e_geo_3d family is similar to e_geo_3d
e_map, e_map_3d or e_globe.
Height Choropleth
choropleth <- data.frame(
countries = c("France", "Brazil", "China", "Russia", "Canada", "India", "United States",
"Argentina", "Australia"),
height = runif(9, 1, 5)
)
choropleth |>
dplyr::arrange(-height) |>
e_color_range(height, color) |>
e_charts(countries) |>
e_geo_3d(height, color)Lines
flights <- read.csv(
paste0("https://raw.githubusercontent.com/plotly/datasets/",
"master/2011_february_aa_flight_paths.csv")
)
flights |>
e_charts() |>
e_geo_3d() |>
e_lines_3d(
start_lon,
start_lat,
end_lon,
end_lat,
name = "flights",
coord_system = "geo3D",
lineStyle = list(normal = list(curveness = 0.3)),
effect = list(show = TRUE)
)Bars
url <- "https://echarts.apache.org/examples/data-gl/asset/data/population.json"
data <- jsonlite::fromJSON(url)
data <- as.data.frame(data)
names(data) <- c("lon", "lat", "value")
data |>
e_charts(lon) |>
e_geo_3d() |>
e_bar_3d(lat, value, coord_system = "geo3D") |>
e_visual_map()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_color_range(Murder, Color) |>
e_charts(state) |>
em_map("USA") |>
e_geo_3d(Murder, Color, type = "USA", regionHeight = 1) |>
e_visual_map(Murder)You can also use your own geoJSON with
e_map_register.