Hi Roman,
With Haskell you don't have to load the whole data set into memory, as Michael shows. With R, on the other hand, you do.
Can you please point me to a reference to back that claim up? I'll offer [1] and [2] as a pretty good indications that you may not be entirely right about this.
Besides, if you're not an R expert, and if the analysis you want to do is not readily available, it may be quite a pain to implement in R.
Actually, implementing sophisticated queries in R is quite easy because the language was specifically designed for that kind of thing. If you have no experience in neither R nor Haskell, then learning R is *far* easier than learning Haskell is because it doesn't aim to be a powerful general-purpose programming language. It aims to be a powerful language for data analysis. Now, one *could* write a DSL in Haskell, of course, that matches R features and accomplishes data analysis tasks in a similarly convenient syntax, etc. But unfortunately no such library exists, and writing one is not trivial task.
I still don't know an acceptable way to write something like zipWith f (tail vec) vec in R.
Why would that be any trouble? What kind of solutions did you find and in what way were they unacceptable? Best regards, Peter [1] http://cran.r-project.org/web/packages/ff/index.html [2] http://cran.r-project.org/web/packages/bigmemory/index.html