Hi,
May be this helps:
wells<-read.table("wells.txt",header=FALSE,stringsAsFactors=F)
wells2<-wells[-grep(".*\\_.*\\_",wells[,1]),]
head(wells2)
# V1 V2
#1 w7_1 0
#2 w11_1 0
#3 w12_1 0
#4 w13_1 0
#5 w14_1 0
#6 w15_1 0
wellsNew<-wells[grep(".*\\_.*\\_",wells[,1]),]
head(wellsNew)
# V1 V2
#851 99_10_4395 0
#852 99_10_4396 0
#853 99_10_4400 0
#854 99_10_4403 0
#855 99_10_4404 0
#856 99_10_4606 0
nrow(wells)
#[1] 46366
nrow(wells2)
#[1] 38080
nrow(wellsNew)
#[1] 8286
38080+8286
#[1] 46366
A.K.
----- Original Message -----
From: emorway <emor...@usgs.gov>
To: r-help@r-project.org
Cc:
Sent: Saturday, January 26, 2013 1:43 PM
Subject: [R] a function more appropriate than 'sapply'?
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:
wells<-read.table("c:/temp/wells.txt",col.names=c("name","plc_hldr"))
wells2<-wells[sapply(wells[,1],function(x)length(strsplit(as.character(x),
"_")[[1]])==2),]
The 2nd line of R code above gets bogged down and takes all my RAM with it:
<http://r.789695.n4.nabble.com/file/n4656723/memory_loss.png>
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?
-Eric
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