{"title":"新冠肺炎疫情数据可视化研究","authors":"Xiaoquan Ou, Zuying Zhu, Junyan Chen, W. Xiao","doi":"10.1109/ECICE50847.2020.9301964","DOIUrl":null,"url":null,"abstract":"The development of science and technology and the innovation of network technology enable big data technology. In the pandemic of coronary pneumonia in 2020, complex and large scale epidemic data, data analysis, and processing play an important role. Data visualization shows the advantages of rapid processing and intuitive display of data analysis, which helps people accurately and objectively predict the direction of the epidemic. This paper aims to create display pages on the front end of the epidemic data website with HTML, CSS, and JavaScript. The Flask framework of python is used to build a server to process the data on the back end. At the same time, ECharts is used to visualize and analyze the data, which finally displays the status and trend of the epidemic in each region in real-time.","PeriodicalId":130143,"journal":{"name":"2020 IEEE Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":"383 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Study of Data Visualization of the Neo-coronary Pneumonia Epidemic\",\"authors\":\"Xiaoquan Ou, Zuying Zhu, Junyan Chen, W. Xiao\",\"doi\":\"10.1109/ECICE50847.2020.9301964\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The development of science and technology and the innovation of network technology enable big data technology. In the pandemic of coronary pneumonia in 2020, complex and large scale epidemic data, data analysis, and processing play an important role. Data visualization shows the advantages of rapid processing and intuitive display of data analysis, which helps people accurately and objectively predict the direction of the epidemic. This paper aims to create display pages on the front end of the epidemic data website with HTML, CSS, and JavaScript. The Flask framework of python is used to build a server to process the data on the back end. At the same time, ECharts is used to visualize and analyze the data, which finally displays the status and trend of the epidemic in each region in real-time.\",\"PeriodicalId\":130143,\"journal\":{\"name\":\"2020 IEEE Eurasia Conference on IOT, Communication and Engineering (ECICE)\",\"volume\":\"383 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-10-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE Eurasia Conference on IOT, Communication and Engineering (ECICE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ECICE50847.2020.9301964\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE Eurasia Conference on IOT, Communication and Engineering (ECICE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ECICE50847.2020.9301964","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Study of Data Visualization of the Neo-coronary Pneumonia Epidemic
The development of science and technology and the innovation of network technology enable big data technology. In the pandemic of coronary pneumonia in 2020, complex and large scale epidemic data, data analysis, and processing play an important role. Data visualization shows the advantages of rapid processing and intuitive display of data analysis, which helps people accurately and objectively predict the direction of the epidemic. This paper aims to create display pages on the front end of the epidemic data website with HTML, CSS, and JavaScript. The Flask framework of python is used to build a server to process the data on the back end. At the same time, ECharts is used to visualize and analyze the data, which finally displays the status and trend of the epidemic in each region in real-time.
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