dplyr - remove duplicated rows specifying which rows to keep?-CodePudding

I have the following tibble:

> dput(y)
structure(list(line = c("786O_C9", "786O_C9", "786O_C9", "786O_C9", 
"786O_C9", "786O_C9", "786O_C9", "786O_C9", "C2BBe1_C9", "C2BBe1_C9", 
"C2BBe1_C9", "C2BBe1_C9", "C2BBe1_C9", "C2BBe1_C9", "C2BBe1_C9", 
"C2BBe1_C9", "C2BBe1_C9", "C2BBe1_C9", "786O_C9", "786O_C9", 
"786O_C9"), rep = c(2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 1L, 1L, 1L, 
1L, 2L, 2L, 2L, 2L, 3L, 3L, 2L, 2L, 2L), attempt = c(1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
2L, 2L, 2L), omit = c(FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE), date = c("07/09/2022", 
"07/09/2022", "07/09/2022", "07/09/2022", "07/09/2022", "07/09/2022", 
"07/09/2022", "07/09/2022", "21/09/2022", "21/09/2022", "21/09/2022", 
"21/09/2022", "21/09/2022", "21/09/2022", "21/09/2022", "21/09/2022", 
"21/09/2022", "21/09/2022", "22/09/2022", "22/09/2022", "22/09/2022"
), conc = c(379.35, 363.45, 355.3, 349.4, 364.25, 919.3, 172.25, 
172.45, 293.1, 383.5, 436.9, 446.8, 391.2, 382.4, 392.5, 384.5, 
409.8, 402, 434, 419.6, 418.9), a260_280 = c(1.842, 1.84, 1.84, 
1.835, 1.836, 1.877, 1.809, 1.807, 1.764, 1.756, 1.733, 1.734, 
1.879, 1.877, 1.762, 1.763, 1.858, 1.869, 1.828, 1.833, 1.847
), a260_230 = c(2.015, 2.016, 2.014, 2.014, 2.02, 1.977, 1.652, 
1.669, 1.471, 1.475, 1.441, 1.438, 1.606, 1.592, 1.515, 1.619, 
1.6, 1.605, 1.866, 2.004, 2.02)), class = c("tbl_df", "tbl", 
"data.frame"), row.names = c(NA, -21L))

> data.frame(y)
        line rep attempt  omit       date   conc a260_280 a260_230
1    786O_C9   2       1 FALSE 07/09/2022 379.35    1.842    2.015
2    786O_C9   2       1 FALSE 07/09/2022 363.45    1.840    2.016
3    786O_C9   2       1 FALSE 07/09/2022 355.30    1.840    2.014
4    786O_C9   2       1 FALSE 07/09/2022 349.40    1.835    2.014
5    786O_C9   2       1 FALSE 07/09/2022 364.25    1.836    2.020
6    786O_C9   2       1  TRUE 07/09/2022 919.30    1.877    1.977
7    786O_C9   3       1 FALSE 07/09/2022 172.25    1.809    1.652
8    786O_C9   3       1 FALSE 07/09/2022 172.45    1.807    1.669
9  C2BBe1_C9   1       1 FALSE 21/09/2022 293.10    1.764    1.471
10 C2BBe1_C9   1       1 FALSE 21/09/2022 383.50    1.756    1.475
11 C2BBe1_C9   1       1 FALSE 21/09/2022 436.90    1.733    1.441
12 C2BBe1_C9   1       1 FALSE 21/09/2022 446.80    1.734    1.438
13 C2BBe1_C9   2       1 FALSE 21/09/2022 391.20    1.879    1.606
14 C2BBe1_C9   2       1 FALSE 21/09/2022 382.40    1.877    1.592
15 C2BBe1_C9   2       1 FALSE 21/09/2022 392.50    1.762    1.515
16 C2BBe1_C9   2       1 FALSE 21/09/2022 384.50    1.763    1.619
17 C2BBe1_C9   3       1 FALSE 21/09/2022 409.80    1.858    1.600
18 C2BBe1_C9   3       1 FALSE 21/09/2022 402.00    1.869    1.605
19   786O_C9   2       2 FALSE 22/09/2022 434.00    1.828    1.866
20   786O_C9   2       2 FALSE 22/09/2022 419.60    1.833    2.004
21   786O_C9   2       2 FALSE 22/09/2022 418.90    1.847    2.020

For those lines and reps where there are multiple attempts (1 2), I would like to remove any rows which are attempt 1. Is this possible?

Ideal output would be:

> y %>% filter(!(line == '786O_C9' & rep == 2 & attempt == 1))
# A tibble: 15 × 8
   line        rep attempt omit  date        conc a260_280 a260_230
   <chr>     <int>   <int> <lgl> <chr>      <dbl>    <dbl>    <dbl>
 1 786O_C9       3       1 FALSE 07/09/2022  172.     1.81     1.65
 2 786O_C9       3       1 FALSE 07/09/2022  172.     1.81     1.67
 3 C2BBe1_C9     1       1 FALSE 21/09/2022  293.     1.76     1.47
 4 C2BBe1_C9     1       1 FALSE 21/09/2022  384.     1.76     1.48
 5 C2BBe1_C9     1       1 FALSE 21/09/2022  437.     1.73     1.44
 6 C2BBe1_C9     1       1 FALSE 21/09/2022  447.     1.73     1.44
 7 C2BBe1_C9     2       1 FALSE 21/09/2022  391.     1.88     1.61
 8 C2BBe1_C9     2       1 FALSE 21/09/2022  382.     1.88     1.59
 9 C2BBe1_C9     2       1 FALSE 21/09/2022  392.     1.76     1.52
10 C2BBe1_C9     2       1 FALSE 21/09/2022  384.     1.76     1.62
11 C2BBe1_C9     3       1 FALSE 21/09/2022  410.     1.86     1.6 
12 C2BBe1_C9     3       1 FALSE 21/09/2022  402      1.87     1.60
13 786O_C9       2       2 FALSE 22/09/2022  434      1.83     1.87
14 786O_C9       2       2 FALSE 22/09/2022  420.     1.83     2.00
15 786O_C9       2       2 FALSE 22/09/2022  419.     1.85     2.02

Thanks ........................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................

CodePudding user response：

Is this what you are asking?
setdiff(y, (y %>% dplyr::filter(duplicated(y[,1:5]) & attempt == 1)))