This intensive 2-day Software Carpentry bootcamp will introduce attendees to a range of computing skills aimed at making them more productive and efficient in their work. A substantial focus of the workshop will be on improving programming skills in R, but will also include topics on version control, using the shell, and reproducible research. Short tutorials will alternate with hands-on practical exercises. Participants will be encouraged both to help one another, and to apply what they have learned to their own research problems during and between sessions.
Instructors: Diego Barneche, Gavin Simpson, Ross Dickson
Helpers: Daniel Morrison
Who: The bootcamp is targeted at postgraduate students and other researchers in Biology and Oceanography. Please note that this is not an introductory R course and in order to get the most out of the bootcamp, attendees should have at least a basic knowledge of programming in R. However, please don't let that scare you off - if you'd like to attend but have never used R before, working through the online material covered in 'Day 1' of the NiceR code 'Introduction to R' will get you up to speed!
Requirements: Participants must bring a laptop with a few specific software packages installed (listed below).
Contact: Please mail firstname.lastname@example.org for more information.
|08:00 - 08:30||Introduction + Rstudio|
|08:30 - 11:00||Functions|
|13:00 - 14:00||Project setup|
|14:00 - 15:30||Repeating things (plyr)|
|15:30 - 15:45||Tea break|
|15:45 - 17:00||Repeating things (loops)|
|09:00 - 10:00||Testing|
|10:00 - 11:00||Basic shell scripting|
|13:00 - 15:00||Version control with git|
|15:00 - 15:15||Tea break|
|15:15 - 16:00||Git workflows|
|16:00 - 17:00||Reproducible research with knitr|
To participate in a Software Carpentry bootcamp, you will need working copies of the software described below. Please make sure to install everything (or at least to download the installers) before the start of your bootcamp.
When you're writing code, it's nice to have a text editor that is optimized for writing code, with features like automatic color-coding of key words. The default text editor on Mac OS X and Linux is usually set to Vim, which is not famous for being intuitive. if you accidentally find yourself stuck in it, try typing the escape key, followed by ':q!' (colon, lower-case 'q', exclamation mark), then hitting Return to return to the shell.
Bash is a commonly-used shell. Using a shell gives you more power to do more tasks more quickly with your computer.
Git is a state-of-the-art version control system. It lets you track who made changes to what when and has options for easily updating a shared or public version of your code on github.com.
R is a programming language that is especially powerful for data exploration, visualization, and statistical analysis. To interact with R, we will use RStudio, an interactive development environment (IDE).
Install Git for Windows by download and running the installer. This will provide you with both Git and Bash in the Git Bash program.
Notepad++ is a popular free code editor for Windows. Be aware that you must add its installation directory to your system path in order to launch it from the command line (or have other tools like Git launch it for you). Please ask your instructor to help you do this.
The default shell in all versions of Mac OS X is bash,
so no need to install anything. You access bash from
the Terminal (found
/Applications/Utilities). You may want
to keep Terminal in your dock for this workshop.
Install Git for Mac by downloading and running the installer. For older versions of OS X (10.5-10.7) use the most recent available installer available here. Use the Leopard installer for 10.5 and the Snow Leopard installer for 10.6-10.7.
The default shell is usually
but if your machine is set up differently
you can run it by opening a terminal and typing
There is no need to install anything.
If Git is not already available on your machine you can try
to install it via your distro's package manager
Kate is one option for Linux users.
In a pinch, you can use
which should be pre-installed.
You can download the binary files for your distribution
from CRAN. Or
you can use your package manager, e.g. for Debian/Ubuntu
apt-get install r-base or
yum install R.
Also, please install the