问题
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?
Source:
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
Destination:
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
回答1:
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)]
By not current_lvl looks as follows (keyed by level1)
level1 level_number
1: air 1
2: land 1
3: water 1
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
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
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))
}
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
what results in
> 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
回答2:
Using the data.tree package, you could do the following:
library(data.tree)
df <- data.frame(name = c("land", "water", "air", "car", "bicycle", "boat", "balloon", "airplane", "helicopter", "Ford", "BMW", "Airbus"),
parent = c("root", "root", "root", "land", "land", "water", "air", "air", "air", "car", "car", "airplane"))
Note that I replaced the NAs with "root", which makes the conversion to a data.tree much easier. Namely:
tree <- FromDataFrameNetwork(df)
Getting the required format then becomes trivial as we can use the hierarchy infrastructure from data.tree:
ToDataFrameTree(tree,
level1 = function(x) x$path[2],
level2 = function(x) x$path[3],
level3 = function(x) x$path[4],
level_number = function(x) x$level - 1)[-1,-1]
回答3:
Do not use "root"
as parent-value for toplevel-records. The solution using the data.tree-package is great, however, in newer versions "root"
is a reserved name for nodes. Altough it is automatically replaced with "root2", the call to FromDataFrameNetwork(df)
does not return a tree as wanted.
来源:https://stackoverflow.com/questions/33069353/r-hierarchical-data-frame-from-child-parent-relations