Question

我正在处理一个大数据集，并且在数据清理方面遇到了问题。我的数据集如下所示：

data <- cbind (group = c(1,1,1,2,2,3,3,3,4,4,4,4,4), 
               member = c(1,2,3,1,2,1,2,3,1,2,3,4,5), 
               score = c(0,1,0,0,0,1,0,1,0,1,1,1,0))

我只想保留得分总和等于1的组，并删除得分总和等于0的整个组。对于得分总和大于1的组例如，得分总和= 3，我想随机选择两个得分等于1的组成员，并从组中删除它们。然后数据可能如下所示：

newdata <- cbind (group = c(1,1,1,3,3,4,4,4), 
                  member = c(1,2,3,2,3,1,3,5), 
                  score = c(0,1,0,0,1,0,1,0))

有人可以帮我完成这件事吗？

Answer 1

我会定义一个能够达到你想要的功能。然后使用ddply并按group分割。

myfun <- function(x) {
  if(sum(x$score)==1) {
    return(x)
  } else if(sum(x$score)==0) {
    return(data.frame())
  } else {
    row.names(x) <- NULL
    score.1 <- sample(as.integer(row.names(x[x$score==1,])), nrow(x[x$score==1,])-1)
    return(x[-score.1,])
  }
}

library(plyr)
ddply(as.data.frame(dat), .(group), myfun)

  group member score
1     1      1     0
2     1      2     1
3     1      3     0
4     3      1     1
5     4      1     0
6     4      2     1
7     4      3     1

Answer 2

我会编写一个功能，结合各种操作。这是一个这样的功能，评论很多：

process <- function(x) {
    ## this adds a vector with the group sum score
    x <- within(x, sumScore <- ave(score, group, FUN = sum))
    ## drop the group with sumScore == 0
    x <- x[-which(x$sumScore == 0L), , drop = FALSE]
    ## choose groups with sumScore > 1
    ## sample sumScore - 1 of the rows where score == 1L
    foo <- function(x) {
        scr <- unique(x$sumScore) ## sanity & take only 1 of the sumScore
        ## which of the grups observations have score = 1L
        want <- which(x$score == 1L)
        ## want to sample all bar one of these
        want <- sample(want, scr-1)
        ## remove the selected rows & retun
        x[-want, , drop = FALSE]
    }
    ## which rows are samples with group sumScore > 1
    want <- which(x$sumScore > 1L)
    ## select only those samples, split up those samples by group, lapplying foo
    ## to each group, then rbind the resulting data frames together
    newX <- do.call(rbind,
                    lapply(split(x[want, , drop = FALSE], x[want, "group"]),
                           FUN = foo))
    ## bind the sampled sumScore > 1L on to x (without sumScore > 1L)
    newX <- rbind(x[-want, , drop = FALSE], newX)
    ## remove row labels
    rownames(newX) <- NULL
    ## return the data without the sumScore column
    newX[, 1:3]
}

与您的数据相关：

dat <- data.frame(group = c(1,1,1,2,2,3,3,3,4,4,4,4,4), 
                  member = c(1,2,3,1,2,1,2,3,1,2,3,4,5), 
                  score = c(0,1,0,0,0,1,0,1,0,1,1,1,0))

给出：

> set.seed(42)
> process(dat)
  group member score
1     1      1     0
2     1      2     1
3     1      3     0
4     3      1     1
5     3      2     0
6     4      1     0
7     4      3     1
8     4      5     0

我认为我想要的是什么。

更新：在上面process()中，内部函数foo()可以重写为仅采样1行并删除其他行。即用下面的foo()替换foo <- function(x) { scr <- unique(x$sumScore) ## sanity & take only 1 of the sumScore ## which of the grups observations have score = 1L want <- which(x$score == 1L) ## want to sample just one of these want <- sample(want, 1) ## return the selected row & retun x[want, , drop = FALSE] }：

foo()

它们本质上是相同的操作，但只选择1行的scr-1使预期的行为显式化;我们想从得分== 1L的那些中随机选择1行，而不是样本{{1}}值。

Answer 3

ugroups<-unique(data[,1])
scores<-sapply(ugroups,function(x){sum(data[,1]==x & data[,3]==1)})
data[data[,1]%in%ugroups[scores>0],]
....... etc

将为您提供每组等的累积分数

删除整个组或组成员

3 个答案: