Hi:
One approach:
(1) Put your files into a separate directory.
(2) Use list.files() to grab the individual file names.
(3) Write a function that takes a data frame as an argument and does
the necessary processing.
(4) Use lapply() or ldply/llply from the plyr package to recursively
run the function on each file in the list. lapply() and llply() will
return lists, ldply() would return a data frame. If you intend to use
ldply(), then the function in (3) needs to return a data frame.
Here's a small demo. I have five data sets in my starting directory
with variables x1, x2, y. The function reads in the data and returns
the output of a regression model; when lapply() is run on it, the
output of the five models is returned as a list. One can then cherry
pick output from the list of models.
files <- paste('dat', 1:5, '.csv', sep = '')
myfun <- function(d) {
df <- read.csv(d, header = TRUE)
lm(y ~ ., data = df)
}
lout <- lapply(files, myfun)
library(plyr)
ldply(lout, function(x) coef(x)) # coefficients
ldply(lout, function(x) summary(x)$r.squared) # R^2
One could also use
do.call(rbind, lapply(lout, function(x) coef(x))
do.call(rbind, lapply(lout, function(x) summary(x)$r.squared))
but ldply() has a somewhat simpler syntax.
Hopefully, you can adapt these steps to your problem.
Dennis
On Mon, Jun 27, 2011 at 3:01 PM, Trying To learn again
<tryingtolearnag...@gmail.com> wrote:
> Hi all,
>
> I have the next problem: I have a matrix with size 8,000,000x18. My personal
> computer...blocks...so I have cut my original file into 100 different file.
>
> I have written a function that should be run on each of this file.
>
> So imagine
>
> I need to read data from q1 to q100 file
>
> data<-read.table("q1.txt",sep="")
>
> and each time I read 1 file execute my personal function (I get some stats)
> and my last target is to add each partial stats...
>
> My question is:
>
> Is posible to say something similar to this?
>
> for (i in 1:100){
>
> data[i]<-read.table("q[i].txt", sep="")
>
> execute .....
>
> }
>
> Many thanks in advance
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help@r-project.org mailing list
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> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
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