A Software Carpentry workshop at Northwestern

November 5, 2014

(This article was first published on Thinking inside the box , and kindly contributed to R-bloggers)

On Friday October 31, 2014, and Saturday November 1, 2014, around thirty-five graduate students and faculty members attended a Software Carpentry workshop. Attendees came primarily from the Economics department and the Kellogg School of Management, which was also the host and sponsor providing an excellent venue with the Allen Center on the (main) Evanston campus of Northwestern University.

The focus of the two-day workshop was an introduction, and practical initiation, to working effectively at the shell, getting introduced and familiar with the git revision control system, as well as a thorough introduction to working and programming in R—from the basics all the way to advanced graphing as well as creating reproducible research documents.

The idea of the workshop had come out of discussion during our R/Finance 2014 conference. Bob McDonald of Northwestern, one of this year’s keynote speakers, and I were discussing various topic related to open source and good programming practice — as well as the lack of a thorough introduction to either for graduate students and researcher. And once I mentioned and explained Software Carpentry, Bob was rather intrigued. And just a few months later we were hosting a workshop (along with outstanding support from Jackie Milhans from Research Computing at Northwestern).

We were extremely fortunate in that Karthik Ram and Ramnath Vaidyanathan were able to come to Chicago and act as lead instructors, giving me an opportunity to get my feet wet. The workshop began with a session on shell and automation, which was followed by three session focusing on R: a core introduction, a session focused on function, and to end the day, a session on the split-apply-combine approach to data transformation and analysis.

The second day started with two concentrated session on git and the git workflow. In the afternoon, one session on visualization with R as well as a capstone-alike session on reproducible research rounded out the second day.

Things that worked

The experience of the instructors showed, as the material was presented and an effective manner. The selection of topics, as well as the pace were seen by most students to be appropriate and just right. Karthik and Ramnath both did an outstanding job.

No students experienced any real difficulties installing software, or using the supplied information. Participants were roughly split between Windows and OS X laptops, and had generally no problem with bash, git, or R via RStudio.

The overall Software Carpentry setup, the lesson layout, the focus on hands-on exercises along with instruction, the use of the electronic noteboard provided by etherpad and, of course, the tried-and-tested material worked very well.

Things that could have worked better

Even more breaks for exercises could have been added. Students had difficulty staying on pace in some of the exercise: once someone fell behind even for a small error (maybe a typo) it was sometimes hard to catch up. That is a general problem for hands-on classes. I feel I could have done better with the scope of my two session.

Even more cohesion among the topics could have been achieved via a single continually used example dataset and analysis.


Robert McDonald from Kellogg, and Jackie Milhans from Research Computing IT, were superb hosts and organizers. Their help in preparing for the workshop was tremendous, and the pick of venue was excellent, and allowed for a stress-free two days of classes. We could not have done this without Karthik and Ramnath, so a very big Thank You to both of them. Last but not least the Software Carpentry ‘head office’ was always ready to help Bob, Jackie and myself during the earlier planning stage, so another big Thank You! to Greg and Arliss.

To leave a comment for the author, please follow the link and comment on their blog: Thinking inside the box .

R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...

If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Comments are closed.

Search R-bloggers


Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)