I have to split a vector into n chunks of equal size in R. I couldn't find any base function to do that. Also Google didn't get me anywhere. So here is what I came up with, hopefully it helps someone some where.
x <- 1:10
n <- 3
chunk <- function(x,n) split(x, factor(sort(rank(x)%%n)))
chunk(x,n)
$`0`
[1] 1 2 3
$`1`
[1] 4 5 6 7
$`2`
[1] 8 9 10
Any comments, suggestions or improvements are really welcome and appreciated.
Cheers, Sebastian
转载于:https://stackoverflow.com/questions/3318333/split-a-vector-into-chunks-in-r
You could combine the split/cut, as suggested by mdsummer, with quantile to create even groups:
split(x,cut(x,quantile(x,(0:n)/n), include.lowest=TRUE, labels=FALSE))
This gives the same result for your example, but not for skewed variables.
A few more variants to the pile...
> x <- 1:10
> n <- 3
Note, that you don't need to use the factor function here, but you still want to sort o/w your first vector would be 1 2 3 10:
> chunk <- function(x, n) split(x, sort(rank(x) %% n))
> chunk(x,n)
$`0`
[1] 1 2 3
$`1`
[1] 4 5 6 7
$`2`
[1] 8 9 10
Or you can assign character indices, vice the numbers in left ticks above:
> my.chunk <- function(x, n) split(x, sort(rep(letters[1:n], each=n, len=length(x))))
> my.chunk(x, n)
$a
[1] 1 2 3 4
$b
[1] 5 6 7
$c
[1] 8 9 10
Or you can use plainword names stored in a vector. Note that using sort to get consecutive values in x alphabetizes the labels:
> my.other.chunk <- function(x, n) split(x, sort(rep(c("tom", "dick", "harry"), each=n, len=length(x))))
> my.other.chunk(x, n)
$dick
[1] 1 2 3
$harry
[1] 4 5 6
$tom
[1] 7 8 9 10
split(x,matrix(1:n,n,length(x))[1:length(x)])
perhaps this is more clear, but the same idea:split(x,rep(1:n, ceiling(length(x)/n),length.out = length(x)))
if you want it ordered,throw a sort around it
A one-liner splitting d into chunks of size 20:
split(d, ceiling(seq_along(d)/20))
More details: I think all you need is seq_along(), split() and ceiling():
> d <- rpois(73,5)
> d
[1] 3 1 11 4 1 2 3 2 4 10 10 2 7 4 6 6 2 1 1 2 3 8 3 10 7 4
[27] 3 4 4 1 1 7 2 4 6 0 5 7 4 6 8 4 7 12 4 6 8 4 2 7 6 5
[53] 4 5 4 5 5 8 7 7 7 6 2 4 3 3 8 11 6 6 1 8 4
> max <- 20
> x <- seq_along(d)
> d1 <- split(d, ceiling(x/max))
> d1
$`1`
[1] 3 1 11 4 1 2 3 2 4 10 10 2 7 4 6 6 2 1 1 2
$`2`
[1] 3 8 3 10 7 4 3 4 4 1 1 7 2 4 6 0 5 7 4 6
$`3`
[1] 8 4 7 12 4 6 8 4 2 7 6 5 4 5 4 5 5 8 7 7
$`4`
[1] 7 6 2 4 3 3 8 11 6 6 1 8 4
This will split it differently to what you have, but is still quite a nice list structure I think:
chunk.2 <- function(x, n, force.number.of.groups = TRUE, len = length(x), groups = trunc(len/n), overflow = len%%n) {
if(force.number.of.groups) {
f1 <- as.character(sort(rep(1:n, groups)))
f <- as.character(c(f1, rep(n, overflow)))
} else {
f1 <- as.character(sort(rep(1:groups, n)))
f <- as.character(c(f1, rep("overflow", overflow)))
}
g <- split(x, f)
if(force.number.of.groups) {
g.names <- names(g)
g.names.ordered <- as.character(sort(as.numeric(g.names)))
} else {
g.names <- names(g[-length(g)])
g.names.ordered <- as.character(sort(as.numeric(g.names)))
g.names.ordered <- c(g.names.ordered, "overflow")
}
return(g[g.names.ordered])
}
Which will give you the following, depending on how you want it formatted:
> x <- 1:10; n <- 3
> chunk.2(x, n, force.number.of.groups = FALSE)
$`1`
[1] 1 2 3
$`2`
[1] 4 5 6
$`3`
[1] 7 8 9
$overflow
[1] 10
> chunk.2(x, n, force.number.of.groups = TRUE)
$`1`
[1] 1 2 3
$`2`
[1] 4 5 6
$`3`
[1] 7 8 9 10
Running a couple of timings using these settings:
set.seed(42)
x <- rnorm(1:1e7)
n <- 3
Then we have the following results:
> system.time(chunk(x, n)) # your function
user system elapsed
29.500 0.620 30.125
> system.time(chunk.2(x, n, force.number.of.groups = TRUE))
user system elapsed
5.360 0.300 5.663
EDIT: Changing from as.factor() to as.character() in my function made it twice as fast.
chunk2 <- function(x,n) split(x, cut(seq_along(x), n, labels = FALSE))
I needed the same function and have read the previous solutions, however i also needed to have the unbalanced chunk to be at the end i.e if i have 10 elements to split them into vectors of 3 each, then my result should have vectors with 3,3,4 elements respectively. So i used the following (i left the code unoptimised for readability, otherwise no need to have many variables):
chunk <- function(x,n){
numOfVectors <- floor(length(x)/n)
elementsPerVector <- c(rep(n,numOfVectors-1),n+length(x) %% n)
elemDistPerVector <- rep(1:numOfVectors,elementsPerVector)
split(x,factor(elemDistPerVector))
}
set.seed(1)
x <- rnorm(10)
n <- 3
chunk(x,n)
$`1`
[1] -0.6264538 0.1836433 -0.8356286
$`2`
[1] 1.5952808 0.3295078 -0.8204684
$`3`
[1] 0.4874291 0.7383247 0.5757814 -0.3053884
Here's another variant.
NOTE: with this sample you're specifying the CHUNK SIZE in the second parameter
chunk <- function(x,n)
{
f <- sort(rep(1:(trunc(length(x)/n)+1),n))[1:length(x)]
return(split(x,f))
}
#Test
n<-c(1,2,3,4,5,6,7,8,9,10,11)
c<-chunk(n,5)
q<-lapply(c, function(r) cat(r,sep=",",collapse="|") )
#output
1,2,3,4,5,|6,7,8,9,10,|11,|
Credit to @Sebastian for this function
chunk <- function(x,y){
split(x, factor(sort(rank(row.names(x))%%y)))
}
If you don't like split() and you don't mind NAs padding out your short tail:
chunk <- function(x, n) { if((length(x)%%n)==0) {return(matrix(x, nrow=n))} else {return(matrix(append(x, rep(NA, n-(length(x)%%n))), nrow=n))} }
The columns of the returned matrix ([,1:ncol]) are the droids you are looking for.
If you don't like split() and you don't like matrix() (with its dangling NAs), there's this:
chunk <- function(x, n) (mapply(function(a, b) (x[a:b]), seq.int(from=1, to=length(x), by=n), pmin(seq.int(from=1, to=length(x), by=n)+(n-1), length(x)), SIMPLIFY=FALSE))
Like split(), it returns a list, but it doesn't waste time or space with labels, so it may be more performant.
simplified version...
n = 3
split(x, sort(x%%n))
Simple function for splitting a vector by simply using indexes - no need to over complicate this
vsplit <- function(v, n) {
l = length(v)
r = l/n
return(lapply(1:n, function(i) {
s = max(1, round(r*(i-1))+1)
e = min(l, round(r*i))
return(v[s:e])
}))
}
Sorry if this answer comes so late, but maybe it can be useful for someone else. Actually there is a very useful solution to this problem, explained at the end of ?split.
> testVector <- c(1:10) #I want to divide it into 5 parts
> VectorList <- split(testVector, 1:5)
> VectorList
$`1`
[1] 1 6
$`2`
[1] 2 7
$`3`
[1] 3 8
$`4`
[1] 4 9
$`5`
[1] 5 10
Yet another possibility is the splitIndices function from package parallel:
library(parallel)
splitIndices(20, 3)
Gives:
[[1]]
[1] 1 2 3 4 5 6 7
[[2]]
[1] 8 9 10 11 12 13
[[3]]
[1] 14 15 16 17 18 19 20
Wow, this question got more traction than expected.
Thanks for all the ideas. I have come up with this solution:
require(magrittr)
create.chunks <- function(x, elements.per.chunk){
# plain R version
# split(x, rep(seq_along(x), each = elements.per.chunk)[seq_along(x)])
# magrittr version - because that's what people use now
x %>% seq_along %>% rep(., each = elements.per.chunk) %>% extract(seq_along(x)) %>% split(x, .)
}
create.chunks(letters[1:10], 3)
$`1`
[1] "a" "b" "c"
$`2`
[1] "d" "e" "f"
$`3`
[1] "g" "h" "i"
$`4`
[1] "j"
The key is to use the seq(each = chunk.size) parameter so make it work. Using seq_along acts like rank(x) in my previous solution, but is actually able to produce the correct result with duplicate entries.
Using base R's rep_len:
x <- 1:10
n <- 3
split(x, rep_len(1:n, length(x)))
# $`1`
# [1] 1 4 7 10
#
# $`2`
# [1] 2 5 8
#
# $`3`
# [1] 3 6 9
And as already mentioned if you want sorted indices, simply:
split(x, sort(rep_len(1:n, length(x))))
# $`1`
# [1] 1 2 3 4
#
# $`2`
# [1] 5 6 7
#
# $`3`
# [1] 8 9 10