根据条件计算变量的最高百分比

Question

样本数据结构如下：

Individ <- data.frame(Participant = c("Bill", "Bill", "Bill", "Bill", "Bill", "Bill", "Bill", "Bill", "Bill", "Bill", "Bill", "Bill", 
                                      "Harry", "Harry", "Harry", "Harry", "Harry", "Harry", "Harry", "Harry", "Harry", "Harry", "Harry", "Harry"),
                      Time = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12),
                      Power = c(400, 250, 180, 500, 300, 450, 600, 512, 300, 500, 450, 200, 402, 210, 130, 520, 310, 451, 608, 582, 390, 570, NA, NA))

我计算了两秒、三秒和四秒的滚动平均值 Power。我知道我可以通过执行以下操作对每个滚动平均值进行子集化（考虑 Participant 的变化）：

Individ$TwoSec <- ave(Individ$Power, Individ$Participant, 
                          FUN= function(x) rollapply(x, 2, mean, na.rm = TRUE, fill = NA) )
Individ$ThreeSec <- ave(Individ$Power, Individ$Participant, 
                          FUN= function(x) rollapply(x, 3, mean, na.rm = TRUE, fill = NA) )
Individ$FourSec <- ave(Individ$Power, Individ$Participant, 
                            FUN= function(x) rollapply(x, 4, mean, na.rm = TRUE, fill = NA) )

我现在希望为每个滚动平均值（TwoSec、ThreeSec 和 FourSec）找到 Power 的前 5%。我该怎么做才能解释 Name 的变化并进行计算？

我的实际 data.frame 超过 300 万行，因此最好有一个快速的解决方案。

Answer 1

我们可以试试

library(data.table)
library(RcppRoll)
setDT(Individ)[, lapply(2:4, function(n) {
      r1 <- roll_mean(Power, n, fill=NA)
      r2 <- r1[order(-r1)]
      r2[seq(ceiling(.N*0.05))]}) ,  by = Participant]

根据条件计算变量的最高百分比

Calculate top % of variable according to condition

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