How to generate a country map with specific regions filled in

Question

I'm trying to create a country map with specific regions filled in. I want to divide the country in 3 categories: extreme, high, too high. So in each category there will be a number of regions(DEPARTAMEN). Each category should have a specific color (black, red, orange). Let's say , for example, in extreme category there will be 8 regions(DEPARTAMEN) with the same color (black).

The first answer is exactly what I want, but I couldn't do the same because I can´t use the rworldmap package in this case: How to create a world map in R with specific countries filled in?. In the first answer they used rworldmap fuctions to join maps, and to fill regions by category.

This is how my data looks like (shp file):

Simple feature collection with 6 features and 4 fields
geometry type:  MULTIPOLYGON
dimension:      XY
bbox:           xmin: -79.45845 ymin: -17.28501 xmax: -70.80408 ymax: -2.986125
geographic CRS: WGS 84
  IDDPTO DEPARTAMEN     CAPITAL FUENTE                       geometry
1     01   AMAZONAS CHACHAPOYAS   INEI MULTIPOLYGON (((-77.81211 -...
2     02     ANCASH      HUARAZ   INEI MULTIPOLYGON (((-77.64692 -...
3     03   APURIMAC     ABANCAY   INEI MULTIPOLYGON (((-73.74632 -...
4     04   AREQUIPA    AREQUIPA   INEI MULTIPOLYGON (((-71.98109 -...
5     05   AYACUCHO    AYACUCHO   INEI MULTIPOLYGON (((-74.34843 -...
6     06  CAJAMARCA   CAJAMARCA   INEI MULTIPOLYGON (((-78.70034 -...

Is there a way to do the same as the answer chosen in this question (How to create a world map in R with specific countries filled in?) but without using rworldmap package? Also I'm using ggplot package to plot the map.

This is my desired output:

Answer 1

You could merge a dataframe (i.e. left_join()) with the categories you need into your sf object. As I do not have your shapefile, I get a similar one with the help of raster::getData().

I manually create a dataframe called "example_data" with, as per your request, Lima, Ancash, and Amazonas, with "extreme" values, and randomly assign "very high" or "high" to the rest of the departments.

library(tidyverse)
library(sf)
library(raster)

sf_peru <- raster::getData("GADM", country ="PE", level =1) %>% sf::st_as_sf()

example_data <- tibble(
  departamentos = sf_peru$NAME_1,
  risk = sample(x = c('very high', 'high'), 
                   size = length(sf_peru$NAME_1), 
                   replace = TRUE )) %>% 
  mutate(risk = if_else(departamentos %in% c("Lima", "Amazonas", "Ancash"), true = "extreme", false = risk))

sf_peru_joined <-  sf_peru %>% left_join(example_data, by = c("NAME_1" = "departamentos"))
custom_colour_scale <- c("extreme" = "red", "very high" = "orange", "high" = "yellow")

ggplot() + 
  geom_sf(data = sf_peru_joined,
          aes(fill = risk)) +
  scale_fill_manual(values = custom_colour_scale,
                    limits = c("extreme", "very high", "high"))