These posts are general blog posts on R and they are also published on R bloggers. Consequently, the language is in English.
The UEFA EURO 2020 tournament is over and we are ready to announce the winner of the tournament prediction competition. On June 2nd, football enthusiasts and data analysts were encouraged to provide predictions of the tournament results. And we already know who did the best! (In fact we’ve known for some time since the outcome of the last couple of matches did not change who did best). And the prediction winner is
The UEFA EURO 2020 tournament is finally starting and 24 teams are competing to be able to raise the trophy on July 11th. While the individual games are exciting and interesting by themselves, they are no match for the competition as to which data analyst will provide the best prediction of the tournament results. And you are hereby invited to participate!
The year 2020 marks the 20th anniversary of the release of R version 1.0.0! To celebrate this, we are inviting the community of R users and developers for a two-day celebRation workshop/mini-conference on February 28-29th 2020 in Copenhagen.
Debates about vaccines are ongoing in many countries and the debate has reblossomed in Denmark after we’ve had five recent occurrences of measels. While that is nothing compared to the measles outbreak currently ravaging Japan it is still enough to worry the health authorities that it might result in an epidemic. Here we’ll use Shiny to create an app that shows the impact of contagious diseases and the influence of vaccination. Wrapping the computations in a Shiny app will allow non-R-users to tweak the input parameters themselves and observe the consequences of an outbreak. Hopefully, this can lead to a more informed discussion about vaccination.
Predicting the outcome of the different teams in the FIFA World Cup has been of great interest to the general public, and predicting the outcome has also attracted quite some attention in the R community. The World Cup has ended and by now, everyone knows that France managed to take home the trophy that slipped through their fingers when they hosted the UEFA Euro 2016 championship. But who won the more important competition of predicting the outcome?
A codebook is a technical document that provides an
overview of and information about the variables in a dataset. The
codebook ensures that the statistician has the complete background
information necessary to undertake the analysis, and a codebook
documents the data to make sure that the data is well understood and
reusable in the future. Here we will show how to create codebooks in R
using the dataMaid packages.
As data analysts, we all have tasks that we enjoy more than others. Some like the exploratory analysis steps, some like statistical computing, while others enjoy visualizing and communicating the results of their analyses. But we have yet to meet a data analyst that is passionate about data cleaning, even though everyone is very much aware of the importance of a thorough, well-documented data cleaning. This first step of virtually any data analysis process is often unavoidable and key for smooth sailing through the rest of the data analysis.