knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) library(echarts4r) e_common( font_family = "Raleway" )
e_map_3d
family is similar to e_geo_3d
e_map
, or e_globe
.
choropleth <- data.frame( countries = c("France", "Brazil", "China", "Russia", "Canada", "India", "United States", "Argentina", "Australia"), values = round(runif(9, 10, 25)) ) choropleth |> e_charts(countries) |> e_map_3d(values, shading = "lambert") |> e_visual_map(values) # scale to values
buildings <- jsonlite::read_json("https://echarts.apache.org/examples/data-gl/asset/data/buildings.json") heights <- purrr::map(buildings$features, "properties") |> purrr::map("height") |> unlist() names <- purrr::map(buildings$features, "properties") |> purrr::map("name") |> unlist() data <- dplyr::tibble( name = names, value = round(runif(length(names), 0, 1), 6), height = heights / 10 ) data |> e_charts() |> e_map_register("buildings", buildings) |> e_map_3d_custom(name, value, height) |> e_visual_map( show = FALSE, min = 0.4, max = 1 )
The companion package echarts4r.maps comes with 215 maps.
You can install the package with:
install.packages("remotes") remotes::install_github('JohnCoene/echarts4r.maps')
View the full list of maps with echarts4r.maps::em_bank()
.
library(echarts4r.maps) USArrests$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
.
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