R Notebook

library(raster) CMR1 <- getData(‘GADM’, country=‘CMR’, level=1) CMR2 <- getData(‘GADM’, country=‘CMR’, level=2) CMR3 <- getData(‘GADM’, country=‘CMR’, level=3) plot(CMR1) plot(CMR2) plot(CMR3)

library(rgeos) # il a fallu instalqler rgeos library(sf) # il faut attacher le packages “sf” pour utiliser la fonction “st_as_sf”

is(CMR1) is(CMR2) is(CMR3) CMR1sf = st_as_sf(CMR1) CMR2sf = st_as_sf(CMR2) CMR3sf = st_as_sf(CMR3)

sf_cent <- as.data.frame(st_centroid(CMR1sf\(geometry)) library(stringr) long <- as.numeric(substr(sf_cent\)geometry, 3, 17)) lat <- as.numeric(substr(sf_cent$geometry, 21, 35)) NAME_1 <- c(“Adamaoua”, “Centre”, “Est”, “Extrême-Nord”, “Littoral”, “Nord”, “Nord-Ouest”,
“Ouest”, “Sud”, “Sud-Ouest”) Label <- c(“AD”, “CE”, “ET”, “EN”, “LT”, “NO”, “NW”, “OU”, “SU”, “SW”) NB_Communes <- c(19, 70, 33, 46, 35, 22, 34, 41, 29, 31) Center <- data.frame(NAME_1, long, lat, Label, NB_Communes) library(dplyr) CMR1sf_Bon <- left_join(CMR1sf, Center, by=c(“NAME_1”)) # J’ai déjà mes données au format sf maintenant je veux ajouter les noms de régions library(ggplot2) ggplot() + geom_sf(data = CMR1sf_Bon, fill = NA, color =NA, lwd = 1) + geom_sf_text(data = CMR1sf_Bon, aes(label = Label), nudge_x = 0.05, nudge_y = -0.16, fun.geometry = sf::st_centroid) + geom_sf(data = CMR1sf_Bon, color = “black”, fill = NA, lwd = 1) + geom_sf(data = CMR1sf_Bon, fill=NA, color =NA) + geom_sf_text(data = CMR1sf_Bon, aes(label = NB_Communes),inherit.aes = FALSE,nudge_x = 0.05, nudge_y = 0.05)+ theme_void() # Dessinons une region spécifique

ggplot() + geom_sf(data = CMR1sf_Bon[CMR1sf_Bon\(NAME_1=="Ouest",], fill = NA, color =NA, lwd = 1) + geom_sf_text(data = CMR1sf_Bon[CMR1sf_Bon\)NAME_1==“Ouest”,], aes(label = Label), nudge_x = 0.05, nudge_y = -0.16, fun.geometry = sf::st_centroid) + geom_sf(data = CMR1sf_Bon[CMR1sf_Bon\(NAME_1=="Ouest",], color = "black", fill = NA, lwd = 1) + geom_sf(data = CMR1sf_Bon[CMR1sf_Bon\)NAME_1==“Ouest”,], fill=NA, color =NA) + geom_sf_text(data = CMR1sf_Bon[CMR1sf_Bon$NAME_1==“Ouest”,], aes(label = NB_Communes),inherit.aes = FALSE,nudge_x = 0.05, nudge_y = 0.05)+ theme_void()

names(CMR1sf_Bon)<-c(“GID_0”, “NAME_0”, “GID_1”, “Régions”, “VARNAME_1”,
“NL_NAME_1”, “TYPE_1”, “ENGTYPE_1”, “CC_1”, “HASC_1”,
“long”, “lat”, “Label”, “NB_Communes”, “geometry”)

CMR1sf_Bon %>% ggplot() + aes(fill = Régions) + geom_sf(color = “black”, size = 0.1) + geom_sf_text(aes(label = NB_Communes), inherit.aes = FALSE,nudge_x = 0.02, nudge_y = 0.02) + ggtitle(“Nombre de communes par région au Cameroun”, subtitle = “Source: Auteurs, Données FEICOM 2022”) + theme_void()+ theme(plot.background = element_rect(color = “black”, size = 0.1))