imranshiundu/population

A comprehensive data pipeline and interactive dashboard for analyzing age- and sex-structured population data from WorldPop for Kenya and Uganda. This project transforms complex spatial datasets into actionable insights for public health planning and resource allocation. # WorldPop Population Dashboard A comprehensive data pipeline and interactive dashboard for analyzing age- and sex-structured population data from WorldPop for Kenya and Uganda. This project transforms complex spatial datasets into actionable insights for public health planning and resource allocation. ## 📋 Project Overview The WorldPop Population Dashboard provides: - **Data Pipeline**: Automated processing of WorldPop 2025 raster data - **District-Level Analysis**: Population summaries using GADM administrative boundaries - **Interactive Dashboard**: Filterable visualizations for country, age group, and sex - **Public Health Insights**: Automated analysis and service planning recommendations ### Key Features - 🌍 **Multi-country support**: Kenya (KEN) and Uganda (UGA) - 👥 **Age-sex disaggregation**: 17 age groups, male/female breakdown - 🗺️ **Spatial analysis**: District-level population mapping - 📊 **Interactive visualizations**: Choropleth maps, age-sex pyramids, summary charts - 🏥 **Public health context**: Automated insights and service recommendations ## 🚀 Quick Start ### Prerequisites - Python 3.8 or higher - 4GB RAM minimum (8GB recommended for large datasets) - 2GB free disk space ### Installation 1. **Clone the repository** ```bash git clone cd population-dashboard ``` 2. **Create virtual environment** ```bash # On Windows python -m venv venv venv\Scripts\activate # On macOS/Linux python3 -m venv venv source venv/bin/activate ``` 3. **Install dependencies** ```bash pip install -r requirements.txt ``` 4. **Set up project structure** ```bash # Create necessary directories mkdir -p assets/gadm outputs cache ``` ### Running the Dashboard 1. **Start the dashboard** ```bash streamlit run dashboard/app.py ``` 2. **Open your browser** - Navigate to: `localhost` - The dashboard will load with sample data 3. **Explore the data** - Use sidebar filters for country, age groups, and sex - View public health insights and visualizations - An …