Map 3D

e_map_3d family is similar to e_geo_3d e_map, or e_globe.

Choropleth

choropleth <- data.frame(
  countries = c("France", "Brazil", "China", "Russia", "Canada", "India", "United States",
                "Argentina", "Australia"),
  values = round(runif(9, 10, 25))
)

choropleth |> 
  e_charts(countries) |> 
  e_map_3d(values, shading = "lambert") |> 
  e_visual_map(values) # scale to values

Buildings

buildings <- jsonlite::read_json("https://echarts.apache.org/examples/data-gl/asset/data/buildings.json")

heights <- purrr::map(buildings$features, "properties") |> 
  purrr::map("height") |> 
  unlist()
  
names <- purrr::map(buildings$features, "properties") |> 
  purrr::map("name") |> 
  unlist()
  
data <- dplyr::tibble(
  name = names,
  value = round(runif(length(names), 0, 1), 6),
  height = heights / 10
)

data |> 
  e_charts() |> 
  e_map_register("buildings", buildings) |>
  e_map_3d_custom(name, value, height) |> 
  e_visual_map(
    show = FALSE,
    min = 0.4,
    max = 1
  )

GeoJSON

The companion package echarts4r.maps comes with 215 maps.

You can install the package with:

install.packages("remotes")
remotes::install_github('JohnCoene/echarts4r.maps')

View the full list of maps with echarts4r.maps::em_bank().

library(echarts4r.maps)

USArrests$state <- row.names(USArrests) # add states as column

USArrests |> 
  e_charts(state) |>
  em_map("USA") |> 
  e_map_3d(Murder, map = "USA") |> 
  e_visual_map(Murder)

You can also use your own geoJSON with e_map_register.

John Coene

2024-02-16

Choropleth

Buildings

GeoJSON