Count rows by group based on values

I have a dataframe, DATA, containing information on students and their test dates. I want to create a variable called WANT, where for all the STUDENTs you count the unique months (not the unique rows) as shown in the sample of the WANT variable below:

library(dplyr)

set.seed(0)

DATA <- data.frame("STUDENT" = sample(1:5, 100, r = T),
                   "TESTDATE" = sample(seq(as.Date('2010/01/01'), as.Date('2010/12/31'), by="day"), 100, r=T))
    
DATA <- DATA %>% arrange(STUDENT, TESTDATE)
    
DATA$WANT <- c(1,1,1,2,2,3,3,4,4,5,5,6,7,7,8,8,9,1,1,1,2,3,3,4,5,5,6,7,8,8,9,10,10, rep(NA, 67))

My attempt only does rows and it’s not what I wish for

DATA %>% group_by(STUDENT) %>% mutate(WANT = 1:n())

>Solution :

We may extract the month part and use match or as.integer(factor(WANT2 levels = unique(WANT2)))

library(dplyr)
out <- DATA %>% 
  group_by(STUDENT) %>% 
  mutate(WANT2 = as.integer(format(TESTDATE, '%m')),
        WANT2 = match(WANT2, unique(WANT2))) %>%
   ungroup

-output

> head(out, 22) %>% as.data.frame
   STUDENT   TESTDATE WANT WANT2
1        1 2010-01-20    1     1
2        1 2010-01-31    1     1
3        1 2010-02-10    2     2
4        1 2010-02-10    2     2
5        1 2010-03-27    3     3
6        1 2010-04-20    4     4
7        1 2010-04-21    4     4
8        1 2010-05-02    5     5
9        1 2010-05-06    5     5
10       1 2010-05-13    5     5
11       1 2010-05-20    5     5
12       1 2010-06-17    6     6
13       1 2010-08-22    7     7
14       1 2010-08-25    7     7
15       1 2010-08-27    7     7
16       1 2010-08-30    7     7
17       1 2010-09-06    8     8
18       1 2010-09-30    8     8
19       1 2010-10-27    9     9
20       1 2010-10-31    9     9
21       1 2010-12-10   10    10
22       1 2010-12-21   10    10

If we want the year-month to count as separate, then do

out <- DATA %>% 
  group_by(STUDENT) %>% 
  mutate(WANT2 = format(TESTDATE, '%Y-%m'),
        WANT2 = match(WANT2, unique(WANT2))) %>%
   ungroup