Suppose I have a data frame with 8 schools and its characteristics, and another with 48 teachers and its characteristics. I can generate some fake data with the following code:

```
library(dplyr)
library(geosphere)
set.seed(6232015)
n.schools <-8
n.teachers <- 48
makeRandomString <- function(pre, n=1, length=12) {
randomString <- c(1:n) # initialize vector
for (i in 1:n) {
randomString[i] <- paste0(pre,'.', paste(sample(c(0:9, letters, LETTERS),
length, replace=TRUE),
collapse=""))
}
return(randomString)
}
gen.teachers <- function(n.teachers){
Teacher.ID <- makeRandomString(pre= 'T', n = n.teachers, length = 20)
Teacher.exp <- runif(n = n.teachers, min = 1, max = 30)
Teacher.Other <- sample(c(0,1), replace = T, prob = c(0.5, 0.5), size = n.teachers)
Teachers <- data.frame(Teacher.ID, Teacher.exp, Teacher.Other)
return(Teachers)
}
gen.schools <- function(n.schools){
School.ID <- makeRandomString(pre= 'S', n = n.schools, length = 20)
School.lat <- runif(n = n.schools, min = -2, max = 2)
School.long <- runif(n = n.schools, min = -2, max = 2)
Schools <- data.frame(School.ID, School.lat, School.long) %>%
rowwise() %>% mutate (School.distance = distHaversine(p1 = c(School.long, School.lat),
p2 = c(0, 0), r = 3961))
return(Schools)
}
Teachers <- gen.teachers(n.teachers = n.teachers)
Schools <- gen.schools(n.schools = n.schools)
```

To each shool, I want to assign 6 teachers (every teacher get 1 and only 1 school). I could use:

```
Teachers %>% sample_n(6)
```

To get a list of 6 teachers assign those to a school, remove them from my original pool and keep going with a loop. My guess/hope is that there is a much easier way of doing this.

Thanks for the help!

Answer:

In the context of your code

```
sample(rep(Schools$School.ID, each = 6))
```

gives a random sequence of schools where each school.id appears 6 times. Set Teachers$AssignedSchool to this sample and each teacher has an assigned school

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