• EDIT* 使用新数据，尝试重建distinct之后的组。如果这不是真实的的数据，则该方法可能随时失败，因为需求是不对称的。

df %>% 
  distinct(Contrast, .keep_all=T) %>% 
  rowwise() %>% 
  mutate(uniqCon = sum(unique(Contrast) == df$Contrast)) %>% 
  ungroup() %>% 
  mutate(uniqCon = min(uniqCon), 
         Group = LETTERS[which(LETTERS == Group[1]):
          (which(LETTERS == Group[1])+(uniqCon[1]-1))], .by = Group) %>% 
  select(-uniqCon)
# A tibble: 7 × 2
  Group Contrast
  <chr> <chr>   
1 A     X-Y     
2 B     X-Z     
3 C     Y-Z     
4 D     N-M     
5 D     R-S     
6 D     R-O     
7 E     X-S

数据

df <- structure(list(Group = c("A", "A", "A", "B", "B", "B", "C", "C", 
"C", "D", "D", "D", "E", "E", "E"), Contrast = c("X-Y", "X-Z", 
"Y-Z", "X-Y", "X-Z", "Y-Z", "X-Y", "X-Z", "Y-Z", "N-M", "R-S", 
"R-O", "N-M", "R-S", "X-S")), class = "data.frame", row.names = c(NA, 
-15L))

• 老办法 *

类似这样的东西，使用cur_group_id()

library(dplyr)

df %>% 
  summarize(Contrast = Contrast[cur_group_id()], .by = Group)
  Group Contrast
1     A      X-Y
2     B      X-Z
3     C      Y-Z