Bootstrap

【推荐】新冠肺炎的最新数据集和可视化和预测分析(附代码)

新冠肺炎现在情况怎么样了?推荐Github标星24.7K+的新冠肺炎公开数据集,利用这个数据集,可以用代码进行简单地可视化及预测。

推荐新冠肺炎的公开数据集:

https://github.com/CSSEGISandData/COVID-19

数据可视化:

https://www.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6

数据集能做什么?

这个数据集可以做以下分析:

  • 全球趋势

  • 国家(地区)增长

  • 省份情况

  • 美国

  • 欧洲

  • 亚洲

  • 什么时候会收敛?进行预测

简单演示

新冠肺炎感染人数可视化效果

数据来源

数据来源:

  • World Health Organization (WHO): https://www.who.int/

  • DXY.cn. Pneumonia. 2020. http://3g.dxy.cn/newh5/view/pneumonia.  

  • BNO News: https://bnonews.com/index.php/2020/02/the-latest-coronavirus-cases/  

  • National Health Commission of the People’s Republic of China (NHC):
    http://www.nhc.gov.cn/xcs/yqtb/list_gzbd.shtml

  • China CDC (CCDC): http://weekly.chinacdc.cn/news/TrackingtheEpidemic.htm

  • Hong Kong Department of Health: https://www.chp.gov.hk/en/features/102465.html

  • Macau Government: https://www.ssm.gov.mo/portal/

  • Taiwan CDC: https://sites.google.com/cdc.gov.tw/2019ncov/taiwan?authuser=0

  • US CDC: https://www.cdc.gov/coronavirus/2019-ncov/index.html

  • Government of Canada: https://www.canada.ca/en/public-health/services/diseases/coronavirus.html

  • Australia Government Department of Health: https://www.health.gov.au/news/coronavirus-update-at-a-glance

  • European Centre for Disease Prevention and Control (ECDC): https://www.ecdc.europa.eu/en/geographical-distribution-2019-ncov-cases

  • Ministry of Health Singapore (MOH): https://www.moh.gov.sg/covid-19

  • Italy Ministry of Health: http://www.salute.gov.it/nuovocoronavirus

  • 1Point3Arces: https://coronavirus.1point3acres.com/en

  • WorldoMeters: https://www.worldometers.info/coronavirus/

  • COVID Tracking Project: https://covidtracking.com/data. (US Testing and Hospitalization Data. We use the maximum reported value from "Currently" and "Cumulative" Hospitalized for our hospitalization number reported for each state.)

  • French Government: https://dashboard.covid19.data.gouv.fr/

  • COVID Live (Australia): https://www.covidlive.com.au/

  • Washington State Department of Health: https://www.doh.wa.gov/emergencies/coronavirus

  • Maryland Department of Health: https://coronavirus.maryland.gov/

  • New York State Department of Health: https://health.data.ny.gov/Health/New-York-State-Statewide-COVID-19-Testing/xdss-u53e/data

  • NYC Department of Health and Mental Hygiene: https://www1.nyc.gov/site/doh/covid/covid-19-data.page and https://github.com/nychealth/coronavirus-data

  • Florida Department of Health Dashboard: https://services1.arcgis.com/CY1LXxl9zlJeBuRZ/arcgis/rest/services/Florida_COVID19_Cases/FeatureServer/0 and https://fdoh.maps.arcgis.com/apps/opsdashboard/index.html#/8d0de33f260d444c852a615dc7837c86

总结

本文推荐新冠肺炎的公开数据集,利用这个数据集,可以用代码进行简单地可视化及预测。

数据集地址:

https://github.com/CSSEGISandData/COVID-19

数据预测代码:

https://www.kaggle.com/corochann/covid-19-current-situation-on-october?scriptVersionId=45297457

(数据请从数据集地址下载最新)


往期精彩回顾



适合初学者入门人工智能的路线及资料下载机器学习及深度学习笔记等资料打印机器学习在线手册深度学习笔记专辑《统计学习方法》的代码复现专辑
AI基础下载机器学习的数学基础专辑
获取本站知识星球优惠券,复制链接直接打开:
https://t.zsxq.com/y7uvZF6
本站qq群704220115。

加入微信群请扫码:

;