R for Reproducible Scientific Analysis

University of Oslo

May 31, 2022

09:00 - 16:00

Instructors: Claudia Barth, Agata Bochynska

Helpers: Mohamed Abdelhalim, Chi Zhang, Espen Rosenquist

General Information

Software Carpentry aims to help researchers get their work done in less time and with less pain by teaching them basic research computing skills. This hands-on workshop will cover basic concepts and tools, including program design, version control, data management, and task automation. Participants will be encouraged to help one another and to apply what they have learned to their own research problems.

For more information on what we teach and why, please see our paper "Best Practices for Scientific Computing".

Who: The course is aimed at graduate students and other researchers. You don't need to have any previous knowledge of the tools that will be presented at the workshop.

Where: Seminar room Perl, Ole-Johan Dahls hus, Gaustadalléen 23B, 0373 Oslo. Get directions with OpenStreetMap or Google Maps.

When: May 31, 2022. Add to your Google Calendar.

Requirements: Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on. They should have a few specific software packages installed (listed below).

Accessibility: We are committed to making this workshop accessible to everybody. The workshop organizers have checked that:

Materials will be provided in advance of the workshop and large-print handouts are available if needed by notifying the organizers in advance. If we can help making learning easier for you (e.g. sign-language interpreters, lactation facilities) please get in touch (using contact details below) and we will attempt to provide them.

Contact: Please email contact-us@carpentry.uio.no for more information.

Roles: To learn more about the roles at the workshop (who will be doing what), refer to our Workshop FAQ.

Code of Conduct

Everyone who participates in Carpentries activities is required to conform to the Code of Conduct. This document also outlines how to report an incident if needed.


Please be sure to complete these surveys before and after the workshop.

Pre-workshop Survey

Post-workshop Survey


Before Pre-workshop survey
09:00 Introduction to R and R Studio
09:45 Data Structures
10:30 Morning break
11:00 Data Frames
12:00 Lunch break
13:00 Data visualization with {ggplot2}
14:00 Afternoon break
14:30 Manipulating data sets with {dplyr} and {tidyr}
15:30 Practical tips
16:00 END
After Post-workshop Survey


  • Working with R Studio
  • Reading and storing data in different formats
  • Understanding R's data types and structures
  • Working with vectors and data frames
  • Using conditionals to control program flow
  • Plotting data
  • Reference...


To participate in a Software Carpentry workshop, you will need access to the software described below. Please install the software *before* you attend the workshop. If you run into trouble with the installation, contact your local IT department or us. In addition, you will need an up-to-date web browser.

We maintain a list of common issues that occur during installation as a reference for instructors that may be useful on the Configuration Problems and Solutions wiki page.

R and RStudio

R is a programming language that is especially powerful for data exploration, visualization, and statistical analysis. To interact with R, we use RStudio.

We will run most of the course content in RStudio Cloud (in the web browser) but please install R and RStudio on your computer before the course! We will take time to show how to use them. If you are using your private computer this should be no problem. You can find installation instructions for your operating system below.

If you are using a computer that is managed by your IT department, you might need help from an administrator to install the software. On computers from UiO, you may be able to install R and RStudio using an application called *UiO Software Center*. In any case, it would be a good idea to check whether you can install packages in R. See the instructions below.

During the course you also need to create a directory, download text files and move them to that directory. This should be possible on all but the most strictly controlled computers.

Install R by downloading and running this .exe file from CRAN. Also, please install the RStudio IDE. Note that if you have separate user and admin accounts, you should run the installers as administrator (right-click on .exe file and select "Run as administrator" instead of double-clicking). Otherwise problems may occur later, for example when installing R packages.

Video Tutorial

You can download the binary files for your distribution from CRAN. Or you can use your package manager (e.g. for Debian/Ubuntu run sudo apt-get install r-base and for Fedora run sudo dnf install R). Also, please install the RStudio IDE.

Installing R packages

During the course you will need to install R packages. Packages contain useful programs written by other people. In the course we will use four packages, namely dplyr, tidyr, lubridate, and ggplot2. However, we recommend installing the tidyverse meta-package instead, which contains these four plus many other handy packages.

If you are using a private computer, installing packages should be no problem, but if your computer is managed by your IT department it might be best to try this before the course to avoid troubleshooting during the course. To try to install packages, open RStudio and copy and paste the following command into the console window (look for the blinking cursor):

install.packages("tidyverse"); library(tidyverse); glimpse(mtcars)

The press the Enter (Windows) or Return (MacOS) key to execute the command. R now tries to download and install a bunch of packages on you machine. When the installation is finished, you should see a summary of a data set about cars. If there are problems, contact your IT department or us.