r - 如何根据条件删除数据框的 N 行

Question

我的问题来自 How to find tail rows of a data frame that satisfy set criteria?因此，我的(更新的)示例数据的结构如下:

Individ <- data.frame(Participant = c("Bill", "Bill", "Bill", "Bill", "Bill", "Jane", "Jane", "Jane", "Jane", "Jane", "Jane", "Jane", "Jane", "Jane", "Jane", "Jane", "Jane", "Bill", "Bill", "Bill", "Bill"),  
                      Time = c(1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4),
                      Condition = c("Placebo", "Placebo", "Placebo", "Placebo", "Placebo", "Expr", "Expr", "Expr", "Expr", "Expr", "Expr", "Placebo", "Placebo", "Placebo", "Placebo", "Placebo", "Placebo", "Expr", "Expr", "Expr", "Expr"),
                      Location = c("Home", "Home", "Home", "Home", "Home", "Home", "Home", "Home", "Home", "Home", "Home", "Home", "Home", "Home", "Home", "Home", "Home", "Away", "Away", "Away", "Away"),
                      Power = c(400, 250, 180, 500, 300, 600, 512, 300, 500, 450, 200, 402, 210, 130, 520, 310, 451, 608, 582, 390, 570))

我学会了根据每个 Participant 最后一次出现的 在不同的 Condition 加上 Location 中找到尾行电源。我现在希望针对每个 Condition 和 Location 从每个 Participant 中删除最后 3 行。但是，为每个 Participant 和 Condition 收集的 Time 不同，因此我不能完全基于标准化的 Time 。

如何快速遍历每个 Participant 及其各自的 Condition 加上 Location 并删除最后 3 行？我的实际数据框是 400 万行 + 超过 50 个参与者，因此理想情况下，迭代每个 Participant 和 Condition 的解决方案将是可取的。

我的预期输出是:

Output <- data.frame(Participant = c("Bill", "Bill", "Jane", "Jane", "Jane", "Jane", "Jane", "Jane", "Bill"),
                     Time = c(1, 2, 1, 2, 3, 1, 2, 3, 1),
                     Condition = c("Placebo", "Placebo", "Expr", "Expr", "Expr", "Placebo", "Placebo", "Placebo", "Expr"),
                     Location = c("Home", "Home", "Home", "Home", "Home", "Home", "Home", "Home", "Away"),
                     Power = c(400, 250, 600, 512, 300, 402, 210, 130, 608))

Answer 1

如果你使用dplyr，用row_number()和n()...

library(dplyr)
Individ %>%
  group_by(Participant, Condition, Location) %>%
  filter(row_number() < n() - 2)

返回

Source: local data frame [9 x 5]
Groups: Participant, Condition, Location [4]

  Participant  Time Condition Location Power
       (fctr) (dbl)    (fctr)   (fctr) (dbl)
1        Bill     1   Placebo     Home   400
2        Bill     2   Placebo     Home   250
3        Jane     1      Expr     Home   600
4        Jane     2      Expr     Home   512
5        Jane     3      Expr     Home   300
6        Jane     1   Placebo     Home   402
7        Jane     2   Placebo     Home   210
8        Jane     3   Placebo     Home   130
9        Bill     1      Expr     Away   608