Lær hvordan du automatisk kan trække data fra online kilder ved hjælp af R. Vi gennemgår de grundlæggende principper i de to typiske måder at lade dit R script tale sammen med online databaser, bl.a. Danmarks Statistik.
Kurset ligger i forlængelse af vores begynderkurser. På kurset har du således mulighed for at anvende de ting, du allerede har lært, samtidig med at du udbygger din viden og dine færdigheder i R. Derfor kan en god forberedelse være at deltage i et vores begynderkurser
Det forudsættes at du har installeret R og Positron/RStudio før kurset, sådan at vi kan nå så langt som muligt på kurset. Du kan finde hjælp til at installere R og Positron/RStudio her.
Kurset er som udgangspunkt på dansk, men hvis en eller flere deltagere ønsker det, afholdes det på engelsk. Learn how to automatically extract data from online sources using R. We cover the basic principles in the two major ways of getting your R script to communicate with online databases, including Statistics Denmark.
The course builds on our beginner courses. You will therefore have the opportunity to apply what you have already learned while expanding your knowledge and skills in R. As preparation, it may be beneficial to attend one of our beginner courses.
It is assumed that you have installed R and Positron/RStudio before the course so that we can make as much progress as possible. You can find help with installing R and Positron/RStudio here.
The course is primarily conducted in Danish, but if one or more participants prefer, it can be delivered in English.
Related LibGuide: Data Lab by Christian Knudsen
Please note this is an online event. The online event URL will be sent to you in an email confirming your registration.
* Required Field
Registration only possible for emails from these domains - ku.dk, @kb.dk, @itu.dk, au.dk, aau.dk, sdu.dk, @ruc.dk, e.g. xyz123@alumni.ku.dk
We will send confirmation of registration in your email. If you do not receive an e-mail, please contact the course organiser.
Registration is required. There are 21 seats available.
Cand.Polyt.
Specialkonsulent
Københavns Universitetsbibliotek, KUB Datalab
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