删除依赖于因子的重复行

Question

我想从由不同的fators和条件分层的数据帧中删除重复的行,例如最高均值或sd.

一些数据a是行的因子和id.

set.seed(13654)
a<- sort(c(1,1,4,1,2,3,2,3,1,5))
b<- matrix(runif(100,min = 6,max = 14),nrow = 10)
c<- data.frame(a,b)  

例如,我想减少具有最高平均值的行上的最终数据集.

# calculate means per row
gr <- cbind(a,M=rowMeans(c[,-1]))
# get rows stratified by a with highest mean:
gr1 <- aggregate(M~a,gr,which.max)
gr1
  a M
1 1 3
2 2 2
3 3 1
4 4 1
5 5 1

因此,因子级别1的第三行,因子级别2的第二行......应该包括在新数据帧中.我想避免循环.我尝试的是split数据,然后使用lapply,但到目前为止没有工作.

cl <- split(c,a)
# this function does not work it will select not the correct rows. 
lapply(cl, "[", gr1, )

我的最终目标是这样的功能:

remove.dupl <- function(data,factor,method=c(highest.mean,highest.sd,lowest.sd,...))

你能为我的问题提供一些tipps或解决方案吗？按照我的工作流程,我需要一个"操作方法"来"["正确使用lapply从数据帧列表中选择不同的行.

Answer 1

使用data.table包，我将按如下方式处理它：

library(data.table)
# method 1:
setDT(cc)[, `:=` (rn = 1:.N, wm = which.max(rowMeans(.SD))), a][rn==wm]
# method 2:
setDT(cc)[, wm := frank(1/rowMeans(.SD), ties.method="first"), a][wm==1]

这使：

   a        X1        X2        X3        X4        X5        X6        X7        X8       X9       X10 wm rn
1: 1 13.946254  7.302729  9.406389  8.924367  8.129423 10.174735  6.547805 11.618872 12.84100  9.494790  3  3
2: 2 13.606555 12.798149 11.261258 12.991822 12.875935 11.199411  8.551149 10.377451 13.63219 13.643163  2  2
3: 3  6.820769 13.748507 11.630297 11.559873  6.196406  8.925419 11.230415 10.584249 10.41442  6.821673  1  1
4: 4  8.418767 10.673998  6.693021 11.101287  7.855519  9.106210 12.279536  6.925023  6.92334 10.279204  1  1
5: 5 11.529072  7.940031 10.746172  8.535466 13.703122 12.294424 11.362498 11.256843 13.95535 13.264835  1  1

在基本 R 中你可以这样做：

cc$rm <- apply(cc[,-1], 1, mean)
cc$wm <- ave(cc$rm, cc$a, FUN = function(x) max(x)==x)
cc[cc$wm == 1,]

这使：

   a        X1        X2        X3        X4        X5        X6        X7        X8       X9       X10        rm wm
3  1 13.946254  7.302729  9.406389  8.924367  8.129423 10.174735  6.547805 11.618872 12.84100  9.494790  9.838637  1
6  2 13.606555 12.798149 11.261258 12.991822 12.875935 11.199411  8.551149 10.377451 13.63219 13.643163 12.093708  1
7  3  6.820769 13.748507 11.630297 11.559873  6.196406  8.925419 11.230415 10.584249 10.41442  6.821673  9.793203  1
9  4  8.418767 10.673998  6.693021 11.101287  7.855519  9.106210 12.279536  6.925023  6.92334 10.279204  9.025591  1
10 5 11.529072  7.940031 10.746172  8.535466 13.703122 12.294424 11.362498 11.256843 13.95535 13.264835 11.458781  1

回应您的评论：作为替代方案，您可以使用rank里面的函数ave：

# duplicate the row for which 'max(x)==x' for the first group
cc <- rbind(cc,cc[3,])

cc$wm2 <- ave(cc$rm, cc$a, FUN = function(x) rank(-x, ties.method = "first"))
cc[cc$wm2 == 1,]

这使：

   a        X1        X2        X3        X4        X5        X6        X7        X8       X9       X10        rm wm wm2
3  1 13.946254  7.302729  9.406389  8.924367  8.129423 10.174735  6.547805 11.618872 12.84100  9.494790  9.838637  1   1
6  2 13.606555 12.798149 11.261258 12.991822 12.875935 11.199411  8.551149 10.377451 13.63219 13.643163 12.093708  1   1
7  3  6.820769 13.748507 11.630297 11.559873  6.196406  8.925419 11.230415 10.584249 10.41442  6.821673  9.793203  1   1
9  4  8.418767 10.673998  6.693021 11.101287  7.855519  9.106210 12.279536  6.925023  6.92334 10.279204  9.025591  1   1
10 5 11.529072  7.940031 10.746172  8.535466 13.703122 12.294424 11.362498 11.256843 13.95535 13.264835 11.458781  1   1

注意：我将数据框重命名为，cc因为最好不要使用函数名称作为数据框的名称