An interactive dashboard that maps and clusters Uganda’s wastewater treatment plants using KMeans. Built with Dash and Plotly, it features filters by cluster and treatment type, a capacity bar chart, and a correlation heatmap to support data-driven planning and infrastructure analysis.
# 🚰 Uganda Wastewater Treatment Plant Clustering Dashboard 🌍
This project visualizes and analyzes **Wastewater Treatment Plants (WWTPs)** across **Uganda** using geospatial clustering, treatment type analysis, and capacity insights. Built with **Dash**, **Plotly**, and **scikit-learn**, the app allows interactive exploration of Uganda’s wastewater infrastructure.
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## 💡 Project Overview
Wastewater treatment is crucial for public health and environmental sustainability. This dashboard aims to:
- 🗺️ Visualize spatial clusters of WWTPs
- 🧪 Analyze treatment types and their total capacities
- 📊 Examine the correlation between treatment types and capacity
- 🎯 Aid stakeholders like NGOs and governments in better planning and resource allocation
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## 🚀 Live Demo
👉 Launch Dashboard
*(You can deploy it using Render, Heroku, or Dash Enterprise)*
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## ⚙️ Tech Stack
- 🐍 Python (Pandas, NumPy, scikit-learn)
- 📊 Dash & Plotly
- 🌐 HTML/CSS with Dash Components
- 📍 KMeans Clustering for geographic grouping
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## 📦 Installation
```bash
# Clone the repo
git clone
github.com
cd uganda-wwtp-dashboard
# Install dependencies
pip install -r requirements.txt
# Run the Dash app
python app.py