Aarhus University

Mar 5-7, 2018

9:00 am - 4:00 pm

Instructors: Dan Mønster, Kristian Tylén

Helpers: N/A

Software Carpentry Workshop at Moesgaard, Aarhus University.

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 how to write modular code and best practices for using R for data analysis and visualization. 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: Moesgård Allé 15 (room 4240-302 and 4206-121). Get directions with OpenStreetMap or Google Maps.

When: Mar 5-7, 2018. 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). They are also required to abide by Software Carpentry's Code of Conduct.

Accessibility: We are committed to making this workshop accessible to everybody.

Contact: Please email lovschal@cas.au.dk , danm@econ.au.dk or kristian@cc.au.dk for more information.

Sign-up: Please send an e-mail to Mette Løvschal to sign up.



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

Pre-workshop Survey

Post-workshop Survey

Monday 5 March (room 4240-302)

09:00 Introduction to R and R Studio
10:30 Coffee
10:45 Managing projects
12:00 Lunch break
13:00 Working with data
14:30 Coffee
14:45 Subsetting data
16:00 END

Tuesday 6 March (room 4206-121)

09:00 Control flow
10:30 Coffee
10:45 Visualizing data
12:00 Lunch break
13:00 Modular programming
14:30 Coffee
14:45 Manipulating data
16:00 END

Wednesday 7 March (room 4206-121)

09:00 Data frame manipulation
10:30 Coffee
10:45 Integrating software and reports
11:30 Writing good software
12:00 END

We will use this collaborative document for chatting, taking notes, and sharing URLs and bits of code.


R for Reproducible Scientific Analysis

  • Introduction to R and RStudio
  • Data Structures
  • Reading and manipulating data
  • Loops and conditionals
  • Functions in R
  • Creating plots
  • Writing data
  • Producing reports with knitr
  • Reference...


To participate in this Software Carpentry workshop, you will need access to the software described below. 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.

The gapminder data can be downloaded here.


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


Video Tutorial

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

Install R by downloading and running this .pkg file from CRAN. Also, please install the RStudio IDE.


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.