On Jan 8, 2012, at 4:48 PM, jawbonemurphy wrote:
Hi,
I am trying to create a script that will evaluate each column of a
data
frame, regardless of # columns, using some function and sorting the
results
by an index vector:
?lapply
?"["
?order
#upload data (112 rows x 73 columns)
SD <- read.csv("/Users/johnjacob/Desktop/StudentsData_RInput.csv",
header=TRUE)
#assign index vector
ID <- SD[ ,2]
#write indexed mean function
meanfun <- function(x) {
for(i in 3:ncol(x)) {
meanSD <- tapply(x[,i], ID, FUN=mean)}
Aren't you worried about over-writing meanSD? this would appear to
leave meanSD with only the result from the last column.
return(meanSD)
}
What are you expecting to get back? 'tapply' will very possibly return
a matrix.
#apply function to data
meanfun(SD)
What I get is one set of indexed means:
7605 Andrea Billy ERR006 FJM13
2.111111 1.400000 1.888889 3.692308 3.750000
Gayan Jschaef Whitney
1.300000 2.285714 2.000000
...and what I would like to generate is a set of indexed means
By indexed you mean grouped? Perhaps you should be looking at ?aggregate
for each
column in the data set.
Any guidance would be much appreciated!
David Winsemius, MD
West Hartford, CT
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