Is there is a faster way to make a counter index than using a loop? For each contiguous run of equal values, the index should be the same. I find the looping very slow especially when the data is so big.
For illustration, here is the input and desired output
x <- c(2, 3, 9, 2, 4, 4, 3, 4, 4, 5, 5, 5, 1)
Desired resulting counter:
c(1, 2, 3, 4, 5, 5, 6, 7, 7, 8, 8, 8, 9)
Note that non-contiguous runs have different indexes. E.g. see the desired indexes of the values 2
and 4
My inefficient code is this:
group[1]<-1
counter<-1
for (i in 2:n){
if (x[i]==x[i-1]){
group[i]<-counter
}else{
counter<-counter+1
group[1]<-counter}
}
Above answer by Jota can be further simplified to, which will be even faster
with(rle(x), rep(1:length(lengths), lengths))
[1] 1 2 3 4 5 5 6 7 7 8 8 8 9
If you have numeric values like this, you can use diff
and cumsum
to add up changes in values
x <- c(2,3,9,2,4,4,3,4,4,5,5,5,1)
cumsum(c(1,diff(x)!=0))
# [1] 1 2 3 4 5 5 6 7 7 8 8 8 9
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