问题
Is there is a faster way to make a counter index than using a loop? Within contiguous runs 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}
}
回答1:
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
回答2:
Using data.table, which has the function rleid()
:
require(data.table) # v1.9.5+
rleid(x)
# [1] 1 2 3 4 5 5 6 7 7 8 8 8 9
回答3:
This will work with numeric of character values:
rep(1:length(rle(x)$values), times = rle(x)$lengths)
#[1] 1 2 3 4 5 5 6 7 7 8 8 8 9
You can also be a bit more efficient by calling rle
just once (about 2x faster) and a very slight speed improvement can be made using rep.int
instead of rep
:
y <- rle(x)
rep.int(1:length(y$values), times = y$lengths)
来源:https://stackoverflow.com/questions/30314679/add-index-to-contiguous-runs-of-equal-values