KosiMbachuIgwe/Covid-19-Data-Analytics-Project

The aim of this project is to utilize data analytics expertise to gather, examine, analyze, visualize, and draw conclusions from COVID-19 data that is critical to Nigeria. Specifically, the focus is on assessing the virus's spread in different states, as well as its impact on the Real Domestic Gross Product and State Budget. # Nigeria-Covid-19-Data-Analytics-Project-Using-Python This project provides data analytics skills in collecting, exploring, perform analysis, create visualizations, and generate insights of COVID-19 data central to Nigeria in terms of penetration of the virus across each states, Real Domestic Gross Product and State Budget in relation to the pandemics. # PROJECT OVERVIEW Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus, and it has affected major parts of the world. Nigeria, a West-African country, has also been affected by the COVID-19 pandemic after recording its first case on 27th February 2020. Nigeria is a country with 37 states - Federal Capital Territory included- and a fast-growing economic environment with about 200 million citizens. COVID-19 has affected several country activities as the country steadily progressed from its first case to shutting down major airports, state-wide lockdown, curfews, and reviving its economy. # PROJECT APPROACHES In this project, data science and analytics skills are employed to collect data, explore the data, perform analysis, create visualizations, and generate insights. ## DATA INFORMATION The data source is divided into different parts, and combined to perform analysis and provide insights. 1. The Nigeria Centre for Diseases Control (NCDC) monitors the country’s COVID-19 situation, and releases data on the states affected by the virus, the number of cases on confirmation and admission, number of discharged, and number of death. 2. The Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE) publishes daily data on confirmed, death and recovered cases across different countries. The data for Nigeria will only be extracted from there. 3. Nigeria Community Vulnerability Index data. The vulnerability index was computed by considering several factors such as socio-economic status, population density, housing type, transportation, epidemiological, healt …