dt <- data.table(id = rep(1:5, 5), obs = rnorm(1, n = 25))[order(id)]
dt

   id      obs
1:  1  0.1470735
2:  1  1.6954685
3:  1  2.3947260
4:  1  2.1782338
5:  1  0.5168873
6:  2 -0.8879545
7:  2  1.9320034
8:  2  2.6269272
9:  2  1.5212627
10: 2 -0.1581711

id      obs      group
1:  1  0.1470735      A
2:  1  1.6954685      A
3:  1  2.3947260      A
4:  1  2.1782338      A
5:  1  0.5168873      A
6:  2 -0.8879545      A
7:  2  1.9320034      A
8:  2  2.6269272      A
9:  2  1.5212627      A
10: 2 -0.1581711      A

dt <- data.table(id = rep(1:5, 5), obs = rnorm(1, n = 25))[order(id)]

max_per_group <- 5
n_ids <- length(unique(dt$id))

data.frame(id = unique(dt$id), grp = sample(rep(LETTERS, max_per_group), n_ids)) %>%
  left_join(dt, ., by = "id")

   id         obs grp
1   1  1.28879713   S
2   1  1.04471197   S
3   1  0.36470847   S
4   1  0.46741567   S
5   1  1.07749891   S
6   2  1.73640785   K
7   2  1.61144042   K
8   2  2.85196859   K
9   2  1.84848117   K
10  2  2.11395863   K
11  3  0.88623462   S
12  3  2.11706351   S
13  3  1.29225433   S
14  3  0.30458037   S
15  3 -1.72070005   S
16  4  2.24593162   U
17  4  2.10346287   U
18  4  2.28724412   U
19  4  0.02978044   U
20  4  0.56234660   U
21  5  2.92050008   F
22  5  1.08048974   F
23  5  0.58885261   F
24  5  1.53299092   F
25  5  1.47271123   F