GeoJSON data

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 citiy or county level that are not included in this package, you may need to get the detailed map data from third-party source such as gadm.org. This document shows how to make your own GeoJSON file which can be used in e_map_register.

Packages

These are packages to help you building such maps

sp: spatial data management package.
raster: get spatial data from gadm.org.
geojsonio: convert spatial data into json format.
rmapshaper: simplify the spatial data.

library(echarts4r)
library(sp)
library(raster)
library(geojsonio)
#> Registered S3 method overwritten by 'geojsonsf':
#>   method        from   
#>   print.geojson geojson
#> 
#> Attaching package: 'geojsonio'
#> The following object is masked from 'package:base':
#> 
#>     pretty
library(rmapshaper)

Example

Get India map data from gadm website, this command need network available, it will download the rds data to the current directory.

india_sp <- raster::getData('GADM', country = 'INDIA', level = 2) 
#> Warning in raster::getData("GADM", country = "INDIA", level = 2): getData will be removed in a future version of raster
#> . Please use the geodata package instead
india_sp |> 
  head() |> 
  knitr::kable()

	GID_0	NAME_0	GID_1	NAME_1	NL_NAME_1	GID_2	NAME_2	VARNAME_2	NL_NAME_2	TYPE_2	ENGTYPE_2	CC_2	HASC_2
1	IND	India	IND.1_1	Andaman and Nicobar	NA	IND.1.1_1	Nicobar Islands	NA	NA	District	District	NA	IN.AN.NI
2	IND	India	IND.1_1	Andaman and Nicobar	NA	IND.1.2_1	North and Middle Andaman	NA	NA	District	District	NA	IN.AN.NM
3	IND	India	IND.1_1	Andaman and Nicobar	NA	IND.1.3_1	South Andaman	NA	NA	District	District	NA	IN.AN.SA
214	IND	India	IND.2_1	Andhra Pradesh	NA	IND.2.1_1	Anantapur	Anantpur, Ananthapur	NA	District	District	NA	IN.AD.AN
219	IND	India	IND.2_1	Andhra Pradesh	NA	IND.2.2_1	Chittoor	Chitoor\|Chittor	NA	District	District	NA	IN.AD.CH
220	IND	India	IND.2_1	Andhra Pradesh	NA	IND.2.3_1	East Godavari	NA	NA	District	District	NA	IN.AD.EG

Note that you can then combine maps with raster::union(map1, map2) or with the em_maps function from the echarts4r.maps package. Then convert the SpatialPolygonsDataFrame into GeoJSON with geojsonio: this will take a long time as the map is very detailed.

india_json <- geojsonio::geojson_list(india_sp)
print(object.size(india_json), units = "Mb")
#> 59.6 Mb

Therefore we can simplify the map to make it smaller.

india_small <- rmapshaper::ms_simplify(india_sp, keep = 0.05) 
india_json_small <- geojsonio::geojson_list(india_small)
print(object.size(india_json_small), units = "Mb") 
#> 6.8 Mb

The function raster::getData gives each polygon a NAME_* property (where * is the level specified) rather than just name. The tooltip will not display properly unless we use the nameMap to point to that property, by default echarts expects the name property.

Now we can use the GeoJSON with e_map_register.

# plot 
e_charts() |>
  e_map_register("India", india_json_small) |>
  e_map(map = "India", nameProperty = "NAME_2")

Pengfei Li

2024-02-16

Introduction

Packages

Example