COVID-19 data -1-

With the current corona virus outbreak reliable data about occurrences is important.

In response to this ongoing public health emergency, the Johns Hopkins University, developed an interactive web-based dashboard (static snapshot shown above) hosted by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University, to visualize and track reported cases in real-time. The dashboard, first shared publicly on January 22, illustrates the location and number of confirmed COVID-19 cases, deaths and recoveries for all affected countries. It was developed to provide researchers, public health authorities and the general public with a user-friendly tool to track the outbreak as it unfolds. Further, all the data collected and displayed is made freely available, initially as google sheets, now in a GitHub repository, along with the feature layers of the dashboard, which are now included in the ESRI Living Atlas.
This is the data repository for the 2019 Novel Coronavirus Visual Dashboard operated by the Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE). Also, Supported by ESRI Living Atlas Team and the Johns Hopkins University Applied Physics Lab (JHU APL).

The website and its contents herein, including all data, mapping, and analysis (“Website”), copyright 2020 Johns Hopkins University, all rights reserved, is provided to the public strictly for educational and academic research purposes. The Website relies upon publicly available data from multiple sources, that do not always agree. The Johns Hopkins University hereby disclaims any and all representations and warranties with respect to the Website, including accuracy, fitness for use, and merchantability. Reliance on the Website for medical guidance or use of the Website in commerce is strictly prohibited.

The data on github is available as .csv files. In this blog post i will explain how his data can be imported easy in a google spreadsheet. The data than can be used to create your own graphs or make special calculations.
In github you can view the *.csv data and the button [raw] opens a page with the raw csv file. Using the URL in the google spreadsheet function fills the spreadsheet with the github data.
 Currently there are 3 important time-series data files:

https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_19-covid-Confirmed.csv

https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_19-covid-Deaths.csv

https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_19-covid-Recovered.csv

A simple recipe to get this data in your own google spreadsheet:

Create a spreadsheet with 3 pages.

Rename these pages to Confirmed, Deaths and Recovered.

Place cel A1 of each of this pages the link to the corresponding raw data. (See above)

Put in each of this three pages in another cell (e.g. in A3  this formula:

=IMPORTDATA(A1)

Each time this function gets executed it will grab the data from github.

So when the github data gets updated new data will appear automatic in your spreadsheet and can be used to create custom graphs, do custom calculations or use a special script in your spreadsheet.

This also uses some bandwidth an gives addition load. If you want to present this data give credits to Johns Hopkins University, respect their use policy and for a high traffic website better do not use this data direct as shown in this example. Grab periodical fresh data and use a local copy (e.g. with wget command in a cronjob.)

(Update 10 March 2020 : I added -1- in the title and added the COVID-19 label as i decided to do another post about COVID-19 data  perhaps more posts will follow. )


(Important (27 March 2020) see also https://blog.jeronimus.net/2020/03/covid-19-data-3.html as files in Github changed! )