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COVID-Team-3

Covid Data Analysis

Table of contents

Introduction

No one could have ever imagined the situation that the entire world would be living in early this year. The pandemic virus COVID-19 also known as coronavirus, made the entire world pause for several weeks and even months. This requires many changes to the everyday life of each person including the prevention of social gatherings, increase of disinfection processes, use of masks, and closing of businesses as well as government offices. This drastically changed and affected the lives of many. Some lost their jobs and others even lost their own loved ones. This motivated organizations to monitor and record this virus as well as study its habits to prevent its spread and protect our most loved ones. As a part of the Data Science course (CSC 405/605) taught at the University of North Carolina at Greensboro by Dr. Somya Mohanty, we have taken the task to analyze the publicly available data obtained by various organizations of the virus COVID-19 to learn more about this virus and try to derive conclusions from the analysis of the data. As a team we will strive to understand and analyze this information as a means to not only further our learning of Data Science but as well as try to derive conclusions from the data which could be helpful to further the understanding of this virus that has affected our lives so drastically.

Who are we :

  • Nikitha Narsing, Graduate student in department of CS at UNCG
  • Amulya Yadagani, Graduate student in department of CS at UNCG
  • Rashmi Hassan Udaya Kumar,Graduate student in department of CS at UNCG
  • Serena Wisnewski, Undergraduate student in department of CS at UNCG
  • Eric Cortes Aguilera, Undergraduate student in department of CS at UNCG

Project Aim

We intend to analyse the covid-19 data and a few enrichment datasets to draw meaningful insights from it. We also envision to develop models which can predict the information about the number of covid-19 cases and deaths across the various counties present in the United States of America and display this information supported by facts and stastics through a dashboard.

Technologies Used

We are using Python3 as a programming lannguage and include code, narrative text, equations and rich output though Jupyter Notebooks. We are also making use of various python libraries in data science like Numpy, Pandas for scientific computation.

Setup

The /src folder contains the Jupyter notebooks and the /data folder contains the the various data sets that we are using for the analysis. The detailed information and documetation about this project is inculded in the report which is present under the /docs folder of this repository.

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