COVID-19 Data Tracker & Visualizer with Forecasting and Analytics

The COVID-19 pandemic has triggered a global demand for real-time data analysis, monitoring, and visualization. In response, this paper presents a comprehensive COVID-19 Data Tracker and Visualizer developed using Python, Pandas, Plotly, and Google Colab. This system processes a publicly available Kaggle dataset that contains chronological data on confirmed, recovered, and death cases worldwide. The notebook not only visualizes this data with interactive and informative graphs but also forecasts future trends using simple linear regression models. It presents critical visual summaries, including line plots for daily cases, active case trends, a choropleth world map for spatial distribution, and a pie chart illustrating recovery and death ratios. The results show that the model can effectively communicate evolving COVID-19 patterns and enable meaningful insight for academic, public health, and data science audiences. This project serves as a lightweight, accessible tool to bridge data and decision-making during global health crises.