COVID-19 Data Exploration

There are different types of coronavirus that can infect humans and animals. A novel strain of coronavirus was first detected in December 2019 in Wuhan, China. It was declared as a pandemic by the World Health Organization (WHO) in March 2020. Since then, COVID-19 is controversial and people (including me) did not stop asking questions regarding the novel coronavirus.

In this Project, I aim to exploit python tools for data scinece in order to answer COVID-19 related questions including:

1. Which countries have the highest total cases/deaths toll?
2. Is the number of COVID-19 cases correlated with country population?
3. What is the case fatality rate?

In this repository you can find:

1. Data file : raw csv dataset used in this notebook
2. Jupyter Notebook: data analysis using python libraries

Table of Contents

• 1. Libraries
• 2. Installation
• 3. Data Source
• 4. Acknowladgment

1. Libraries

Pandas
Plotly
Seaborn

2. Installation

pip Pandas
Pip Plotly
Pip Seaborn

3. Data Source

For this purpose, I used a public dataset for 170 countries worldwide.

http://dx.doi.org/10.17632/b2wvnbnpj9.1

4. acknowledgements

Vitenu-Sackey, Prince Asare (2020), “The Impact of Covid-19 Pandemic on the Global Economy: Emphasis on Poverty Alleviation and Economic Growth”, Mendeley Data, V1, doi: 10.17632/b2wvnbnpj9.1