Append value to empty vector in R?
Solution 1
Appending to an object in a for loop causes the entire object to be copied on every iteration, which causes a lot of people to say "R is slow", or "R loops should be avoided".
As BrodieG mentioned in the comments: it is much better to pre-allocate a vector of the desired length, then set the element values in the loop.
Here are several ways to append values to a vector. All of them are discouraged.
Appending to a vector in a loop
# one way
for (i in 1:length(values))
vector[i] <- values[i]
# another way
for (i in 1:length(values))
vector <- c(vector, values[i])
# yet another way?!?
for (v in values)
vector <- c(vector, v)
# ... more ways
help("append")
would have answered your question and saved the time it took you to write this question (but would have caused you to develop bad habits). ;-)
Note that vector <- c()
isn't an empty vector; it's NULL
. If you want an empty character vector, use vector <- character()
.
Pre-allocate the vector before looping
If you absolutely must use a for loop, you should pre-allocate the entire vector before the loop. This will be much faster than appending for larger vectors.
set.seed(21)
values <- sample(letters, 1e4, TRUE)
vector <- character(0)
# slow
system.time( for (i in 1:length(values)) vector[i] <- values[i] )
# user system elapsed
# 0.340 0.000 0.343
vector <- character(length(values))
# fast(er)
system.time( for (i in 1:length(values)) vector[i] <- values[i] )
# user system elapsed
# 0.024 0.000 0.023
Solution 2
FWIW: analogous to python's append():
b <- 1
b <- c(b, 2)
Solution 3
You have a few options:
c(vector, values)
append(vector, values)
vector[(length(vector) + 1):(length(vector) + length(values))] <- values
The first one is the standard approach. The second one gives you the option to append someplace other than the end. The last one is a bit contorted but has the advantage of modifying vector
(though really, you could just as easily do vector <- c(vector, values)
.
Notice that in R you don't need to cycle through vectors. You can just operate on them in whole.
Also, this is fairly basic stuff, so you should go through some of the references.
Some more options based on OP feedback:
for(i in values) vector <- c(vector, i)
Solution 4
Just for the sake of completeness, appending values to a vector in a for loop is not really the philosophy in R. R works better by operating on vectors as a whole, as @BrodieG pointed out. See if your code can't be rewritten as:
ouput <- sapply(values, function(v) return(2*v))
Output will be a vector of return values. You can also use lapply
if values is a list instead of a vector.
Solution 5
Sometimes we have to use loops, for example, when we don't know how many iterations we need to get the result. Take while loops as an example. Below are methods you absolutely should avoid:
a=numeric(0)
b=1
system.time(
{
while(b<=1e5){
b=b+1
a<-c(a,pi)
}
}
)
# user system elapsed
# 13.2 0.0 13.2
a=numeric(0)
b=1
system.time(
{
while(b<=1e5){
b=b+1
a<-append(a,pi)
}
}
)
# user system elapsed
# 11.06 5.72 16.84
These are very inefficient because R copies the vector every time it appends.
The most efficient way to append is to use index. Note that this time I let it iterate 1e7 times, but it's still much faster than c
.
a=numeric(0)
system.time(
{
while(length(a)<1e7){
a[length(a)+1]=pi
}
}
)
# user system elapsed
# 5.71 0.39 6.12
This is acceptable. And we can make it a bit faster by replacing [
with [[
.
a=numeric(0)
system.time(
{
while(length(a)<1e7){
a[[length(a)+1]]=pi
}
}
)
# user system elapsed
# 5.29 0.38 5.69
Maybe you already noticed that length
can be time consuming. If we replace length
with a counter:
a=numeric(0)
b=1
system.time(
{
while(b<=1e7){
a[[b]]=pi
b=b+1
}
}
)
# user system elapsed
# 3.35 0.41 3.76
As other users mentioned, pre-allocating the vector is very helpful. But this is a trade-off between speed and memory usage if you don't know how many loops you need to get the result.
a=rep(NaN,2*1e7)
b=1
system.time(
{
while(b<=1e7){
a[[b]]=pi
b=b+1
}
a=a[!is.na(a)]
}
)
# user system elapsed
# 1.57 0.06 1.63
An intermediate method is to gradually add blocks of results.
a=numeric(0)
b=0
step_count=0
step=1e6
system.time(
{
repeat{
a_step=rep(NaN,step)
for(i in seq_len(step)){
b=b+1
a_step[[i]]=pi
if(b>=1e7){
a_step=a_step[1:i]
break
}
}
a[(step_count*step+1):b]=a_step
if(b>=1e7) break
step_count=step_count+1
}
}
)
#user system elapsed
#1.71 0.17 1.89
Related videos on Youtube
O.rka
I am an academic researcher studying machine-learning and microorganisms
Updated on July 08, 2022Comments
-
O.rka almost 2 years
I'm trying to learn R and I can't figure out how to append to a list.
If this were Python I would . . .
#Python vector = [] values = ['a','b','c','d','e','f','g'] for i in range(0,len(values)): vector.append(values[i])
How do you do this in R?
#R Programming > vector = c() > values = c('a','b','c','d','e','f','g') > for (i in 1:length(values)) + #append value[i] to empty vector
-
Private about 5 yearsjust for clarity's sake, this is not how you'd do this in python, at least if I understand you correctly. you could simply do
vector = values
; or you could do vector = vector + values. But I might be misunderstanding your use case
-
-
O.rka about 10 yearsi'm doing something a little more complicated tho. i need to append them through for-loop because i am modifying them
-
BrodieG about 10 years@draconisthe0ry, why don't you provide more details on what you're trying to do?
-
O.rka about 10 yearsI tried this but got a NULL list when i print(vector)
-
BrodieG about 10 years+1 for reminder about inefficiency, but maybe add details on how to work around (
vector <- character(length(values)); for(...
)? -
O.rka about 10 yearsoh i see! instead of doing c(vector,values[i]) in the for loop you have to "vector = c(vector,values[i])
-
loretoparisi over 7 yearssupposed i would like to use
c
to append dataframe instead of vectors? -
juanbretti almost 7 yearsThere is also the append() in R. Will be used as:
b <- 1; b <- append(b, 2)
. But as you mention, c() is a more R way of doing things. -
baxx over 5 yearsIf all are discouraged it would be nice to highlight what's encouraged instead, as this is a fairly common pattern.
-
tjebo almost 4 yearsat this point, it may be worth also to mention the great book "R inferno" which discusses growing vectors in circle 2 burns-stat.com/pages/Tutor/R_inferno.pdf
-
Dev Solution over 3 yearsjust moment, I am not sure for this is true or false. But thanks.
-
Brian Wiley over 3 yearsIn practice many (most?) of the times you do not know how large your vector will be such as when you only add something if a condition is met inside the for loop. How do you handle this?
-
Soumya about 3 yearsNote that as of R4.0.3 at least, preallocating hardly makes any difference at data sizes 1e4 (milliseconds difference) or 1e5 (centiseconds difference).