【推荐】新冠肺炎的最新数据集和简单的可视化和预测分析（附代码）

新冠肺炎现在情况怎么样了？推荐Github标星21.7K+的新冠肺炎公开数据集，并且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

世界病例增长

美国病例增长

主要国家的比较

病例预测（按照现在的速度，到7月份，全球就会有700万例了！！！）

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，并把数据可视化，并对感染人数进行了预测。

数据集地址：

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

演示代码地址：https://github.com/fengdu78/machine_learning_beginner/blob/master/covid19/code/coronavirus-covid-19-visualization-prediction.ipynb