"One of the reasons we are using a general-purpose language rather than a stats language like R is that for many projects the "hard" part is preparing the data, not doing the analysis."
quote from week 2 of the accompanying lecture notes:
I find preparing the data is actually easier in R than in something like python, but that certainly depends on type and amount of data. And, of course, each to their own..
quote from week 2 of the accompanying lecture notes:
https://sites.google.com/site/thinkstats2010b/lecture-notes/...