Return nested list with nested level and value

Question

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 rad

Answer 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

Answer 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")