Research School for Socio-Economic and
Natural Sciences of the Environment
Research School for Socio-Economic and
Natural Sciences of the Environment

R Users Discussion Group Meeting

Date: 13 December 2019
Time: 15:50 - 17:20
Location: Wageningen Campus, Forum Building, C0211

The R Users Meeting is a monthly meeting for people working with R. PhD and MSc students, as well as staff members, both beginners as well as advanced R users are welcome. The meeting offers an opportunity to help each other with specific questions and exchange ideas. In each meeting a specific topic is discussed by demonstrating and discussing examples of R functions and example data. The second part of each meeting is reserved for short questions on R codes and offers opportunity to get advice on your R code and how to fix or improve it. The meetings are hands-on, so please try to run the code and prepare your questions prior to the meeting. Also, bring your laptop to the meeting. New group members are welcome and are kindly asked to contact us.

There is also an online meeting place where the participants can share problems and experiences additional to the monthly meeings: In the text you will find links to a few R scripts, R learning resources, a schedule of upcoming meetings, and the issue section where you can discuss your problems. You can visit everything; however to post or answer an issue, you have to create an account and log in.

For more information contact the R user group organizers (

Upcoming meetings

13 December 2019: The future of parallel programming with R
Last time we tested a few parallel processing techniques that are very similar in nature (parallel, foreach). In this presentation we'll take a different approach and test how far can a promise take us. We will discuss advantages and disadvantages of different parallelization techniques and particular situations where they can shine.

Past meetings

  • 26 November 2019: An introduction to parallel programming with R: snow(fall), parallel, foreach
    Nowadays nearly every computer processor contains multiple cores (even smartphone processors do) that allow to boost processing performance and let them keep up with Moore’s Law ( However, standard evaluation in R makes use of 1 core only. In this talk we want to give an introduction how you can use the whole power of your machine. First, we will present basic principles of functional programming, which is a useful concept to ease parallel computation. Then we will show how these principles can be used to distribute tasks among the CPUs of your machine. Finally, we also want to give pros and cons for parallel computation. We will cover how to do parallel computation (on a single machine) with the snowfall, parallel and foreach packages.
  • 26 June 2019: RKWard: an alternative to RStudio, or what we can do with R without writing any code While RStudio is the most popular R integrated development environment (IDE), it is far from the only one. In this meeting, we will discuss alternative IDEs and GUIs with the example of RKWard, a beginner-friendly yet powerful R graphical user interface. We will showcase how R can be used by people who are either completely new to R or are used to other statistical packages such as SPSS. In addition, we will cover why such an IDE is useful also for power users of R.
  • 22 May 2019: Back to basics In this meeting we will be going back to the basics and talk about how and when to use conditionals, switch/case, loops, and the apply function family. We will also cover the `foreach` and `iter` packages as a prelude to the next session.
  • 15 April 2019: Efficient data.frame manipulation with dplyr and data.table In this meeting we will discuss the dplyr and data.table packages for manipulation of (big) data.frames. The basic ideas of both packages will be explained and how they differ from base R. Also a quick comparison between the two will be made, their (dis)advantages, in case you want to switch or decide to use any of the two. With examples of course.
  • 27 February 2019: GGPLOT2 In our first meeting after new year, we will discuss visualisation with the ggplot2 package. We will show an overview of how ggplot2 logic works, how to convert your data into a format that works well with ggplot2, how to make beautiful and interactive plots, and also how to visualise information on a spatial map. Several companion packages to ggplot2 will also be introduced. We will conclude with a discussion about when to use ggplot2 and share our experiences with it.
  • 22 November 2018: Getting Git running In this hands-on workshop, you are invited to bring your laptops to set up Git in practice! We will go over the basics of how to start using Git: installing it on your laptop, linking it with your GitHub/GitLab account, making a new Git repository, adding files to it, making commits and uploading them to GitHub/GitLab. In class, we will be following this tutorial: It might be useful to have a look at the theory part before -- however, we will do the exercises in the meeting.
  • 23 October 2018: How git you do this summer? This is an interactive session where we look at how people use git and GitHub/GitLab in their research! So come along and show us whatever your experience is. If you just tried it out and which features you found helpful. If you didn’t try git yet, this is the chance to have a look what could be in for you. We from the R-Users organiser team also have git-experience, so there will definitely by something to see.
    Git in a few lines:
  • 6 June 2018: Introduction to Git for R projects. Git is a popular open source version control system that enables collaborating on code development. Git hosting platforms like GitHub and GitLab offer a number of tools that make project management easier. In this session, the background and concept of Git and GitHub/GitLab will be introduced, with examples of the ways you can use it in practice for efficient project management and collaboration. R package development will be used as a case study. Presented by: Dainius Masiliunas, Laboratory of Geo-information Science and Remote Sensing.
  • 19 April 2018: Data Types and Data Modelling in R. This session will recall basic R data types first. Later, we will have a look at how you can efficiently model your data in R (represent your bits and bytes as concise entities).
  • 14 March 2018: performing computationally reproducible research with R, loosely based on the books Reproducible Research with R and R Studio, Gandrud, 2015, and The Practice of Reproducible Research: Case Studies and Lessons from the Data-Intensive Sciences, Kitzes et al. 2017. We will touch upon technical solutions (such as exporting R-scripts and results, integrated, to html or pdf documents), but also discuss points of awareness, and practical considerations and priorities in the daily practice of PhDs and other researchers. We invite you to share your ideas and experiences during this session.
  • 14 February 2018: Joost van Heerwaarden: Loops, functions and apply
  • 16 January 2018: Johannes Kruisselbrink (Biometris): C++ code from R using Rcpp
  • 5 December 2017: R-Users Sinterklaas meeting.
    We will do some coding exercises to learn from each other.
    Homework: Prepare 1 basic (level Fibonacci numbers) and 1 advanced (level quick-sort algorithm) coding exercise. They can be very specific to your field, but you need to be able to explain them, so everybody can solve them. You can also include plotting (e.g. how to plot a dataset in a certain way).
    Reward: We will provide some Kruidnoten and drinks!
  • 7 November 2017: Making presentations in Rstudio: my (good/bad) experiences with IOSLIDES.
  • 3 October 2017: The Good, the Bad and the Ugly
  • 14 June 2017
  • 17 May 2017: An introduction to parallel programming with R12 April 2017: ggplot2 and other tools
  • 15 February 2017: Topic: not sure yet, but perhaps basic descriptive statistics in R. (CANCELLED)
  • 25 January 2017: Benjamin Brede (PhD candidate, Laboratory of Geo-information Science and Remote Sensing): "Raster processing with R: Reading, writing, manipulating, analyzing and modeling of gridded spatial data."
    It concerns the R-packages ‘raster’ and ‘gdalUtils’; Level: advanced
  • 14 December 2016: Ron Wehrens (Biometris) will talk about the Lattice plotting system and about good plotting habits. So: plotting in R! Level indication: somewhere between basic and intermediate
  • 16 November 2016: Vincent Garin, PhD candidate at Biometris: “Data structure and good practises in R”

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