How to keep only the first set of duplicate if there are multiple duplicates in a column

The clin.info$Sample.ID has duplicates. If there are more than one pair of duplicates, I want to take only the first pair.

n_occur <- data.frame(table(clin.info$Sample.ID))
multiple.duplicates <- n_occur[n_occur$Freq > 2,]

if(multiple.duplicates$Var1 %in% clin.info$Sample.ID){
  clin.info <- clin.info %>% 
    group_by(Sample.ID) %>% 
    distinct
}

Traceback:

Error in if (multiple.duplicates$Var1 %in% clin.info$Sample.ID) { : 
  argument is of length zero

Data:

> dput(clin.info)
structure(list(Sample.ID = c("TCGA.B2.3924.01", "TCGA.B2.3924.01", 
"TCGA.B2.3924.01", "TCGA.B2.3924.01", "TCGA.B2.5635.01", "TCGA.B2.5635.01", 
"TCGA.B2.5635.01", "TCGA.B2.5635.01", "TCGA.B2.5635.01", "TCGA.B2.5635.01", 
"TCGA.A3.3357.01", "TCGA.A3.3357.01", "TCGA.A3.3367.01", "TCGA.A3.3367.01", 
"TCGA.A3.3387.01", "TCGA.A3.3387.01", "TCGA.B0.4698.01", "TCGA.B0.4698.01", 
"TCGA.B0.4710.01", "TCGA.B0.4710.01"), age = c("73", "73", "73", 
"73", "74", "74", "74", "74", "74", "74", "62", "62", "72", "72", 
"49", "49", "75", "75", "75", "75")), row.names = c(67L, 68L, 
69L, 70L, 71L, 72L, 73L, 74L, 75L, 76L, 1L, 2L, 3L, 4L, 5L, 6L, 
7L, 8L, 9L, 10L), class = "data.frame")

> dput(multiple.duplicates)
structure(list(Var1 = structure(6:7, levels = c("TCGA.A3.3357.01", 
"TCGA.A3.3367.01", "TCGA.A3.3387.01", "TCGA.B0.4698.01", "TCGA.B0.4710.01", 
"TCGA.B2.3924.01", "TCGA.B2.5635.01"), class = "factor"), Freq = c(4L, 
6L)), row.names = 6:7, class = "data.frame")

Expected output:

Based on multiple.duplicates, there are two Sample.ID values with more than one duplicate.

Hence, for these two Sample.ID, keep only the first set of duplicate in clin.info.

dplyr::slice_head(clin.info, n = 2, by = Sample.ID)
#>          Sample.ID age
#> 1  TCGA.B2.3924.01  73
#> 2  TCGA.B2.3924.01  73
#> 3  TCGA.B2.5635.01  74
#> 4  TCGA.B2.5635.01  74
#> 5  TCGA.A3.3357.01  62
#> 6  TCGA.A3.3357.01  62
#> 7  TCGA.A3.3367.01  72
#> 8  TCGA.A3.3367.01  72
#> 9  TCGA.A3.3387.01  49
#> 10 TCGA.A3.3387.01  49
#> 11 TCGA.B0.4698.01  75
#> 12 TCGA.B0.4698.01  75
#> 13 TCGA.B0.4710.01  75
#> 14 TCGA.B0.4710.01  75

^{Created on 2023-05-28 with reprex v2.0.2}

Input data:

clin.info <-
structure(list(Sample.ID = c("TCGA.B2.3924.01", "TCGA.B2.3924.01", 
"TCGA.B2.3924.01", "TCGA.B2.3924.01", "TCGA.B2.5635.01", "TCGA.B2.5635.01", 
"TCGA.B2.5635.01", "TCGA.B2.5635.01", "TCGA.B2.5635.01", "TCGA.B2.5635.01", 
"TCGA.A3.3357.01", "TCGA.A3.3357.01", "TCGA.A3.3367.01", "TCGA.A3.3367.01", 
"TCGA.A3.3387.01", "TCGA.A3.3387.01", "TCGA.B0.4698.01", "TCGA.B0.4698.01", 
"TCGA.B0.4710.01", "TCGA.B0.4710.01"), age = c("73", "73", "73", 
"73", "74", "74", "74", "74", "74", "74", "62", "62", "72", "72", 
"49", "49", "75", "75", "75", "75")), row.names = c(67L, 68L, 
69L, 70L, 71L, 72L, 73L, 74L, 75L, 76L, 1L, 2L, 3L, 4L, 5L, 6L, 
7L, 8L, 9L, 10L), class = "data.frame")

I think you can use below code:

dedup <- clin.info %>%
  group_by(Sample.ID) %>%
  filter(n() > 2) %>%
  distinct() %>% ungroup()

if (dim(dedup)[1] >0) {
    result <- clin.info %>%
    filter(!(Sample.ID  %in% dedup$Sample.ID)) %>%
    bind_rows(dedup)
}