donnees_parc_automobile_des_menages_en_2023 %>%
filter(decile != "Total", decile != "NC",
`Classe Crit'air` != "Total",
`Classe Crit'air` != "Indéterminé",
`Classe Crit'air` != "Non-classé") %>%
mutate(decile = factor(decile, levels = paste0("D", 1:10), labels = c("D1\n10% les - riches", paste0("D", 2:9), "D10\n10% les + riches"))) %>%
mutate(`Classe Crit'air` = factor(`Classe Crit'air`, levels = c("Crit'Air E", paste("Crit'Air", 1:5)), labels = c("Crit'Air E", paste("Crit'Air", 1:5)))) %>%
ggplot + geom_col(aes(x = decile, y = value, fill = `Classe Crit'air`)) +
theme_minimal() + xlab("Dixième de Revenu") + ylab("Nombre de véhicules") +
theme(legend.title = element_blank(),
axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) +
scale_y_continuous(breaks = seq(0, 4000000, 500000),
labels = scales::dollar_format(pre = "")) +
scale_fill_manual(values = palette_critair)