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# setup chunk NOT_CRAN <- identical(tolower(Sys.getenv("NOT_CRAN")),"true") knitr::opts_chunk$set(purl = NOT_CRAN) library(insee) embed_png <- function(path, dpi = NULL) { meta <- attr(png::readPNG(path, native = TRUE, info = TRUE), "info") if (!is.null(dpi)) meta$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(htmltools) library(prettydoc)
embed_png("pop.png")
# please download the Github version # devtools::install_github("hadrilec/insee") library(ggplot2) library(dplyr) library(magrittr) 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]))
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