create a loop to get samples in grouped data which meet a condition

Question

I have a dataframe where data are grouped by ID. I need to know how many cells are the 10% of each group in order to select this number in a sample, but this sample should select the cells which EP is 1.

I've tried to do a nested For loop: one For to know the quantity of cells which are the 10% for each group and the bigger one to sample this number meeting the condition EP==1

x <- data.frame("ID"=rep(1:2, each=10),"EP" = rep(0:1, times=10))
x
   ID EP
1   1  0
2   1  1
3   1  0
4   1  1
5   1  0
6   1  1
7   1  0
8   1  1
9   1  0
10  1  1
11  2  0
12  2  1
13  2  0
14  2  1
15  2  0
16  2  1
17  2  0
18  2  1
19  2  0
20  2  1

for(j in 1:1000){
  for (i in 1:nrow(x)){
    d <- x[x$ID==i,]
    npix <- 10*nrow(d)/100
  }
  r <- sample(d[d$EP==1,],npix)
  print(r)
}
data frame with 0 columns and 0 rows
data frame with 0 columns and 0 rows
data frame with 0 columns and 0 rows
.
.
.
until 1000

I would want to get this dataframe, where each sample is in a new column in x, and the cell sampled has "1":

   ID EP s1 s2....s1000
1   1  0 0  0 ....
2   1  1 0  1
3   1  0 0  0
4   1  1 0  0
5   1  0 0  0
6   1  1 0  0
7   1  0 0  0
8   1  1 0  0
9   1  0 0  0
10  1  1 1  0
11  2  0 0  0
12  2  1 0  0
13  2  0 0  0
14  2  1 0  1
15  2  0 0  0
16  2  1 0  0
17  2  0 0  0
18  2  1 1  0
19  2  0 0  0
20  2  1 0  0

see that each 1 in S1 and s2 are the sampled cells and correspond to 10% of cells in each group (1, 2) which meet the condition EP==1

Answer 1

We can write a function which gives us 1's which are 10% for each ID and place it where EP = 1.

library(dplyr)
 rep_func <- function() {
   x %>%
    group_by(ID) %>%
    mutate(s1 = 0,
           s1 = replace(s1, sample(which(EP == 1), floor(0.1 * n())), 1)) %>%
    pull(s1)
}

then use replicate to repeat it for n times

n <- 5
x[paste0("s", seq_len(n))] <- replicate(n, rep_func())

x
#   ID EP s1 s2 s3 s4 s5
#1   1  0  0  0  0  0  0
#2   1  1  0  0  0  0  0
#3   1  0  0  0  0  0  0
#4   1  1  0  0  0  0  0
#5   1  0  0  0  0  0  0
#6   1  1  1  0  0  1  0
#7   1  0  0  0  0  0  0
#8   1  1  0  1  0  0  0
#9   1  0  0  0  0  0  0
#10  1  1  0  0  1  0  1
#11  2  0  0  0  0  0  0
#12  2  1  0  0  1  0  0
#13  2  0  0  0  0  0  0
#14  2  1  1  1  0  0  0
#15  2  0  0  0  0  0  0
#16  2  1  0  0  0  0  1
#17  2  0  0  0  0  0  0
#18  2  1  0  0  0  1  0
#19  2  0  0  0  0  0  0
#20  2  1  0  0  0  0  0