Yet another solution. This time using the LaF package:
library(LaF)
d<-c(1,4,7,8)
P1 <- laf_open_csv("M1.csv", column_types=rep("double", 10), skip=1)
P2 <- laf_open_csv("M2.csv", column_types=rep("double", 10), skip=1)
for (i in d) {
M<-data.frame(P1[, i],P2[, i])
}
(The skip=1 is needed as laf_open_csv doesn't read headers)
Jan
On 11/08/2011 11:04 AM, Sergio René Araujo Enciso wrote:
Dear all:
I have two larges files with 2000 columns. For each file I am
performing a loop to extract the "i"th element of each file and create
a data frame with both "i"th elements in order to perform further
analysis. I am not extracting all the "i"th elements but only certain
which I am indicating on a vector called "d".
See an example of my code below
### generate an example for the CSV files, the original files contain
more than 2000 columns, here for the sake of simplicity they have only
10 columns
M1<-matrix(rnorm(1000), nrow=100, ncol=10,
dimnames=list(seq(1:100),letters[1:10]))
M2<-matrix(rnorm(1000), nrow=100, ncol=10,
dimnames=list(seq(1:100),letters[1:10]))
write.table(M1, file="M1.csv", sep=",")
write.table(M2, file="M2.csv", sep=",")
### the vector containing the "i" elements to be read
d<-c(1,4,7,8)
P1<-read.table("M1.csv", header=TRUE)
P2<-read.table("M1.csv", header=TRUE)
for (i in d) {
M<-data.frame(P1[i],P2[i])
rm(list=setdiff(ls(),"d"))
}
As the files are quite large, I want to include "read.table" within
the loop so as it only read the "i"th element. I know that there is
the option "colClasses" for which I have to create a vector with zeros
for all the columns I do not want to load. Nonetheless I have no idea
how to make this vector to change in the loop, so as the only element
with no zeros is the "i"th element following the vector "d". Any ideas
how to do this? Or is there anz other approach to load only an
specific element?
best regards,
Sergio René
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