Analysis on COVID-19 Infection rates globally 2020

This project involves analyzing global COVID-19 datasets using Python to uncover patterns in infection rates, mortality, and recovery trends over time. Using libraries like Pandas, NumPy, and Matplotlib, I cleaned, processed, and visualized data sourced from Kaggle. I conducted time-series analysis to identify peaks and waves, and compared regional responses and vaccination rollouts. The project also included building a simple interactive dashboard using Plotly to display country-specific insights. The goal was to support data-driven public health decision-making through accessible and accurate analytics.