Understanding the COVID-19 Pandemic Through Data Analysis

Abstract

The COVID-19 pandemic has imposed new challenges and created the need for analyzing data to tackle public health emergencies. This study utilizes Python's prowess in data manipulation, along with Tableau's interactive visualization capabilities to take apart the massive data set of COVID-19 data. The approach we take is to thoroughly explore the data on infections, recoveries and death rates, looking for trends and connections, which can be used in policy-making decisions. Using our advanced analytics and interactive dashboard, we are working towards improving the visibility and understanding of the pandemic's trajectory and its many layers of effects. The present study adds to the academic debate but can also act as a 'how to' guide for public health officials and policy makers and guide the development of effective actions for the current crisis. In this paper, we show the synergy of Python and Tableau as powerful tools to support data-driven decision making in epidemiology.