On 12/11/14 09:21, Peter Simons wrote:
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.
Ah, great then. My impression was formed after listening to this FLOSS weekly episode: http://twit.tv/show/floss-weekly/306 (starting from 33:55).
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.
That doesn't match my experience. Maybe it's just me and my unwillingness and write C-like code that traverses arrays by indexes (I know most scientists don't have a problem with that), but I found it hard to express data transformations and queries functionally in R.
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?
This was a while ago, and I don't remember what solution I picked up eventually. Of course I could just write a for-loop to populate an array, but I hadn't found anything that matches the simplicity and clarity of the line above. How would you write it in R? Roman