DOWNLOAD_TIME |
---|
2022-03-11 |
Pyramide des âges - Données annuelles 2022 - demo-pop-pyram
Data - INSEE
Info
DOWNLOAD_TIME
Sources
variable
Code
`demo-pop-pyram` %>%
print_table_conditional()
Pyramide des âges
Tous
Code
`demo-pop-pyram` %>%
select(age = `Âge révolu`, `Femmes` = `Nombre\nde femmes`, `Hommes` = `Nombre\nd'hommes`) %>%
mutate(age = as.numeric(age)) %>%
gather(variable, value, -age) %>%
+ geom_line(aes(x = age, y = value, color = variable)) +
ggplot theme_minimal() + xlab("Âge") + ylab("") +
scale_y_continuous(breaks = seq(0, 1000000, 50000),
labels = dollar_format(pre = "", su = "")) +
scale_x_continuous(breaks = seq(0, 100, 10)) +
scale_color_manual(values = viridis(3)[1:2]) +
theme(legend.position = c(0.9, 0.9),
legend.title = element_blank())
70-
Code
names(`demo-pop-pyram`)
# [1] "Année de \nnaissance" "Âge révolu" "Nombre\nde femmes"
# [4] "Nombre\nd'hommes" "Ensemble"
Code
`demo-pop-pyram` %>%
select(age = `Âge révolu`, `Femmes` = `Nombre\nde femmes`, `Hommes` = `Nombre\nd'hommes`) %>%
mutate(age = as.numeric(age)) %>%
filter(age >= 65) %>%
gather(variable, value, -age) %>%
+ geom_line(aes(x = age, y = value, color = variable)) +
ggplot theme_minimal() + xlab("Âge") + ylab("") +
scale_y_continuous(breaks = seq(0, 1000000, 50000),
labels = dollar_format(pre = "", su = "")) +
scale_x_continuous(breaks = seq(0, 100, 5)) +
scale_color_manual(values = viridis(3)[1:2]) +
theme(legend.position = c(0.9, 0.9),
legend.title = element_blank())