On 2010-05-17 12:54, Henrique Dallazuanna wrote:
Try this:
newData<- sapply(numdat, function(x)lapply(strsplit(as.character(x), '-'),
function(.x)mean(as.numeric(.x))))
There's a potential problem if numdat contains negative numbers.
It would be better to restrict the recoding to character or
factor columns.
cl <- sapply(numdat, class)
idx <- which(cl %in% c('character','factor'))
g <- function(x){
sapply(strsplit(as.character(x),"-"),
function(.x) mean(as.numeric(.x), na.rm=TRUE))
}
newData <- numdat
for(i in idx) newData[,i] <- g(newData[,i])
newData
-Peter Ehlers
On Mon, May 17, 2010 at 3:29 PM, Juliet Hannah<juliet.han...@gmail.com>wrote:
I am recoding some data. Many values that should be 1.5 are recorded
as 1-2. Some example data and my solution is below. I am curious about
better approaches or any other suggestions. Thanks!
# example input data
myData<- read.table(textConnection("id, v1, v2, v3
a,1,2,3
b,1-2,,3-4
c,,3,4"),header=TRUE,sep=",")
closeAllConnections()
# the first column is IDs so remove that
numdat<- myData[,-1]
# function to change dashes: 1-2 to 1.5
myrecode<- function(mycol)
{
newcol<- mycol
newcol<- gsub("1-2","1.5",newcol)
newcol<- gsub("2-3","2.5",newcol)
newcol<- gsub("3-4","3.5",newcol)
newcol<- as.numeric(newcol)
}
newData<- data.frame(do.call(cbind,lapply(numdat,myrecode)))
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