Creates automated charts in Datawrapper for the spread of Covid-19.
- You will need a Datawrapper-API-Key (which is set as a constant in
main.R
). You can find more on that here.
You can run this scripts from your machine, or put it on a server which has R and all required packages installed (check out the needs-call in main.R
to find them).
-
main.R
contains all constants that need to be set beforehand. In the beginning of each function there is achart_id
which needs to be set to the correct Datawrapper-ID. This is quite a manual process but in ensures that there is always a correct mapping between script and chart. -
You might want to set up a Cronjob to run every hour e.g.:
0 * * * * Rscript [PATH TO THE MAIN.R]/main.R >> log.txt
(yes, there are a couple of logs written - just in case).
We've created a dashboard for our website that shows the current case-count and calculated statistics on the doubling-speed and a trend indicator. You can find the live chart here.
Sources:
-
Johns-Hopkins-Dashboard-Data - which is updated more often than the Github (https://www.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6)
-
Worldometers (https://www.worldometers.info/coronavirus/)
We currently only show maps of the German Federal States and Bavarian Counties. We deprecated a map of the whole world when there had been cases everywhere - it is now shown as a Datawrapper table with bar charts (see below).
Both scripts are called in get_geographical_data.R
.
You can find the live map here.
Source:
- our own research (combining sources like the RKI and state-level authorities in a Google Sheet)
You can find the live map here.
This script maps the cases in Bavarian counties. It combines them with a translation table beforehand, to match county name with Lat and Lon-coordinates. Unfortunately the data source changes the names wildly each day (sometimes with a "Land"- or "Stadt"-suffix, sometimes without). So it needs a lot of manual correction.
Source:
- Bayerisches Landesamt für Gesundheit (https://www.lgl.bayern.de/gesundheit/infektionsschutz/infektionskrankheiten_a_z/coronavirus/karte_coronavirus/index.htm)
Showing the cases in China and Worldwide over time. You can find the live chart here.
Sources:
-
John Hopkins CSSE / Github-data (https://github.com/CSSEGISandData/COVID-19/raw/master/csse_covid_19_data/csse_covid_19_time_series/time_series_19-covid-Confirmed.csv)
-
For Germany: our own data
Showing the cases, deaths and cured cum-sums over time. You can find the live chart here.
Source:
- John Hopkins CSSE / Github-data (https://github.com/CSSEGISandData/COVID-19/raw/master/csse_covid_19_data/csse_covid_19_time_series/)
Showing the cases and deaths for each country in a sorted table. You can find the live chart here.
Sources:
-
Johns-Hopkins-Dashboard-Data - which is updated more often than the Github (https://www.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6)
-
Worldometers (https://www.worldometers.info/coronavirus/)
-
For Germany: our own research
table_cases_deaths_recovered.R
Showing the cases, recovered and deaths only for China, Italy, Germany and the World right now in a table. You can find the live chart here.
Source:
- John Hopkins CSSE / Github-data (https://github.com/CSSEGISandData/COVID-19/raw/master/csse_covid_19_data/csse_covid_19_time_series/)
Trys to give a hint which country might be undertested, when deathrates (deaths/cases) exceed prior estimates heavily in some place. You can find the live chart here.
Source:
- John Hopkins CSSE / Github-data (https://github.com/CSSEGISandData/COVID-19/raw/master/csse_covid_19_data/csse_covid_19_time_series/)
Comparing cases of the both. It was used often in the beginning, but right now other aspects emerged. You can find the live chart here.
Sources:
-
John Hopkins CSSE / Github-data (https://github.com/CSSEGISandData/COVID-19/raw/master/csse_covid_19_data/csse_covid_19_time_series/)
-
WHO-data on SARS (https://www.who.int/csr/sars/country/en/)
-
Benedict Witzenberger ([email protected])
-
Christian Endt ([email protected])