christophsax · November 28, 2021 10:21
diff --git a/data.csv b/data.csv
diff --git a/data.tree.R b/data.tree.R
 library(tidyverse)
 library(data.tree)
 library(echarts4r)

 #' Example data from EFV
 raw <-
  read_csv("https://gist.githubusercontent.com/christophsax/8ee2edb7236f5baa16552986084261fa/raw/60d317a604f8a815218d81e2cfe45018e49735a7/data.csv", col_types = cols()) |>
  pivot_longer(-id, "year") |>
  mutate(value = coalesce(value, 0))

 #' I love how easy it is to detect the hierarchy:
 data17 <-
  raw |>
  filter(year == 2017) |>
  select(-year) |>
  mutate(id = gsub("/", "-", id)) |>
  mutate(pathString = gsub(" > ", "/", id)) |>
  select(-id) |>
  as.Node()

 #' This view is nice:
 data17

 #' You can do various cool stuff:
 data17 |> 
  ToDataFrameTypeCol("value") |> 
  as_tibble()

 #' But the greatest thing is how easy it is to use it in echarts sunburst or treemaps:

 # data17$Ertrag |>
 #   e_charts() |>
 #   e_sunburst()

 # data17$Ertrag |>
 #   e_charts() |>
 #  e_treemap()
	library(tidyverse)
	library(data.tree)
	library(echarts4r)

	#' Example data from EFV
	raw <-
	read_csv("https://gist.githubusercontent.com/christophsax/8ee2edb7236f5baa16552986084261fa/raw/60d317a604f8a815218d81e2cfe45018e49735a7/data.csv", col_types = cols()) \|>
	pivot_longer(-id, "year") \|>
	mutate(value = coalesce(value, 0))

	#' I love how easy it is to detect the hierarchy:
	data17 <-
	raw \|>
	filter(year == 2017) \|>
	select(-year) \|>
	mutate(id = gsub("/", "-", id)) \|>
	mutate(pathString = gsub(" > ", "/", id)) \|>
	select(-id) \|>
	as.Node()

	#' This view is nice:
	data17

	#' You can do various cool stuff:
	data17 \|>
	ToDataFrameTypeCol("value") \|>
	as_tibble()

	#' But the greatest thing is how easy it is to use it in echarts sunburst or treemaps:

	# data17$Ertrag \|>
	# e_charts() \|>
	# e_sunburst()

	# data17$Ertrag \|>
	# e_charts() \|>
	# e_treemap()