r - 如何在给定 R 中的父子关系的情况下展平分层数据结构

Question

我有描述亲子关系的数据:

df <- tibble::tribble(
       ~Child,     ~Parent,
      "Fruit",      "Food",
  "Vegetable",      "Food",
      "Apple",     "Fruit",
     "Banana",     "Fruit",
       "Pear",     "Fruit",
     "Carrot", "Vegetable",
     "Celery", "Vegetable",
       "Bike",  "Not Food",
        "Car",  "Not Food"
  )
df
#> # A tibble: 9 x 2
#>   Child     Parent   
#>   <chr>     <chr>    
#> 1 Fruit     Food     
#> 2 Vegetable Food     
#> 3 Apple     Fruit    
#> 4 Banana    Fruit    
#> 5 Pear      Fruit    
#> 6 Carrot    Vegetable
#> 7 Celery    Vegetable
#> 8 Bike      Not Food 
#> 9 Car       Not Food

在视觉上，这看起来像:

最终，我想要的结果是将其“扁平化”为看起来更像这样的结构:

results <- tibble::tribble(
             ~Level.03, ~Level.02,  ~Level.01,
               "Apple",   "Fruit",     "Food",
              "Banana",   "Fruit",     "Food",
                "Pear",   "Fruit",     "Food",
                    NA,    "Bike", "Not Food",
                    NA,     "Car", "Not Food"
             )
results
#> # A tibble: 5 x 3
#>   Level.03 Level.02 Level.01
#>   <chr>    <chr>    <chr>   
#> 1 Apple    Fruit    Food    
#> 2 Banana   Fruit    Food    
#> 3 Pear     Fruit    Food    
#> 4 <NA>     Bike     Not Food
#> 5 <NA>     Car      Not Food

注意:并非所有元素都具有所有级别。例如，bike 和 car 没有 Level.03 元素。

我觉得有一种方法可以使用 tidyr 或来自 jsonlite 的某种类型的 next/unnest 函数优雅地完成此操作？我从递归连接开始，但我觉得我正在重新发明轮子，而且可能有一种直接的方法。

Answer 1

这是一个带有 while 循环的函数:

fun <- function(s){
  i <- 1
  while(i<=length(s)){
    if(any(s[[i]] %in% names(s)))
    {
      nms <- s[[i]]
      s[[i]] <- stack(s[nms])
      s[nms] <- NULL
    }
    else
      s[[i]] <- data.frame(values = NA, ind = s[[i]])
    i <- i+1
  }
  s
}

dplyr::bind_rows(fun(unstack(df)), .id = 'Level.01')[c(2:3,1)]
 values       ind Level.01
1  Apple     Fruit     Food
2 Banana     Fruit     Food
3   Pear     Fruit     Food
4 Carrot Vegetable     Food
5 Celery Vegetable     Food
6   <NA>      Bike Not Food
7   <NA>       Car Not Food

如果你有更多的层次，你可以概括这一点