Code
%>%
F1 group_by(date) %>%
summarise(Nobs = n()) %>%
print_table_conditional()
Data - INSEE
%>%
F1 group_by(date) %>%
summarise(Nobs = n()) %>%
print_table_conditional()
%>%
F1 left_join(variable, by = "Variable") %>%
group_by(variable, Variable) %>%
summarise(Nobs = n()) %>%
print_table_conditional()
variable | Variable | Nobs |
---|---|---|
PA_RDB | Pouvoir d’achat du RDB | 66 |
PA_RDB_ARB | Pouvoir d’achat du revenu arbitrable | 66 |
PA_RDB_ARB_UC | Pouvoir d’achat du revenu arbitrable par UC | 66 |
PA_RDB_UC | Pouvoir d’achat du RDB par UC | 66 |
ig_b("insee", "RPM2024", "F1", "fig3")
Rouge: 211, 104, 121 ->
Bleu: 69, 100, 156 ->
<- F1 %>%
plot_lineaire left_join(variable, by = "Variable") %>%
filter(variable %in% c("PA_RDB", "PA_RDB_UC")) %>%
ggplot(aes(x = date, y = value, color = Variable)) + geom_line(size = 1.5) +
theme_minimal() + xlab("") + ylab("") +
scale_x_date(breaks = seq(1960, 2100, 7) %>% paste0("-01-01") %>% as.Date(),
labels = date_format("%Y")) +
scale_y_continuous(breaks = seq(100, 1000, 100)) +
scale_color_manual(values = c("#45639c", "#d3687a")) +
theme(legend.title = element_blank(),
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.minor.y = element_blank(),
legend.position = "top")
plot_lineaire
<- plot_lineaire + scale_y_log10(breaks = seq(100, 1000, 100))
plot_log
plot_log
::ggarrange(plot_lineaire, plot_log, common.legend = T) ggpubr