Visual Exploratory Data Analysis of COVID-19 Pandemic

被引:1
作者
Saini, Sumindar Kaur [1 ]
Dhull, Vishal [1 ]
Singh, Sarbjeet [1 ]
Sharma, Akashdeep [1 ]
机构
[1] Panjab Univ, UIET, Comp Sci & Engn, Chandigarh, India
来源
2020 5TH IEEE INTERNATIONAL CONFERENCE ON RECENT ADVANCES AND INNOVATIONS IN ENGINEERING (IEEE - ICRAIE-2020) | 2020年
关键词
COVID-19; Pneumonia; Data Analysis; Pandemic; Clustering; Coronavirus;
D O I
10.1109/ICRAIE51050.2020.9358331
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
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.
引用
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页数:6
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