R 每行最多可随机删除3个元素

我想在包含五列的数据集中，每行随机删除最多三个元素。下面是

R

代码，我认为可以这样做，但它最多允许删除一行中的所有五个元素。这似乎很基本，但我找不到错误。谢谢你的建议

set.seed(1234)

  # create matrix to contain flags identifying elements to be deleted
  delete.these <- matrix(0, nrow=10, ncol=5)

  for(i in 1:nrow(delete.these)) {

      # for each row randomly select the order of the columns 
      # to be tested for deletion 
      rcols <- sample(5, 5, replace = FALSE)

      for(j in 1:ncol(delete.these)) {

           # select a random draw
           delete.it <- runif(1,0,1)

           # if random draw is below specified threshold and fewer than three
           # elements have already been deleted from the row then delete element
           if((delete.it <= 0.7) & sum(delete.these[i,1:5] <= 2)) { delete.these[i,rcols[j]] = 1}
           if((delete.it >  0.7) | sum(delete.these[i,1:5] >= 3)) { delete.these[i,rcols[j]] = 0}

      }
  }

  delete.these

set.seed（1234）
#创建包含标识要删除元素的标志的矩阵
删除。这些而不是使用
runif（）
尝试直接绘制索引

delete.these <- matrix(0, nrow=10, ncol=5)
for (i in 1:NROW(delete.these)){
   delete.these[i,sample.int(5,sample.int(4,1)-1)] <- 1
}
delete.these
      [,1] [,2] [,3] [,4] [,5]
 [1,]    1    1    1    0    0
 [2,]    0    0    0    0    0
 [3,]    0    1    0    1    1
 [4,]    0    1    1    0    1
 [5,]    1    0    1    0    0
 [6,]    0    0    0    0    0
 [7,]    1    0    1    0    0
 [8,]    0    1    0    1    1
 [9,]    0    1    1    0    0
[10,]    1    0    1    0    1

delete.this使用两列矩阵作为
[谢谢，但我不希望每行删除三个元素。我希望每行最多删除三个元素。Oops。好的，将代码更新为最多选择3个。仍然不需要
runif（）
谢谢！这是漫长的一天。我还需要删除原始帖子中的第二条
if
语句。它会覆盖第一条
if
语句的输出。在您的示例中，每行有三个删除的元素。我希望每行最多删除三个元素。一行可以删除0、1、2或3个元素。
 sum(delete.these[i,1:5] <= 2)

 sum(delete.these[i,1:5]) <= 2

 dfrm <- data.frame(a1=rnorm(20), a2=rnorm(20),a3=rnorm(20),
                     a4=rnorm(20),a5=rnorm(20))
 dfrm[ matrix( c( rep(1:20,each=3),
                  replicate(20,  {sample(5, 3)} ) ), ncol=2) ] <- NA

> dfrm
           a1          a2            a3          a4         a5
1          NA  0.70871541            NA          NA -0.6922827
2   1.9846227  1.70592512            NA          NA         NA
3   0.2684487          NA  0.0008968694          NA         NA
4          NA          NA  0.5546355410  0.07399188         NA
5          NA  0.82324761 -0.0410918599          NA         NA
6          NA          NA -1.0715205164          NA -0.1683819
7   0.0933059          NA            NA          NA  1.3129301
8          NA  0.79382695  0.1877369725          NA         NA
9   0.3124101          NA            NA -1.22087347         NA
10 -0.1657043          NA            NA  1.36626832         NA
11         NA -0.06095247 -0.9622792102          NA         NA
12         NA -1.29243386 -1.2133819819          NA         NA
13 -0.0886702          NA            NA  0.37495775         NA
14  1.0812527 -1.54215156            NA          NA         NA
15         NA -0.24765627            NA  0.81374405         NA
16         NA  0.21307051            NA          NA -0.6825013
17 -0.4129100          NA            NA          NA -0.9844177
18         NA  1.95881167  0.7977172969          NA         NA
19         NA          NA  0.0953287645          NA  1.7067591
20         NA          NA -0.1057690912  0.73408897         NA

idx <- sapply(1:20, function(x) {n<- sample(1:5, sample(1:3,1)) 
                       matrix( c(rep(x,length(n)), n), ncol=2) }) # list
idx <- do.call(rbind, idx) # now a 2 col matrix

dfrm[ idx] <- NA

>     idx <- sapply(1:20, function(x) {n<- sample(1:5, sample(1:3,1)) 
+                            matrix( c(rep(x,length(n)), n), ncol=2) }) # list
>     idx <- do.call(rbind, idx) # now a 2 col matrix
> 
>     dfrm[ idx] <- NA
> 
> dfrm
             a1         a2         a3          a4         a5
1  -0.048776740         NA  1.1879195 -0.23142932 -3.6185891
2            NA  0.4613289 -0.4532400 -0.85891682 -2.2034714
3            NA         NA  1.1191833  1.12545821         NA
4   0.646399767 -0.7126735  2.9474470  0.36358070         NA
5  -0.630929314  1.3770828         NA          NA  1.3987857
6            NA         NA         NA  1.06680025  0.4445383
7   0.484728630         NA  0.7382064          NA  0.9838159
8  -1.558031074  1.1630888         NA          NA         NA
9  -0.968887379 -0.7330051         NA  0.04621124 -0.9785049
10  0.935436533         NA         NA -1.07365274         NA
11           NA  0.2529093         NA -1.38643245 -1.3389529
12           NA -0.2639166 -0.2301257          NA         NA
13  2.026646586 -0.2452684         NA -0.30346521         NA
14  0.522717033         NA         NA  1.25870278         NA
15           NA         NA -0.9934046 -0.89009964 -0.8403772
16           NA         NA  0.0987765 -0.98608109  1.4646301
17           NA  0.7693064 -0.9326388 -0.16240266         NA
18 -0.005393965         NA         NA          NA -0.8111057
19           NA  1.6241122 -1.1376916  0.15812435         NA
20           NA         NA         NA  0.71059666  0.5170046