问题
I would like to visualize some deeply nested data using networkD3. I can't figure out how to get the data into the right format before sending to radialNetwork.
Here is some sample data:
level <- c(1, 2, 3, 4, 4, 3, 4, 4, 1, 2, 3)
value <- letters[1:11]
where level indicates the level of the nest, and value is the name of the node. By using these two vectors, I need to get the data into the following format:
my_list <- list(
name = "root",
children = list(
list(
name = value[1], ## a
children = list(list(
name = value[2], ## b
children = list(list(
name = value[3], ## c
children = list(
list(name = value[4]), ## d
list(name = value[5]) ## e
)
),
list(
name = value[6], ## f
children = list(
list(name = value[7]), ## g
list(name = value[8]) ## h
)
))
))
),
list(
name = value[9], ## i
children = list(list(
name = value[10], ## j
children = list(list(
name = value[11] ## k
))
))
)
)
)
Here is the deparsed object:
> dput(my_list)
# structure(list(name = "root",
# children = list(
# structure(list(
# name = "a",
# children = list(structure(
# list(name = "b",
# children = list(
# structure(list(
# name = "c", children = list(
# structure(list(name = "d"), .Names = "name"),
# structure(list(name = "e"), .Names = "name")
# )
# ), .Names = c("name",
# "children")), structure(list(
# name = "f", children = list(
# structure(list(name = "g"), .Names = "name"),
# structure(list(name = "h"), .Names = "name")
# )
# ), .Names = c("name",
# "children"))
# )), .Names = c("name", "children")
# ))
# ), .Names = c("name",
# "children")), structure(list(
# name = "i", children = list(structure(
# list(name = "j", children = list(structure(
# list(name = "k"), .Names = "name"
# ))), .Names = c("name",
# "children")
# ))
# ), .Names = c("name", "children"))
# )),
# .Names = c("name",
# "children"))
Then I can pass it to the final plotting function:
library(networkD3)
radialNetwork(List = my_list)
The output will look similar to this:
Question: How can I create the nested list?
Note: As pointed out by @zx8754, there is already a solution in this SO post, but that requires data.frame as input. Due to the inconsistency in my level, I don't see a simple way to transform it into a data.frame.
回答1:
Using a data.table-style merge:
library(data.table)
dt = data.table(idx=1:length(value), level, parent=value)
dt = dt[dt[, .(i=idx, level=level-1, child=parent)], on=.(level, idx < i), mult='last']
dt[is.na(parent), parent:= 'root'][, c('idx','level'):= NULL]
> dt
# parent child
# 1: root a
# 2: a b
# 3: b c
# 4: c d
# 5: c e
# 6: b f
# 7: f g
# 8: f h
# 9: root i
# 10: i j
# 11: j k
Now we can use the solution from the other post:
x = maketreelist(as.data.frame(dt))
> identical(x, my_list)
# [1] TRUE
回答2:
As a preface, your data is difficult to work with because critical information is encoded in the order of the values in level. I don't know how you get those values in that order, but consider that there may be a better way to structure that information in the first place, which would make the next task easier.
Here's a base-y way of converting your data into a data frame with 2 columns, parent and child, then passing that into data.tree functions that can easily convert to the JSON format you need... and then pass it on to radialNetwork...
level <- c(1, 2, 3, 4, 4, 3, 4, 4, 1, 2, 3)
value <- letters[1:11]
library(data.tree)
library(networkD3)
parent_idx <- sapply(1:length(level), function(n) rev(which(level[1:n] < level[n]))[1])
df <- data.frame(parent = value[parent_idx], child = value, stringsAsFactors = F)
df$parent[is.na(df$parent)] <- ""
list <- ToListExplicit(FromDataFrameNetwork(df), unname = T)
radialNetwork(list)
Here's a tidyverse way of achieving the same...
level <- c(1, 2, 3, 4, 4, 3, 4, 4, 1, 2, 3)
value <- letters[1:11]
library(tidyverse)
library(data.tree)
library(networkD3)
data.frame(level, value, stringsAsFactors = F) %>%
mutate(row = row_number()) %>%
mutate(level2 = level, value2 = value) %>%
spread(level2, value2) %>%
mutate(`0` = "") %>%
arrange(row) %>%
fill(-level, -value, -row) %>%
gather(parent_level, parent, -level, -value, -row) %>%
filter(parent_level == level - 1) %>%
arrange(row) %>%
select(parent, child = value) %>%
data.tree::FromDataFrameNetwork() %>%
data.tree::ToListExplicit(unname = TRUE) %>%
radialNetwork()
and for a bonus, the current dev version of networkD3 (v0.4.9000) has a new treeNetwork function that takes a data frame with nodeId and parentId columns/variables, which eliminates the need for the data.tree fucntions to convert to JSON, so something like this works...
level <- c(1, 2, 3, 4, 4, 3, 4, 4, 1, 2, 3)
value <- letters[1:11]
library(tidyverse)
library(networkD3)
data.frame(level, value, stringsAsFactors = F) %>%
mutate(row = row_number()) %>%
mutate(level2 = level, value2 = value) %>%
spread(level2, value2) %>%
mutate(`0` = "root") %>%
arrange(row) %>%
fill(-level, -value, -row) %>%
gather(parent_level, parent, -level, -value, -row) %>%
filter(parent_level == level - 1) %>%
arrange(row) %>%
select(nodeId = value, parentId = parent) %>%
rbind(data.frame(nodeId = "root", parentId = NA)) %>%
mutate(name = nodeId) %>%
treeNetwork(direction = "radial")
来源：https://stackoverflow.com/questions/41157332/return-nested-list-with-nested-level-and-value