Don't have your data, but something like this is close:
# something like the following. read into a list for easier processing
allFile <- Sys.glob("sample*.csv")
results <- lapply(allFiles, function(.file){
# extract number from file name
num <- as.integer(sub("^.*?([[:digit:]]+).*", "\\1", .file, perl=TRUE))
.in <- read.table(.file, skip=5)
.in$obs <- num
.in
})
# combine into a single dataframe
result <- do.call(rbind, results)
# now do your processing for average
z <- split(result, result[,1]) # split by first column
do.call(rbind, lapply(z, function(.avg){
data.frame(x=.avg[1,1], y=mean(.avg[,2]))
}))
On 2/8/08, Gator Connection <[EMAIL PROTECTED]> wrote:
>
>
>
>
>
> Dear list:I have a folder that contains more than 50 csv files labels
> sequencially like sample01.csv to sample50.csv. for each file the first 5
> rows are descriptive of the data collected (useful but not needed in data
> merge). each file then start the data at row 6 and have 2 variables x and y.
> In order to know which file one observation is from, I'd like to have a new
> variable location, for example if the data are from file sample11.csv, then
> the location for that obs is 11.Another difficulty is there might be two
> observations actually repetitive, for example sample05.csv might contain (4,
> 10) and (4, 12). I'd like to average it into (4, 11). Any suggestions are
> welcome.Jack
>
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> 08
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--
Jim Holtman
Cincinnati, OH
+1 513 646 9390
What is the problem you are trying to solve?
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