新冠肺炎現在情況怎么樣了？推薦Github標星24.7K+的新冠肺炎公開數據集，利用這個數據集，可以用代碼進行簡單地可視化及預測。

推薦新冠肺炎的公開數據集：

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

數據可視化：

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

數據集能做什么？

這個數據集可以做以下分析：

• 全球趨勢

• 國家（地區）增長

• 省份情況

• 美國

• 歐洲

• 亞洲

• 什么時候會收斂？進行預測

簡單演示

新冠肺炎感染人數可視化效果

數據來源

數據來源:

• 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

總結

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本文推薦新冠肺炎的公開數據集，利用這個數據集，可以用代碼進行簡單地可視化及預測。

數據集地址：

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

數據預測代碼：

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

（數據請從數據集地址下載最新）

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總結

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