Population by age"
In insee: Tools to Easily Download Data from INSEE BDM Database

# setup chunk
NOT_CRAN <- identical(tolower(Sys.getenv("NOT_CRAN")),"true")
knitr::opts_chunk$set(purl = NOT_CRAN)
library(insee)
library(tidyverse)

embed_png <- function(path, dpi = NULL) {
  meta <- attr(png::readPNG(path, native = TRUE, info = TRUE), "info")
  if (!is.null(dpi)) meta$dpi <- rep(dpi, 2)
  knitr::asis_output(paste0(
    "<img src='", path, "'",
    " width=", round(meta$dim[1] / (meta$dpi[1] / 96)),
    " height=", round(meta$dim[2] / (meta$dpi[2] / 96)),
    " />"
  ))}

library(kableExtra)
library(magrittr)
library(htmltools)
library(prettydoc)

embed_png("pop.png")

# please download the Github version
# devtools::install_github("hadrilec/insee")
library(tidyverse)
library(insee)

dataset_list = get_dataset_list()

df_idbank_list_selected =
  get_idbank_list("POPULATION-STRUCTURE") %>% #population dataset
  add_insee_title() %>% 
  filter(INDICATEUR == "POPULATION_1ER_JANVIER") %>% #population at the beginning of the year
  filter(REF_AREA == "FE") %>%  # all France including overseas departements
  filter(SEXE == 0) %>%  # men and women
  filter(AGE %in% c("00-19", "20-59", "60-")) #age ranges

list_idbank = df_idbank_list_selected %>% pull(idbank)

data = get_insee_idbank(list_idbank)

data_plot = 
  data %>%
  split_title() %>% 
  add_insee_metadata() %>% 
  mutate(OBS_VALUE = OBS_VALUE / 10^6)

ggplot(data_plot, aes(x = DATE, y = OBS_VALUE, fill = TITLE_EN3)) +
  geom_area() +
  ggtitle("French population in millions, by age") +
  labs(subtitle = sprintf("Last updated : %s", data_plot$TIME_PERIOD[1]))