[R] a function more appropriate than 'sapply'?
bhh at xs4all.nl
Sat Jan 26 21:23:12 CET 2013
On 26-01-2013, at 21:09, Uwe Ligges <ligges at statistik.tu-dortmund.de> wrote:
> On 26.01.2013 20:46, Berend Hasselman wrote:
>> On 26-01-2013, at 19:43, emorway <emorway at usgs.gov> wrote:
>>> I'm wondering if I need to use a function other than sapply as the following
>>> line of code runs indefinitely (or > 30 min so far) and uses up all 16Gb of
>>> memory on my machine for what seems like a very small dataset (data attached
>>> in a txt file wells.txt
>>> <http://r.789695.n4.nabble.com/file/n4656723/wells.txt> ). The R code is:
>>> The 2nd line of R code above gets bogged down and takes all my RAM with it:
>>> I'm simply trying to extract all of the lines of data that have a single "_"
>>> in the first column and place them into a dataset called "wells2". If that
>>> were to work, I then want to extract the lines of data that have two "_" and
>>> put them into a separate dataset, say "wells3". Is there a better way to do
>>> this than the one-liner above?
>> Read your file with
>> wells<-read.table("wells.txt",col.names=c("name","plc_hldr"), stringsAsFactors=FALSE)
>> Remove all non underscores with
>> w.sub <- gsub("[^_]+","",wells[,1])
>> then select elements of w.sub with 2 underscores and a single underscore with
>> u.2 <- which(w.sub=="__")
>> u.1 <- which(w.sub=="_")
>> and use u.1 and u.2 to select the appropriate rows of wells.
> With grep:
> wells1 <- wells[grep("^[^\\_]*_[^\\_]*$", wells[,1]),]
> wells2 <- wells[grep("^[^\\_]*_[^\\_]*_[^\\_]*$", wells[,1]),]
Are the \\ necessary?
I tried without the \\ and that gives identical results.
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