GeoJSON data

Pengfei Li, Patrick Rekieta

2026-05-12

Introduction

You will find 215 maps in the companion package echarts4r.maps. However, since you may need different kinds of maps i.e.: at the city or county level that are not included in this package, you may need to get detailed map data from a third-party source such as gadm.org. This document shows how to make your own GeoJSON data which can be used in e_map_register.

GeoJSON structure

A GeoJSON object used with e_map_register is a list with a type of "FeatureCollection" and a features array. Each feature needs a properties list with at least a name field (used by echarts for tooltips and matching data) and a geometry defining the shape.

Below we build a small example with three rectangular regions entirely in R — no external data or downloads required.

library(echarts4r)

my_geojson <- list(
  type = "FeatureCollection",
  features = list(
    list(
      type = "Feature",
      properties = list(name = "Region A"),
      geometry = list(
        type = "Polygon",
        coordinates = list(list(
          c(0, 0), c(2, 0), c(2, 2), c(0, 2), c(0, 0)
        ))
      )
    ),
    list(
      type = "Feature",
      properties = list(name = "Region B"),
      geometry = list(
        type = "Polygon",
        coordinates = list(list(
          c(2, 0), c(4, 0), c(4, 2), c(2, 2), c(2, 0)
        ))
      )
    ),
    list(
      type = "Feature",
      properties = list(name = "Region C"),
      geometry = list(
        type = "Polygon",
        coordinates = list(list(
          c(0, 2), c(4, 2), c(4, 4), c(0, 4), c(0, 2)
        ))
      )
    )
  )
)

Registering and plotting the map

Once you have a GeoJSON list, pass it to e_map_register and then use e_map to plot data on it. The name column in your data must match the name property in the GeoJSON features.

data <- data.frame(
  name = c("Region A", "Region B", "Region C"),
  value = c(10, 25, 40)
)

data |>
  e_charts(name) |>
  e_map_register("my_map", my_geojson) |>
  e_map(value, map = "my_map") |>
  e_visual_map(value) |>
  e_tooltip()

Using the nameProperty option

By default, echarts expects each GeoJSON feature to have a name property. If your GeoJSON uses a different property name (e.g., NAME_2 from sources like gadm.org), you can use the nameProperty argument to tell echarts which property to use.

gadm_style_geojson <- list(
  type = "FeatureCollection",
  features = list(
    list(
      type = "Feature",
      properties = list(NAME_2 = "District X", GID_2 = "IND.1.1_1"),
      geometry = list(
        type = "Polygon",
        coordinates = list(list(
          c(0, 0), c(3, 0), c(3, 3), c(0, 3), c(0, 0)
        ))
      )
    ),
    list(
      type = "Feature",
      properties = list(NAME_2 = "District Y", GID_2 = "IND.1.2_1"),
      geometry = list(
        type = "Polygon",
        coordinates = list(list(
          c(3, 0), c(6, 0), c(6, 3), c(3, 3), c(3, 0)
        ))
      )
    )
  )
)

data2 <- data.frame(
  name = c("District X", "District Y"),
  value = c(100, 200)
)

data2 |>
  e_charts(name) |>
  e_map_register("gadm_map", gadm_style_geojson) |>
  e_map(value, map = "gadm_map", nameProperty = "NAME_2") |>
  e_visual_map(value) |>
  e_tooltip()

Working with real spatial data

For real-world maps, the typical workflow is:

1. Obtain spatial data — from packages like geodata, rnaturalearth, or download shapefiles from gadm.org.
2. Convert to GeoJSON — use geojsonio::geojson_list() or sf::st_read() combined with jsonlite::fromJSON().
3. Simplify — detailed maps can be very large. Use rmapshaper::ms_simplify() to reduce file size before converting to GeoJSON.
4. Register and plot — pass the GeoJSON list to e_map_register and plot with e_map.

# Example workflow (not run — requires geodata and geojsonio packages)
india_sp <- geodata::gadm(country = "INDIA", path = tempdir(), level = 2)
india_sp <- methods::as(india_sp, "Spatial")

# Simplify to reduce size
india_small <- rmapshaper::ms_simplify(india_sp, keep = 0.05)

# Convert to GeoJSON list
india_json <- geojsonio::geojson_list(india_small)

# Plot
e_charts() |>
  e_map_register("India", india_json) |>
  e_map(map = "India", nameProperty = "NAME_2")