通过直接引用组来丢弃group_之后的最后一个或第一个组

我假设你不应该假设我们事先知道团队的数量。尝试使用 labels

 all_but_last <- df %>% group_by(A) %>% attr("labels") %>% head(-1)
  A
1 a
2 b

…提取所需行

 > df %>% filter(A %in% all_but_last[[1]])
  A            B
1 a -0.799026840
2 a -0.712402478
3 a  0.685320094
4 b  0.971492883
5 b -0.001479117
6 b -0.817766296

有助于使用 dput 查看“grouped_df”的实际内容:

dput( df %>% group_by(A) )
structure(list(A = c("a", "a", "a", "b", "b", "b", "c", "c", 
"c"), B = c(-0.799026840397576, -0.712402478350695, 0.685320094252465, 
0.971492883452258, -0.00147911717469651, -0.817766295631676, 
-1.00112471676908, 1.88145909873596, -0.305560178617216)), .Names = c("A", 
"B"), row.names = c(NA, -9L), class = c("grouped_df", "tbl_df", 
"tbl", "data.frame"), vars = "A", drop = TRUE, indices = list(
    0:2, 3:5, 6:8), group_sizes = c(3L, 3L, 3L), biggest_group_size = 3L, 
 labels = structure(list(
                       A = c("a", "b", "c")), 
                       row.names = c(NA, -3L), 
                       class = "data.frame", 
                       vars = "A", drop = TRUE, .Names = "A"))

请注意,标签是数据。框架,以便您可以进一步应用 unlist 结果变成了 all_but_last 然后你就不需要用 "[["

library(dplyr)
df %>%
  group_by(A) %>% 
  group_indices(.) %in% 1:2 %>%
  df[.,] 

或与 data.table

library(data.table)
setDT(df)[,  grp := .GRP, A][grp %in% unique(grp)[1:2]][, grp := NULL][]