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Visual Exploratory Data Analysis of COVID-19 Pandemic
IEEE Int. Conf. Recent Adv. Innov. Eng., ICRAIE - Proceeding ; 2020.
Article in English | Scopus | ID: covidwho-1142834
ABSTRACT
The emerging novel coronavirus (2019-nCoV) caused by a respiratory syndrome coronavirus 2 (SARS-CoV-2) is the lead cause of threat to life worldwide today. It is important to analyze the worldwide pandemic spread so that certain guide strategies can be set for complete situational awareness and application of conventional methodologies to control the impacts caused by it globally. This paper is composed of the visual exploratory data analysis of the countries based on the number of confirmed, recovered and death cases along with the comparative analysis of the mortality and recovery rate for nearly 222 nations worldwide. Also, K-means clustering is used to cluster the countries according to the number of confirmed and death cases. Hence, this study can be used to evaluate the rise of risks in a given area by comparing the count of the cases via visual analysis and work on the set up of some strategies to control its spread globally. © 2020 IEEE.

Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: IEEE Int. Conf. Recent Adv. Innov. Eng., ICRAIE - Proceeding Year: 2020 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: IEEE Int. Conf. Recent Adv. Innov. Eng., ICRAIE - Proceeding Year: 2020 Document Type: Article