Yeah - for the small data sets, Ruby or Python is often easier easier to use to whip a data set into a form that can be simply slurped into R as a dataframe.
Has to be said I cheated a bit on the Coursera course, I used Ruby to clean up some of the data. Seemed a lot easier, and it's a lot more likely I'd use some kind of scripting language (be it Perl, Ruby, Grep, ...) to do a first clean up than head directly to R to do the job.
With pandas / statsmodels / patsy, it's getting easier to stick with python for everything.