https://github.com/ajitagupta/cyclone-risk-dashboard
A statistical dashboard built using Streamlit for modeling cyclone risk
https://github.com/ajitagupta/cyclone-risk-dashboard
cyclone dashboard python risk-dashboard risk-modelling streamlit streamlit-dashboard
Last synced: 7 months ago
JSON representation
A statistical dashboard built using Streamlit for modeling cyclone risk
- Host: GitHub
- URL: https://github.com/ajitagupta/cyclone-risk-dashboard
- Owner: ajitagupta
- License: mit
- Created: 2025-02-26T10:47:29.000Z (8 months ago)
- Default Branch: main
- Last Pushed: 2025-03-04T18:10:17.000Z (7 months ago)
- Last Synced: 2025-03-04T19:20:54.991Z (7 months ago)
- Topics: cyclone, dashboard, python, risk-dashboard, risk-modelling, streamlit, streamlit-dashboard
- Language: HTML
- Homepage: https://cyclone-risk-dashboard.streamlit.app/
- Size: 226 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Cyclone Risk Analysis Dashboard
## Overview
This project provides a **Cyclone Risk Analysis Dashboard** built using **Streamlit**. The dashboard visualizes and analyzes cyclone-related data, helping users understand cyclone occurrences, risk levels, and affected regions.
## Features
- **Interactive Map**: Displays cyclone paths with risk levels.
- **Data Filtering**: Select by date, location, and risk level.
- **Statistical Insights**: Shows key metrics on cyclone frequency and impact.
- **Graphical Representations**: Includes bar charts, time series plots, and heatmaps.
- **User-Friendly Interface**: Built with Streamlit for an intuitive experience.
## Installation
To run the dashboard locally, follow these steps:
### Prerequisites
- Python 3.8+
- Pip
- Virtual environment (optional but recommended)
### Steps
1. **Clone the repository**:
```bash
git clone https://github.com/your-username/cyclone-risk-dashboard.git
cd cyclone-risk-dashboard
```
2. **Create a virtual environment** (optional but recommended):
```bash
python -m venv venv
source venv/bin/activate # On Windows use: venv\Scripts\activate
```
3. **Install dependencies**:
```bash
pip install -r requirements.txt
```
4. **Run the Streamlit app**:
```bash
streamlit run app.py
```
## Usage
Once the dashboard is running, open the provided local URL in your browser. Use the sidebar controls to filter data and explore cyclone risks.
## Technologies Used
- **Python**
- **Streamlit**
- **Pandas** (for data handling)
- **Matplotlib & Seaborn** (for visualizations)
- **Geopandas** (for mapping)
- **Plotly** (for interactive graphs)
## Data Source
The cyclone data used in this project is sourced from [Admin 0 – Countries](https://www.naturalearthdata.com/downloads/110m-cultural-vectors/).
## Contributing
Contributions are welcome! Feel free to open an issue or submit a pull request.
## License
This project is licensed under the MIT License.
---
⭐ If you like this project, give it a star 🚀