Last data update: 19 sept. 2026, 11:59
Last compile: 19 sept. 2026, 11:59
Figure 1 : structure de consommation selon le niveau de vie, 2017
Code
fig1 |>
select(poste, quintile_1, quintile_5) |>
pivot_longer(-poste, names_to = "groupe", values_to = "part") |>
mutate(groupe = recode(groupe, quintile_1 = "1er quintile (ménages modestes)",
quintile_5 = "5e quintile (ménages aisés)"),
poste = fct_reorder(poste, part, .fun = max)) |>
ggplot(aes(x = poste, y = part, fill = groupe)) +
geom_col(position = "dodge") +
coord_flip() +
scale_fill_manual(values = c("1er quintile (ménages modestes)" = "#E8737A",
"5e quintile (ménages aisés)" = "#1B3F8B"), name = NULL) +
theme_minimal(base_size = 10) +
labs(x = NULL, y = "%",
title = "Structure de consommation selon le niveau de vie",
subtitle = "2017") +
theme(legend.position = "bottom", panel.grid.minor = element_blank())
Figure 2 : structure de consommation des propriétaires et locataires
Code
fig2 |>
filter(groupe %in% c("quintile_1", "quintile_5")) |>
mutate(groupe = recode(groupe, quintile_1 = "1er quintile (modestes)", quintile_5 = "5e quintile (aisés)"),
poste = fct_reorder(poste, part, .fun = max)) |>
ggplot(aes(x = poste, y = part, fill = groupe)) +
geom_col(position = "dodge") +
facet_wrap(~ statut_occupation) +
coord_flip() +
scale_fill_manual(values = c("1er quintile (modestes)" = "#E8737A",
"5e quintile (aisés)" = "#1B3F8B"), name = NULL) +
theme_minimal(base_size = 9) +
labs(x = NULL, y = "%",
title = "Structure de consommation des propriétaires et des locataires",
subtitle = "selon le niveau de vie, 2017") +
theme(legend.position = "bottom", panel.grid.minor = element_blank())
Figure 3 : quatre principaux postes selon le type de ménage, 2017
Code
fig3 |>
mutate(type_menage = fct_relevel(type_menage, "Personnes seules", "Familles monoparentales",
"Couples sans enfant", "Couples avec enfants")) |>
ggplot(aes(x = type_menage, y = part, fill = poste)) +
geom_col(position = "dodge") +
scale_fill_brewer(palette = "Set2", name = NULL) +
theme_minimal(base_size = 11) +
labs(x = NULL, y = "%",
title = "Part des quatre principaux postes dans la consommation",
subtitle = "selon le type de ménage, 2017") +
theme(legend.position = "bottom", axis.text.x = element_text(angle = 20, hjust = 1),
panel.grid.minor = element_blank()) +
guides(fill = guide_legend(ncol = 2))
Figure 4a : écarts aisés/modestes, 1979 et 2017
Code
fig4a |>
mutate(poste = fct_reorder(poste, ecart, .fun = function(x) x[2])) |>
ggplot(aes(x = poste, y = ecart, fill = factor(annee))) +
geom_col(position = "dodge") +
geom_hline(yintercept = 0, color = "grey40") +
coord_flip() +
scale_fill_manual(values = c("1979" = "#8FA8D8", "2017" = "#1B3F8B"), name = NULL) +
theme_minimal(base_size = 10) +
labs(x = NULL, y = "Points",
title = "Écarts de structure de consommation entre ménages aisés et modestes",
subtitle = "20 % les plus aisés moins 20 % les plus modestes, 1979 et 2017") +
theme(legend.position = "bottom", panel.grid.minor = element_blank())
Figure 4b : écarts cadres/ouvriers, 1979 et 2017
Code
fig4b |>
mutate(poste = fct_reorder(poste, ecart, .fun = function(x) x[2])) |>
ggplot(aes(x = poste, y = ecart, fill = factor(annee))) +
geom_col(position = "dodge") +
geom_hline(yintercept = 0, color = "grey40") +
coord_flip() +
scale_fill_manual(values = c("1979" = "#8FA8D8", "2017" = "#1B3F8B"), name = NULL) +
theme_minimal(base_size = 10) +
labs(x = NULL, y = "Points",
title = "Écarts de structure de consommation entre cadres et ouvriers",
subtitle = "1979 et 2017") +
theme(legend.position = "bottom", panel.grid.minor = element_blank())