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r - lapply 并应用于列表 R 的每个组件和元素

问题描述

我有这个清单：

lst

lst <- list(a=c(2.5,9.8,5.0,6.7,6.5,5.2,34.4, 4.2,39.5, 1.3,0.0,0.0,4.1,0.0,0.0,25.5,196.5, 0.0,104.2,0.0,0.0,0.0,0.0,0.0),b=c(147.4,122.9,110.2,142.3))

我想为列表的每个值和列表的每个元素（a和b）计算 z.score 为： (x[i]-mean(x)/sd(x)，其中 x 是列表中每个元素的所有值（togheter）和 x[i] 每个单个组件每个列表元素。我试过了lapply

lapply(lst,function (x) as.data.frame(apply(x,2, function(y)- lapply(lst,mean)/lapply(lst,sd))))

但有一个错误......也许for循环为：

lst.new <- vector("list",1)

for (i in 1:length(lst)){
  for (j in 1:dim(data.frame(lst[i]))[1]){
    res[j] <- (as.numeric(unlist(lst[i]))[j]-mean(as.numeric(unlist(lst[i])))/
      sd(as.numeric(unlist(lst[i])))
    lst.new[[i]] <- res
  }
}

但结果很奇怪（肯定我在lst.new输出中错了）：

[[1]]
 [1] -0.3635464 -0.1982809 -0.3069486 -0.2684621 -0.2729899 -0.3024208  0.3586413 -0.3250599  0.4741007 -0.3907133
[11] -0.4201442 -0.4201442 -0.3273238 -0.4201442 -0.4201442  0.1571532  4.0284412 -0.4201442  1.9388512 -0.4201442
[21] -0.4201442 -0.4201442 -0.4201442 -0.4201442

[[2]]
 [1]  0.9671130 -0.4517055 -1.1871746  0.6717671 -0.2729899 -0.3024208  0.3586413 -0.3250599  0.4741007 -0.3907133
[11] -0.4201442 -0.4201442 -0.3273238 -0.4201442 -0.4201442  0.1571532  4.0284412 -0.4201442  1.9388512 -0.4201442
[21] -0.4201442 -0.4201442 -0.4201442 -0.4201442

预期结果可以是具有不同长度的列表或数据框：

 a       b
   -0.36    0.967113
  -0.19     -0.45
    [...]  [...]

等等... 

P.S: 
 0.36 == (2.5- mean(unlist(lst[1])))/sd(unlist(lst[1]))
 0.967113 == (147.4 -mean(unlist(lst[2])))/sd(unlist(lst[2]))

我最好使用lapply（或他的家庭功能）并解决问题

标签： rlistdataframelapply

解决方案

根据输入和预期输出，scale应该可以工作

lapply(lst, scale)

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