根据条件分区data.frame

Question

我有一个 data.frame 形状像：

c <- data.frame(name=c("a", "a", "b", "b", "c", "c","d","d"), value=c(1,3,2,4,5,3,4,5), address=c("rrrr","rrrr","zzzz","aaaa","ssss","jjjj","qqqq","qqqq"))
> c
  name value address
1    a     1    rrrr
2    a     3    rrrr
3    b     2    zzzz 
4    b     4    aaaa
5    c     5    ssss
6    c     3    jjjj
7    d     4    qqqq
8    d     5    qqqq

我试图根据一个简单的规则将这个数据框分成两个单独的数据框：将没有更改地址的人分组在一起，将更改地址的人分组在一起。关于如何完成任务的任何提示？

到目前为止，我正在玩，没有用，有：

for(i in seq(1,8, by=2)){
    print(i)
    print(unlist(c[which(c[i,3]==c[(i+1),3]),]))    
}

Answer 1

使用 dplyr:

library(dplyr)
z<-c %>% group_by(name) %>% 
         mutate(changed = n_distinct(address))
split(z, z$changed)

感谢@akrun 提醒我n_distinct

Answer 2

@jeremycg 的回答很好，我正在尝试学习 dplyr，但这里也有非 dplyr 版本。

numAddresses <- sapply(split(c, c$name), function(x)
    length(unique(x$address)))
split(c, numAddresses[c$address])

Answer 3

这会计算地址的数量并在此基础上拆分。有一个障碍需要克服，它与总是从 ave 得到 <NA> 直到使用 as.character 有关。有一条警告消息，我正在从中复制开头，因此搜索者可能会找到这个：

Warning messages:
1: In `[<-.factor`(`*tmp*`, i, value = c(1L, 1L)) :

成功版本（使用名为cc的数据对象）：

 split(cc,  ave(as.character(cc$address), cc$name, FUN=function(x) sum(!duplicated(x)) ) )

$`1`
  name value address
1    a     1    rrrr
2    a     3    rrrr
7    d     4    qqqq
8    d     5    qqqq

$`2`
  name value address
3    b     2    zzzz
4    b     4    aaaa
5    c     5    ssss
6    c     3    jjjj

如果你真的想要二分法，那么用 > 1:

转换成逻辑法

 split(cc, ave(as.character(cc$address), cc$name, FUN=function(x) sum(!duplicated(x)) ) >1)

$`FALSE`
  name value address
1    a     1    rrrr
2    a     3    rrrr
7    d     4    qqqq
8    d     5    qqqq

$`TRUE`
  name value address
3    b     2    zzzz
4    b     4    aaaa
5    c     5    ssss
6    c     3    jjjj

我不明白评论。这就是我得到的 str(dat):

List of 2
 $ FALSE:'data.frame':  4 obs. of  3 variables:
  ..$ name   : Factor w/ 4 levels "a","b","c","d": 1 1 4 4
  ..$ value  : num [1:4] 1 3 4 5
  ..$ address: Factor w/ 6 levels "aaaa","jjjj",..: 4 4 3 3
 $ TRUE :'data.frame':  4 obs. of  3 variables:
  ..$ name   : Factor w/ 4 levels "a","b","c","d": 2 2 3 3
  ..$ value  : num [1:4] 2 4 5 3
  ..$ address: Factor w/ 6 levels "aaaa","jjjj",..: 6 1 5 2

根据条件分区data.frame

Partitioning data.frame according to condition

partitioning

r