r-来自子/父关系的分层数据帧 [英] r - hierarchical data frame from child/parent relations

问题描述

我有一个孩子-父data.frame，我想将其转换为具有所有级别和级别编号的完整层次结构列表.下面的示例数据分为三个级别，但可能更多.我可以使用什么函数来转换数据?

I have a child - parent data.frame that I want to transform to a complete hierarchical list with all levels and a level number. The example data below goes to three levels, but it could be more. What function can I use to transform the data?

来源:

data.frame(name = c("land", "water", "air", "car", "bicycle", "boat", "balloon",
  "airplane", "helicopter", "Ford", "BMW", "Airbus"), parent = c(NA, NA, NA, 
  "land", "land", "water", "air", "air", "air", "car", "car", "airplane"))

         name   parent
1        land     <NA>
2       water     <NA>
3         air     <NA>
4         car     land
5     bicycle     land
6        boat    water
7     balloon      air
8    airplane      air
9  helicopter      air
10       Ford      car
11        BMW      car
12     Airbus airplane

目的地:

data.frame(level1 = c("land", "water", "air", "land", "land", "water", "air", 
  "air", "air", "land", "land", "air"), level2 = c(NA, NA, NA, "car", "bicylcle", 
  "boat", "balloon", "airplane", "helicopter", "car", "car", "airplane"),
  level3 = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, "Ford", "BMW", "Airbus"), 
  level_number = c(1, 1, 1, 2, 2, 2, 2, 2, 2, 3, 3, 3))

   level1     level2 level3 level_number
1    land       <NA>   <NA>            1
2   water       <NA>   <NA>            1
3     air       <NA>   <NA>            1
4    land        car   <NA>            2
5    land   bicylcle   <NA>            2
6   water       boat   <NA>            2
7     air    balloon   <NA>            2
8     air   airplane   <NA>            2
9     air helicopter   <NA>            2
10   land        car   Ford            3
11   land        car    BMW            3
12    air   airplane Airbus            3

推荐答案

使用data.table您可以执行以下操作:

Usind data.table you can do the following:

require(data.table)
l <- list() # initialize empty list
setDT(dat) 
setkey(dat, parent) # setting up the data as keyed data.table
current_lvl <- dat[is.na(parent), .(level_number = 1), keyby=.(level1 = name)]

不是 current_lvl 看起来如下(由level1键控)

By not current_lvl looks as follows (keyed by level1)

   level1 level_number
1:    air            1
2:   land            1
3:  water            1

现在的诀窍是加入 dat 和 current_lvl 并适当地修改结果:

The trick is now to join dat and current_lvl and modify the result appropriately:

  current_lvl <- current_lvl[dat][ # Join the data.tables
!is.na(level_number)][ #exclude non-child-rows
  ,level_number := level_number + 1] # increment level_number
setnames(current_lvl, "name", paste0("level",ind+1)) # rename column
setkeyv(current_lvl, paste0("level",ind+1)) # set key

哪个给你(由level2键控)

Which gives you (keyed by level2)

   level1 level_number     level2
1:    air            2   airplane
2:    air            2    balloon
3:   land            2    bicycle
4:  water            2       boat
5:   land            2        car
6:    air            2 helicopter

按如下所示将其置于while循环中工作:

Put this to work in a while-loop as follows:

while(nrow(current_lvl) > 0){
  ind <- length(l) + 1
  l[[ind]] <- current_lvl
  current_lvl <- current_lvl[dat][!is.na(level_number)][,level_number := level_number + 1]
  if(nrow(current_lvl) == 0L){
    break
  }
  setnames(current_lvl, "name", paste0("level",ind+1))
  setkeyv(current_lvl, paste0("level",ind+1))
}

您可以查看 l 来查看结果.通过rbindlist将此组合在一起，即可满足您的需求

You can have a look at l to see the outcome. Combining this via rbindlist gives you what you desire

res <- rbindlist(l, fill=TRUE)
setcolorder(res, sort(names(res)))
res

产生的结果

> res
    level_number level1     level2 level3
 1:            1    air         NA     NA
 2:            1   land         NA     NA
 3:            1  water         NA     NA
 4:            2    air   airplane     NA
 5:            2    air    balloon     NA
 6:            2   land    bicycle     NA
 7:            2  water       boat     NA
 8:            2   land        car     NA
 9:            2    air helicopter     NA
10:            3    air   airplane Airbus
11:            3   land        car    BMW
12:            3   land        car   Ford

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