OAK India WASH Data Analysis

A comprehensive Streamlit web application for analyzing Water, Sanitation, and Hygiene (WASH) data from OAK India. This application provides interactive data visualization, mapping, and statistical analysis capabilities for WASH-related datasets.

🌊 Features

📊 Data Analysis & Visualization

• Interactive Dashboards: Multi-page Streamlit application with comprehensive data analysis tools
• Statistical Analysis: Outlier detection using Z-score and IQR methods
• Data Clustering: DBSCAN clustering for spatial data analysis
• Chart Generation: Multiple chart types including bar charts, scatter plots, and custom water usage visualizations

🗺️ Geographic Visualization

• Interactive Maps: Folium-based maps with marker clustering
• Hexbin Maps: Custom hexbin visualization for spatial data density
• GPS Data Processing: Support for Bengali GPS column mapping
• Village-level Analysis: Geographic analysis at village and para (neighborhood) levels

📈 Advanced Analytics

• Outlier Detection: Automated detection and highlighting of statistical outliers
• Data Quality Assessment: String similarity matching for column mapping
• Report Generation: HTML report generation with embedded charts
• Export Capabilities: PDF and image export functionality

🌐 Multi-language Support

• Bengali Language Support: Native support for Bengali column names and data
• Font Integration: NotoSansBengali font for proper Bengali text rendering

🚀 Quick Start

Prerequisites

• Python 3.11 or higher
• Conda (recommended) or pip

Installation

Option 1: Using Conda (Recommended)

# Clone the repository
git clone <repository-url>
cd oak-india-streamlit

# Create and activate conda environment
conda env create -f environment.yml
conda activate oak-wash

# Run the application
streamlit run app.py

Option 2: Using pip

# Clone the repository
git clone <repository-url>
cd oak-india-streamlit

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Run the application
streamlit run app.py

Usage

1. Open your web browser and navigate to http://localhost:8501
2. Upload your WASH data CSV file or use the provided sample data
3. Explore the various analysis tools and visualizations
4. Generate reports and export results as needed

📁 Project Structure

oak-india-streamlit/
├── app.py                 # Main Streamlit application
├── requirements.txt       # Python dependencies for pip
├── environment.yml        # Conda environment configuration
├── README.md             # This file
└── src/                  # Source code modules (if applicable)
    └── visualization.py   # Custom visualization modules