Preview images for README
├── LICENSE                   # MIT license
└── README.md                 # Project documentation

Dataset Fields:

Dataset Coverage:

• Years: 1908 – 2022
• Scope: Worldwide
• Records: ~5,000 incidents

• Default Chart Height: 600–700px
• Racing Bar Animation: 800px
• Responsive layout with full-width adaptive charts

1. Add your logic inside streamlit_app.py under the appropriate tab.
2. Create reusable visualization functions for each chart type.
3. Maintain modular structure for clarity.
4. Add a descriptive label to your new tab in the sidebar.

• Cache data with @st.cache_data decorator.
• Avoid unnecessary recomputations.
• Optimize Plotly animations for smoother playback.

We welcome contributions!

1. Fork this repo
2. Create a branch

   git checkout -b feature/your-feature

3. Commit & Push

   git commit -m "Add: new visualization feature"
   git push origin feature/your-feature

4. Submit a Pull Request

Before submitting, ensure there are no console errors and your code passes basic lint checks.

💬 Open a discussion or issue for:

• 🐛 Bug Reports
• 💡 Feature Requests
• ⚙️ Development Queries

📬 GitHub Discussions: Start here

Licensed under the MIT License — free for personal and commercial use.
See LICENSE for full terms.

"Every aviation incident leaves behind a lesson — this project transforms those lessons into data-driven insights for a safer tomorrow."

Made with ❤️ using Streamlit, Plotly, and Open-Source Passion ✈️🌍