UIDAI Analytics Dashboard

Overview

Comprehensive analytics dashboard for UIDAI enrollment data

☞ See it live: uidai-data-analytics.streamlit.app

☞ Read the project report: Link

Key Features

• Auto-Detection: Automatically finds and loads all notebooks from base directory
• Smart Rendering: Only displays sections containing visualizations
• Plot Selection: Dropdown to select specific plots with descriptions
• Team Integration: All team members properly credited
• Interactive: Dynamic plot and section selection

Quick Start

# Navigate to project directory
cd /path_to_your_repo/uidai

# Run dashboard (notebooks auto-detected!)
streamlit run app/dashboard.py

Dashboard opens at: http://localhost:8501

Team Members

Analyst	Analysis
Paras	Biometric Failure Analysis
Sriyansh Sharma	Resource Allocation Optimization
Anurag Rai	Fraud Detection
Shivansh Bhageria	Rural vs Urban Adoption
Kartikeya Gupta	District-level Hotspots

Analysis Features

1. Biometric Failure Analysis

• Failure pattern detection
• Age group analysis
• Geographic distribution
• Temporal trends

2. Resource Allocation Optimization

• Demand forecasting
• Resource distribution analysis
• Efficiency metrics

3. Fraud Detection

• Anomaly detection
• Pattern recognition
• Risk scoring

4. Rural vs Urban Adoption

• Comparative analysis
• Adoption trends
• Demographic insights

5. District-level Hotspots

• Geographic anomalies
• Performance metrics
• Hotspot identification

How It Works

1. Auto-Detection: Dashboard scans base directory for notebooks
2. Section Parsing: Extracts sections containing plots
3. Smart Display: Shows only relevant sections with visualizations
4. Plot Selection: Dropdown to choose specific plots
5. Description: Displays markdown text following each plot

Usage

1. Select Feature from sidebar dropdown
2. Choose Section containing the analysis you want
3. Select Plot from available visualizations
4. Read Description below the plot

Installation

# Install dependencies
pip install streamlit pandas plotly numpy jupyter

# Run dashboard
streamlit run enhanced_streamlit_dashboard.py

Data Schema

Biometric Data

• date, state, district, pincode
• bio_age_5_17: Biometric enrollments (age 5-17)
• bio_age_17_: Biometric enrollments (age 17+)

Demographic Data

• date, state, district, pincode
• demo_age_5_17: Demographic enrollments (age 5-17)
• demo_age_17_: Demographic enrollments (age 17+)

Enrollment Data

• date, state, district, pincode
• age_0_5, age_5_17, age_18_greater: Age-wise enrollments

Dashboard Features

• Dashboard Overview: Key metrics and quick insights
• Auto-Loading: No manual file uploads needed
• Plot Dropdown: Select specific visualizations
• Section Navigation: Jump to relevant analysis sections
• Team Credits: All analysts properly acknowledged

Notes

• Place all .ipynb files in the analysys_notebooks directory
• Dashboard automatically detects and loads them
• Only sections with plots are displayed
• Descriptions follow each visualization

Support

For issues or questions, contact the team members listed above.

License

MIT License