Code
%>%
VE2 group_by(centile) %>%
summarise(Nobs = n()) %>%
print_table_conditional()
Data - INSEE
%>%
VE2 group_by(centile) %>%
summarise(Nobs = n()) %>%
print_table_conditional()
%>%
VE2 group_by(variable) %>%
summarise(Nobs = n()) %>%
print_table_conditional()
variable | Nobs |
---|---|
Patrimoine brut hors reste | 101 |
Patrimoine financier | 101 |
Patrimoine immobilier | 101 |
Patrimoine professionnel | 101 |
%>%
VE2 + geom_line(aes(x = centile, y = value, color = variable)) +
ggplot theme_minimal()
%>%
VE2 filter(!grepl("brut", variable)) %>%
mutate(variable = factor(variable, levels = c("Patrimoine immobilier", "Patrimoine financier", "Patrimoine professionnel"))) %>%
+ geom_line(aes(x = centile/100, y = value/100, color = variable)) +
ggplot theme_minimal() +
xlab("Part cumulée de la population (%)") + ylab("Part cumulée du patrimoine (%)") +
scale_x_continuous(breaks = 0.01*seq(0, 100, 20),
labels = percent_format(a = 1)) +
scale_y_continuous(breaks = 0.01*seq(0, 100, 20),
labels = percent_format(a = 1)) +
geom_segment(aes(x = 0, y = 0, xend = 1, yend = 1), linetype = "dashed") +
theme(legend.title = element_blank()) +
geom_text(aes(x = 0.5, y = 0.55, label = "égalité parfaite"), angle = 45)+ coord_equal(ratio = 1)
%>%
VE2 mutate(centile = 1-centile/100,
value = 1-value/100) %>%
+ geom_line(aes(x = centile, y = value, color = variable)) +
ggplot theme_minimal()
%>%
VE2 mutate(centile = 1-centile/100,
value = 1-value/100) %>%
arrange(centile) %>%
filter(centile != 0) %>%
+ geom_line(aes(x = value, y = centile, color = variable)) +
ggplot theme_minimal() +
scale_x_log10() + scale_y_log10()