Add column counting upwards until value in another column changes

Question

I have a df called data_clean:

    > head(data_clean)
  participant    type target_onset key_resp.rt central_size
1        1010     gap          0.4   0.3260000         0.15
2        1010     gap          0.1   0.3380001         0.15
3        1010 overlap            0   0.4480000         0.10
4        1010     gap          0.2   0.3940001         0.10
5        1010     gap          0.1   0.3980000         0.10
6        1010     gap          0.2   0.4990001         0.10

I would like to add a column called trial_num that +=1 every row until the participant column number changes. And then it should start again. So if the next participant started after 6 trials, it would look something like this:

  participant    type target_onset key_resp.rt central_size  trial_num
1        1010     gap          0.4   0.3260000         0.15      1
2        1010     gap          0.1   0.3380001         0.15      2
3        1010 overlap            0   0.4480000         0.10      3
4        1010     gap          0.2   0.3940001         0.10      4
5        1010     gap          0.1   0.3980000         0.10      5
6        1010     gap          0.2   0.4990001         0.10      6
7        1011     gap          0.4   0.3260000         0.15      1
8        1011     gap          0.1   0.3380001         0.15      2
9        1011 overlap            0   0.4480000         0.10      3

Any suggestions are much appreciated. Thanks.

score 2 · Accepted Answer · answered Dec 07 '20 at 19:28

Try this using row_number() after applying a task by groups on your id using group_by(). Here the code using dplyr:

library(dplyr)
#Code
new <- data_clean%>%
  group_by(participant) %>%
  mutate(trial_num=row_number())

Output:

# A tibble: 9 x 6
# Groups:   participant [2]
  participant type    target_onset key_resp.rt central_size trial_num
        <int> <chr>          <dbl>       <dbl>        <dbl>     <int>
1        1010 gap              0.4       0.326         0.15         1
2        1010 gap              0.1       0.338         0.15         2
3        1010 overlap          0         0.448         0.1          3
4        1010 gap              0.2       0.394         0.1          4
5        1010 gap              0.1       0.398         0.1          5
6        1010 gap              0.2       0.499         0.1          6
7        1011 gap              0.4       0.326         0.15         1
8        1011 gap              0.1       0.338         0.15         2
9        1011 overlap          0         0.448         0.1          3

Some data used:

#Data
data_clean <- structure(list(participant = c(1010L, 1010L, 1010L, 1010L, 1010L, 
1010L, 1011L, 1011L, 1011L), type = c("gap", "gap", "overlap", 
"gap", "gap", "gap", "gap", "gap", "overlap"), target_onset = c(0.4, 
0.1, 0, 0.2, 0.1, 0.2, 0.4, 0.1, 0), key_resp.rt = c(0.326, 0.3380001, 
0.448, 0.3940001, 0.398, 0.4990001, 0.326, 0.3380001, 0.448), 
    central_size = c(0.15, 0.15, 0.1, 0.1, 0.1, 0.1, 0.15, 0.15, 
    0.1)), row.names = c("1", "2", "3", "4", "5", "6", "7", "8", 
"9"), class = "data.frame")

Add column counting upwards until value in another column changes

1 Answers1