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Master-45-vic/UIDAI_DATA_HACKTHON_2026

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UIDAI_DATA_HACKTHON_2026

This project analyzes Aadhaar enrolment and update data to uncover temporal, regional, and demographic trends. It identifies patterns, anomalies, and peak periods to support data-driven policy and infrastructure planning.

Key Highlights: 1.Cleaned and standardized large-scale Aadhaar datasets 2.Trend analysis across time, geography, and age groups 3.Detection of peak enrolment periods and regional disparities 4.Actionable policy insights for resource allocation and service optimization

Tech Stack: Python, Pandas, Matplotlib/Seaborn, Jupyter Notebook

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This project analyzes Aadhaar enrolment and update data to uncover temporal, regional, and demographic trends. It identifies patterns, anomalies, and peak periods to support data-driven policy and infrastructure planning.

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