Thank you all for your suggestions! I must say I am amazed by the number of
people who consider helping out another! Fells like it was a good idea to
start using R - back when I was still using Perl for such tasks, I'd been
happy to have this kind of support!
@ Gheorghe Postelnicu: Unfortunately,
2 ideas (haven't tried them):
1. if your data is in a data frame, did you try using the by function?
Seems it would do the grouping for you.
2. Since you mention the cpu cores, you could use libraries like foreach
and %dopar% or mcapply.
I would try 1. and see if it provides a sufficient speed-u
On 8 Dec 2014, at 21:21, apeshifter wrote:
> The last relic of the afore-mentioned for-loop that goes through all the
> word pairs and tries to calculate some statistics on them is the following
> line of code:
>> typefreq.after1[i]<-length(unique(word2[which(word1==word1[i])]))
> (where word1 a
The data.table package might be of use to you, but lacking a reproducible
example [1] I think I will leave figuring out just how to you.
Being on Nabble you may not be able to see the footer appended to every
message on this MAILING LIST. For your benefit, here it is:
* R-help@r-project.org m
Dear all,
for the past two weeks, I've been working on a script to retrieve word pairs
and calculate some of their statistics using R. Everything seemed to work
fine until I switched from a small test dataset to the 'real thing' and
noticed what a runtime monster I had devised!
I could reduce p
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