Using `each` vs `times` for a vector in R?

In the following dataset,

df_final <- data.frame(month = rep(c(1:12), each =30 * 2),
                           site = rep(c("1","2","3","4","5","6"), times = 60 * 2),
                           quad = rep(c(1:5), times = 72 * 2),
                           seed = rep(c(1:2), times = 360))

.. every month (1-12), has 6 sites (1-6), with 5 quadrants (1-5) quad. So one dataset has 12 * 6 * 5 = 360 rows. Here, I have two such datasets (360 * 2). I could also have 1000 such datasets. For every unqiue dataset, I want to assign a different seed.

output should looks like:

month site quad seed
   1     1    1     1 
   1     1    2     1
   1     1    3     1
   1     1    4     1
   1     1    5     1
   1     1    1     2 
   1     1    2     2
   1     1    3     2
   1     1    4     2
   1     1    5     2

I tried using seed = rep(c(1:2), each = 360 but that didn't work as well. How can I get this output? I want a general way to do it, so that I can do the same for 1000 seeds.

You can use cur_group_id:

library(dplyr)
df_final %>% 
  group_by(month, site) %>% 
  mutate(seed = cur_group_id()) %>% 
  ungroup() %>% arrange(month, site)

Or consecutive_id after arranging the columns:

library(dplyr) #1.1.0+
df_final %>% 
  arrange(month, site) %>% 
  mutate(seed = consecutive_id(month, site))

Using data.table

library(data.table)
setDT(df_final)[order(month, site), seed := rleid(month, site)]

Or do

setDT(df_final)[, seed := .GRP, .(month, site)]