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University of Melbourne

Feb 16-17, 2015

9:00 am - 5:00 pm

Instructors: Scott Ritchie

Helpers: Areej Alsheikh-Hussain, Noel Faux, Pip Griffin, Andrew Lonsdale, Jack Simpson, Mike Sumner

Research Bazaar - R Stream

Participants enrolled in the "Programming and Data Analysis in R" stream at the Research Bazaar conference will attend a Software Carpentry workshop on the first two days. The mission of the Software Carpentry project is to help researchers be more productive by teaching them basic computing skills. Researchers often spend much of their time wrestling with software, but most are self-taught programmers. As a result, they spend hours doing things that should take minutes, reinvent a lot of wheels, and still don't know if their results are reliable. To tackle this problem, Software Carpentry runs two-day workshops at hundreds of sites around the world. These hands-on workshops cover basic concepts and tools, including program design, version control, data management, and task automation. Participants are be encouraged to help one another and to apply what they have learned to their own research problems.

Who: The workshop is restricted to Research Bazaar attendees who signed up for the "Programming and Data Analysis with R" stream.

Where: Room 202, Old Metallurgy Building (map).

Requirements: Participants are asked to bring their laptop. They will be given access to the Data Intensive Tools for the Cloud (DIT4C) environment on the NeCTAR Research Cloud, so it's critical that this laptop is able to connect to either the UniWireless or Eduroam wifi networks (see wifi and DIT4C login instructions below). The DIT4C environment has all the required software installed, however there are software installation instructions below for participants who would like to install the software on their own laptop. Also note that participants are required to abide by Software Carpentry's Code of Conduct.

Contact: Please mail for more information.


The class schedule will be released closer to the event. As well as attending this Software Carpentry workshop, people who signed up for the "Programming and Data Analysis with R" stream will have the opportunity to attend a number of other elective classes at ResBaz.

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


The Unix Shell

Version Control with Git

  • Creating a repository
  • Recording changes to files: add, commit, ...
  • Viewing changes: status, diff, ...
  • Ignoring files
  • Working on the web: clone, pull, push, ...
  • Resolving conflicts
  • Open licenses
  • Where to host work, and why
  • Lesson notes...
  • Reference card...
  • Discussion...

R for reproducible scientific analysis

  • Introduction to RStudio and RStudio Projects
  • Introduction to R
  • Reading and writing data
  • Seeking help
  • Data structures
  • Subsetting data
  • Vectorisation
  • Control flow
  • Functions
  • Apply and task repitition
  • Plotting
  • Lesson notes...
  • Reference card...
  • Discussion...



Prior to the workshop, University of Melbourne staff/students should ensure that their laptop can connect to UniWireless. Instructions on how to do this and where to get assistance can be found here. Attendees from other Australian universities should find out (from the IT website of their home institution) how to connect to the Eduroam wireless network.

Create a DIT4C Account

During the week prior to the workshop, one of the instructors will email you the compute node name and access code you'll need for the Data Intensive Tools for the Cloud (DIT4C) environment that is hosted on the NeCTAR Research Cloud. Once you've got that name and code, navigate to the DIT4C homepage and follow these instructions:

  1. Click the "login" button and proceed to login. You can use your institution username and password if you're at an Australian university, otherwise use your GitHub credentials (everyone creates a GitHub account during the Git lessons anyway, so you'll just be getting in early).
  2. Go to the "compute nodes" tab and click "claim compute node access".
  3. From the drop down menu, select the name of the compute node that the instructor emailed to you and enter the corresponding access code.
  4. Go to the "containers" tab and add a new container named after yourself (e.g. johnsmith). The reason for this is that container names are unique (i.e. you can't have the same container name as anyone else in the room). Select an "RStudio" image from the drop down menu and then hit the create button.
  5. When the container is "on", its name should turn blue and you can click on it to launch your environment in a new tab of your browser.
  6. Once you're finished for the day, simply close all the extra tabs that have opened up and turn your container "off". When you come back tomorrow, simply switch back to the 'on' position to continue using that container.

(Optional) Software Installation

The DIT4C environment comes with all the required software pre-installed, however if you would like to install the software on your own computer (either before or after the workshop), here are the instructions to do so.

Text Editor

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.


nano is the editor installed by the Software Carpentry Installer, it is a basic editor integrated into the lesson material.

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.

Mac OS X

We recommend Text Wrangler or Sublime Text. In a pinch, you can use nano, which should be pre-installed.


Kate is one option for Linux users. In a pinch, you can use nano, which should be pre-installed.

The Bash Shell

Bash is a commonly-used shell that gives you the power to do simple tasks more quickly.


Install Git for Windows by download and running the installer. This will provide you with both Git and Bash in the Git Bash program.

Software Carpentry Installer

This installer requires an active internet connection.

After installing Python and Git Bash:

  • Download the installer.
  • If the file opens directly in the browser select File→Save Page As to download it to your computer.
  • Double click on the file to run it.
Mac OS X

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 in /Applications/Utilities). You may want to keep Terminal in your dock for this workshop.


The default shell is usually bash, but if your machine is set up differently you can run it by opening a terminal and typing bash. There is no need to install anything.


Git is a version control system that lets you track who made changes to what when and has options for easily updating a shared or public version of your code on


Git should be installed on your computer as part of your Bash install (described above).

Mac OS X

For OS X 10.8 and higher, install Git for Mac by downloading and running the installer. After installing Git, there will not be anything in your /Applications folder, as Git is a command line program. For older versions of OS X (10.5-10.7) use the most recent available installer for your OS available here. Use the Leopard installer for 10.5 and the Snow Leopard installer for 10.6-10.7.


If Git is not already available on your machine you can try to install it via your distro's package manager. For Debian/Ubuntu run sudo apt-get install git and for Fedora run sudo yum install git.


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


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

Mac OS X

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 yum install R). Also, please install the RStudio IDE.