避免在data.frame中折叠具有多个因子的变量时避免嵌套嵌套

CAO*_*AOC 1 for-loop r sapply

我有一个具有多个因素和多个数值变量的数据框。我想瓦解其中一个因素(平均而言)。

在我的尝试中,我只能想到嵌套的sapply或for循环以隔离要求平均值的数值元素。

var <- data.frame(A = c(rep('a',8),rep('b',8)), B = 
c(rep(c(rep('c',2),rep('d',2)),4)), C = c(rep(c('e','f'),8)),
                  D = rnorm(16), E = rnorm(16))
> var
   A B C           D           E
1  a c e  1.1601720731 -0.57092435
2  a c f -0.0120178626  1.05003748
3  a d e  0.5311032778  1.67867806
4  a d f -0.3399901000  0.01459940
5  a c e -0.2887561691 -0.03847519
6  a c f  0.0004299922 -0.36695879
7  a d e  0.8124655890  0.05444033
8  a d f -0.3777058654  1.34074427
9  b c e  0.7380720821  0.37708543
10 b c f -0.3163496271  0.10921373
11 b d e -0.5543252191  0.35020193
12 b d f -0.5753686426  0.54642790
13 b c e -1.9973216646  0.63597405
14 b c f -0.3728926714 -3.07669300
15 b d e -0.6461596329 -0.61659041
16 b d f -1.7902722068 -1.06761729


sapply(4:ncol(var), function(i){
  sapply(1:length(levels(var$A)), function(j){
    sapply(1:length(levels(var$B)), function(t){
      sapply(1:length(levels(var$C)), function(z){
        mean(var[var$A == levels(var$A)[j] & 
var$B == levels(var$B)[t] & 
var$C == levels(var$C)[z],i])
      })
    })
  })
})

             [,1]       [,2]
[1,]  0.435707952 -0.3046998
[2,] -0.005793935  0.3415393
[3,]  0.671784433  0.8665592
[4,] -0.358847983  0.6776718
[5,] -0.629624791  0.5065297
[6,] -0.344621149 -1.4837396
[7,] -0.600242426 -0.1331942
[8,] -1.182820425 -0.2605947
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没有这么多人,有没有办法做到这一点?也许与mapply或外部

jor*_*ran 5

也许就是

var <- data.frame(A = c(rep('a',8),rep('b',8)), B = 
                    c(rep(c(rep('c',2),rep('d',2)),4)), C = c(rep(c('e','f'),8)),
                  D = rnorm(16), E = rnorm(16))

library(dplyr)
var %>%
  group_by(A,B,C) %>%
  summarise_if(is.numeric,mean)
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(请注意,您显示的输出不是我运行您的apply代码时得到的结果,但以上内容与我运行您的sapply代码时得到的结果相同。)