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)
#> Warning: package 'sp' was built under R version 4.5.2
library(raster)
#> Warning: package 'raster' was built under R version 4.5.2
library(geojsonio)
#> Warning: package 'geojsonio' was built under R version 4.5.2
#> 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)
#> Warning: package 'rmapshaper' was built under R version 4.5.2Example
Get India map data from gadm website, this command need network available, it will download the rds data to the current directory.
india_sp <- geodata::gadm(country = "INDIA", level = 2)
india_sp <- methods::as(india_sp, "Spatial")
india_sp |>
head() |>
knitr::kable()| GID_2 | GID_0 | COUNTRY | GID_1 | NAME_1 | NL_NAME_1 | NAME_2 | VARNAME_2 | NL_NAME_2 | TYPE_2 | ENGTYPE_2 | CC_2 | HASC_2 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| IND.1.1_1 | IND | India | IND.1_1 | Andaman and Nicobar | NA | Nicobar Islands | NA | NA | District | District | NA | IN.AN.NI |
| IND.1.2_1 | IND | India | IND.1_1 | Andaman and Nicobar | NA | North and Middle Andaman | NA | NA | District | District | NA | IN.AN.NM |
| IND.1.3_1 | IND | India | IND.1_1 | Andaman and Nicobar | NA | South Andaman | NA | NA | District | District | NA | IN.AN.SA |
| IND.2.1_1 | IND | India | IND.2_1 | Andhra Pradesh | NA | Anantapur | Anantpur, Ananthapur | NA | District | District | NA | IN.AD.AN |
| IND.2.2_1 | IND | India | IND.2_1 | Andhra Pradesh | NA | Chittoor | Chitoor|Chittor | NA | District | District | NA | IN.AD.CH |
| IND.2.3_1 | IND | India | IND.2_1 | Andhra Pradesh | NA | 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")
#> 61.2 MbTherefore 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")
#> 7.1 MbThe function geodata::gadm 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")