克隆ConcurrentHashMap(Cloning ConcurrentHashMap)

 您要做的第一件事是创建一个空数据帧。 其次，您需要使用for循环在此数据帧中写入，而不是直接打印出结果。 此外，您不希望在已经使用i的for循环中使用包含i作为变量的for循环。 我建议你尝试以下方法： 
 
data <- rep(1:3, times = c(10,4,6))
datafr <- data.frame(Sample=rep(NA,5),Probability.Dist=rep(NA,5))
for(i in 1:5) {
  samp <- sample(data, 4)
  data <- exclude(data, samp)
  datafr$Sample[i] <- samp[1]*1000+samp[2]*100+samp[3]*10+samp[4] #easy way of getting your wanted sample layout

  prsamp <- rep(0,3)
  for(j in 1:3) {
        prsamp[j] <- sum(samp == j)/4
  }
  datafr$Probability.Dist[i] <- toString(prsamp)

  if (length(data) == 0) {
        break
  }
}
datafr
#  Sample Probability.Dist
#1   1231  0.5, 0.25, 0.25
#2   2132  0.25, 0.5, 0.25
#3   1313      0.5, 0, 0.5
#4   2111    0.75, 0.25, 0
#5   3131      0.5, 0, 0.5
 
 我还必须建议您不要在数据帧的单个列中使用3个值。 为了进一步分析甚至可读性，最好将每个值赋予它自己的列。 

The first thing you will have to do is create an empty dataframe. Secondly, you will want your for loop to write in this dataframe instead of simply printing out the results directly. Also, you don't want to use a for loop containing i as variable in a for loop already using i. I suggest you try the following:
 
data <- rep(1:3, times = c(10,4,6))
datafr <- data.frame(Sample=rep(NA,5),Probability.Dist=rep(NA,5))
for(i in 1:5) {
  samp <- sample(data, 4)
  data <- exclude(data, samp)
  datafr$Sample[i] <- samp[1]*1000+samp[2]*100+samp[3]*10+samp[4] #easy way of getting your wanted sample layout

  prsamp <- rep(0,3)
  for(j in 1:3) {
        prsamp[j] <- sum(samp == j)/4
  }
  datafr$Probability.Dist[i] <- toString(prsamp)

  if (length(data) == 0) {
        break
  }
}
datafr
#  Sample Probability.Dist
#1   1231  0.5, 0.25, 0.25
#2   2132  0.25, 0.5, 0.25
#3   1313      0.5, 0, 0.5
#4   2111    0.75, 0.25, 0
#5   3131      0.5, 0, 0.5
 
I also have to advise you against using 3 values in a single column of a dataframe. For further analysis and even readability, it would be much preferred to give each value it's own column.