UIDAI(Aadhaar) Data Hackathon - 2026

A comprehensive data analysis project for exploring and modeling Aadhaar-related datasets, including biometric, demographic, and enrolment information.

📋 Project Overview

This project analyzes three key datasets related to Aadhaar:

• Biometric Data: Contains biometric information (1,861,108 records)
• Demographic Data: Contains demographic information (2,071,700 records)
• Enrolment Data: Contains enrolment information (1,006,029 records)

📁 Project Structure

aadhaar_hackathon/
├── Data/
│   ├── Combined_CSV/              # Merged CSV files
│   │   ├── api_data_aadhar_biometric_combined.csv
│   │   ├── api_data_aadhar_demographic_combined.csv
│   │   └── api_data_aadhar_enrolment_combined.csv
│   ├── Raw_Data/                  # Raw data split into chunks
│   │   ├── api_data_aadhar_biometric/
│   │   ├── api_data_aadhar_demographic/
│   │   └── api_data_aadhar_enrolment/
│   └── merge.ipynb                # Notebook for merging raw data
├── model.ipynb                    # Main analysis notebook
├── requirements.txt               # Python dependencies
├── LICENSE                        # MIT License
└── README.md                      # This file

🚀 Getting Started

Prerequisites

• Python 3.8 or higher
• pip package manager

Installation

1. Clone the repository:

git clone https://github.com/Marmikgaj/aadhaar_hackathon.git
cd aadhaar_hackathon

2. Create a virtual environment (recommended):

python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

3. Install required packages:

pip install -r requirements.txt

💻 Usage

Running the Analysis

1. Open the main analysis notebook:

jupyter notebook model.ipynb

2. Run the cells sequentially to:
   • Load the three datasets
   • View dataset summaries and statistics
   • Perform data analysis and modeling

Data Processing

The project includes combined CSV files ready for analysis. If you need to re-merge the raw data chunks:

1. Navigate to the Data directory
2. Open merge.ipynb to combine raw data files

📦 Dependencies

• pandas==2.3.3 - Data manipulation and analysis
• numpy==2.4.0 - Numerical computing
• python-dateutil==2.9.0.post0 - Date/time utilities
• pytz==2025.2 - Timezone support
• tzdata==2025.3 - Timezone database

📊 Dataset Information

Dataset	Rows	Source Files
Biometric	1,861,108	4 chunks
Demographic	2,071,700	5 chunks
Enrolment	1,006,029	3 chunks

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

👥 Authors

_{Marmik Gajbhiye}

🤝 Contributor

Anant Kumar

Nicky Yadav

Aditya Vaidhya

Ashutosh Gaurav

🙏 Acknowledgments

• Aadhaar Hackathon organizers
• Data providers

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Note: This project is developed for educational and research purposes as part of a hackathon.