Hi,
Try this:
set.seed(51)
mat1<- as.matrix(data.frame(REC.TYPE=
sample(c("SAO","FAO","FL-1","FL-2","FL-15"),20,replace=TRUE),Col2=rnorm(20),Col3=runif(20),stringsAsFactors=FALSE))
dat1<- as.data.frame(mat1,stringsAsFactors=FALSE)
dat1[grepl("SAO|FL-15",dat1$REC.TYPE),]
# REC.TYPE Col2 Col3
#4 FL-15 -1.31594143 0.41193183
#6 FL-15 0.43419586 0.96004780
#9 FL-15 -0.90690732 0.84000657
#10 SAO 0.21363265 0.20155142
#13 SAO -0.55566727 0.71606558
#15 SAO -0.71533068 0.90851364
#17 SAO 1.58611036 0.97475674
#20 SAO -0.42904914 0.33710578
A.K.
----- Original Message -----
From: Matt Borkowski <mathias1...@yahoo.com>
To: r-help@r-project.org
Cc:
Sent: Sunday, March 3, 2013 1:11 AM
Subject: [R] Help searching a matrix for only certain records
Let me start by saying I am rather new to R and generally consider myself to be
a novice programmer...so don't assume I know what I'm doing :)
I have a large matrix, approximately 300,000 x 14. It's essentially a 20-year
dataset of 15-minute data. However, I only need the rows where the column I've
named REC.TYPE contains the string "SAO " or "FL-15".
My horribly inefficient solution was to search the matrix row by row, test the
REC.TYPE column and essentially delete the row if it did not match my criteria.
Essentially...
> j <- 1
> for (i in 1:nrow(dataset)) {
> if(dataset$REC.TYPE[j] != "SAO " && dataset$RECTYPE[j] != "FL-15") {
> dataset <- dataset[-j,] }
> else {
> j <- j+1 }
> }
After watching my code get through only about 10% of the matrix in an hour and
slowing with every row...I figure there must be a more efficient way of pulling
out only the records I need...especially when I need to repeat this for another
8 datasets.
Can anyone point me in the right direction?
Thanks!
Matt
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and provide commented, minimal, self-contained, reproducible code.
