On Sat, 31 Jan 2004, Christian Schulz wrote:
Yes, many thanks i have really to avoid think in loops :-)
Unfortunately Chuck's solution is a loop over rows, disguised by the use
of apply.
Let us assume that the dataframe has all numeric entries and coerce to a
matrix (as apply will, BTW).
tmp <- as.matrix(df)
tmp[is.na(tmp)] <- -1 # get rid of the NAs
tmp <- tmp >= 0 # a logical matrix
tmp <- cbind(tmp, TRUE) # add a fence column
I am happy to loop over 43 columns, though, so
for(i in 2:44) tmp[, i] <- tmp[, i] | tmp[, i-1]
for(i in 44:2) tmp[, i] <- tmp[, i] & !tmp[, i-1]
rtmp <- t(tmp)
z <- row(rtmp)[rtmp]
z[z==44] <- NA
z
is what you want. It's a lot faster (about 12x).
christian
Am Samstag, 31. Januar 2004 16:57 schrieb Chuck Cleland:
df is a data.frame with 43 colums and 29877 rows with lot of NA.
I want the column number for all respondendts in one column
where is the first entry >=0 as columnnumber.
my first step:
time <- function(df)
+ { for (i in 1:length(df [,1])) {
+ which(df[i,1]:df[i,43] >= 0)
+ }
+ }
Error in df[i, 1]:df[i, 43] : NA/NaN argument
I am not sure, but I think you might want something like this:
t1 <- apply(df, 1, function(x){
ifelse(all(is.na(x)) | all(na.omit(x) < 0),
NA, which(x >= 0))})
hope this helps,
Chuck Cleland