Skip to content
Snippets Groups Projects

Resolve "integrer les données INSEE du statut d'occupation par nombre de pièces des résidences principales"

3 files
+ 183
0
Compare changes
  • Side-by-side
  • Inline
Files
3
+ 115
0
# chargement_lgt_rp_insee
# 2020 --> https://www.insee.fr/fr/statistiques/7631446?sommaire=7631713
# https://www.insee.fr/fr/statistiques/fichier/7631446/TD_PRINC2_2020_csv.zip
# paru le 27/06/2023
# librairies ----------
library(tidyverse)
library(lubridate)
library(datalibaba)
library(dplyr)
# library(googlesheets4)
rm(list = ls())
# chargement data -------
download.file(url = "https://www.insee.fr/fr/statistiques/fichier/7631446/TD_PRINC2_2020_csv.zip",
destfile = "extdata/TD_PRINC2_2020_csv.zip")
unzip("extdata/TD_PRINC2_2020_csv.zip", overwrite = TRUE, exdir = "extdata")
# chargement data annees precedentes -------
load("extdata/statut_occupation_des_rp.RData")
# statut_occupation_des_rp <- importer_data(db = "datamart",
# schema = "portrait_territoires",
# table = "source_statut_occupation_des_rp")
statut_occupation_des_rp_old <- statut_occupation_des_rp
rm(statut_occupation_des_rp)
# chargement du nouveau millésime
millesime = 2020
# path <- paste0("extdata/BTT_TD_PRINC2_",millesime,".txt") #pour les années jusque 2016
# path <- paste0("extdata/BTT_TD_PRINC2_",millesime,".csv") #pour les années 2017 à 2019
path <- paste0("extdata/TD_PRINC2_",millesime,".csv") # à partir de 2020
statut_occupation_des_rp0 <- read.csv2(path,
dec='.',
header = TRUE,
sep=";",
stringsAsFactors = FALSE,
encoding = "UTF-8") %>%
mutate( NB = as.numeric(gsub(pattern=",",replacement='.', x=NB))) %>% #ligne ajoutée pour l'import de 2009 à 2011
# rename(NIVGEO = NIVEAU, #lignes ajoutée pour l'import de 2009 à 2010
# NBPIR = C_NBPIC,
# STOCD = C_STOCD) %>%
filter(NIVGEO == "COM") %>%
select (-NIVGEO , -LIBGEO) %>%
# select (-NIVGEO , -REG, -DEP, -EPCI) %>% #utilisé pour 2009
# select (-NIVGEO , -REG, -DEP) %>% #utilisé pour 2010
mutate(STOCD = replace(STOCD, STOCD == "23", "21"), #regroupement des locataires de logements non HLM
NBPIR = replace(NBPIR, NBPIR == "2", "1"), #regroupement des 1 pièce et 2 pièces
NBPIR = replace(NBPIR, NBPIR == "4", "3"), #regroupement des 3 pièces et 4 pièces
NBPIR = replace(NBPIR, NBPIR == "6", "5")) %>% #regroupement des 5 pièces et 6 pièces
mutate(date = make_date(millesime, 12, 31)) %>%
rename(depcom = CODGEO)
statut_occupation_des_rp1 <- statut_occupation_des_rp0 %>%
group_by(depcom,date, NBPIR, STOCD) %>%
summarise(valeur = sum(NB, na.rm=T)) %>%
ungroup() %>%
mutate(variable = paste(STOCD, NBPIR)) %>%
mutate(variable = replace(variable, variable == "10 1", "nb_rp_proprietaire_1a2_pieces"),
variable = replace(variable, variable == "10 3", "nb_rp_proprietaire_3a4_pieces"),
variable = replace(variable, variable == "10 5", "nb_rp_proprietaire_5_pieces_et_plus"),
variable = replace(variable, variable == "21 1", "nb_rp_locataire_non_hlm_1a2_pieces"),
variable = replace(variable, variable == "21 3", "nb_rp_locataire_non_hlm_3a4_pieces"),
variable = replace(variable, variable == "21 5", "nb_rp_locataire_non_hlm_5_pieces_et_plus"),
variable = replace(variable, variable == "22 1", "nb_rp_locataire_hlm_1a2_pieces"),
variable = replace(variable, variable == "22 3", "nb_rp_locataire_hlm_3a4_pieces"),
variable = replace(variable, variable == "22 5", "nb_rp_locataire_hlm_5_pieces_et_plus"),
variable = replace(variable, variable == "30 1", "nb_rp_gratuit_1a2_pieces"),
variable = replace(variable, variable == "30 3", "nb_rp_gratuit_3a4_pieces"),
variable = replace(variable, variable == "30 5", "nb_rp_gratuit_5_pieces_et_plus")) %>%
select (depcom, date, variable, valeur) %>%
complete(depcom, date, variable, fill = list(valeur = 0))
statut_occupation_des_rp2 <- statut_occupation_des_rp0 %>%
group_by(depcom,date, TYPLR, STOCD) %>%
summarise(valeur = sum(NB, na.rm=T)) %>%
ungroup() %>%
mutate(variable = paste(STOCD, TYPLR)) %>%
mutate(variable = replace(variable, variable == "21 1", "nb_rp_locataire_non_hlm_maison"),
variable = replace(variable, variable == "21 2", "nb_rp_locataire_non_hlm_appartement"),
variable = replace(variable, variable == "21 3", "nb_rp_locataire_non_hlm_autre"),
variable = replace(variable, variable == "22 1", "nb_rp_locataire_hlm_maison"),
variable = replace(variable, variable == "22 2", "nb_rp_locataire_hlm_appartement"),
variable = replace(variable, variable == "22 3", "nb_rp_locataire_hlm_autre"),
variable = replace(variable, variable == "10 1", "nb_rp_proprietaire_maison"),
variable = replace(variable, variable == "10 2", "nb_rp_proprietaire_appartement"),
variable = replace(variable, variable == "10 3", "nb_rp_proprietaire_autre"),
variable = replace(variable, variable == "30 1", "nb_rp_gratuit_maison"),
variable = replace(variable, variable == "30 2", "nb_rp_gratuit_appartement"),
variable = replace(variable, variable == "30 3", "nb_rp_gratuit_autre")) %>%
select (depcom, date, variable, valeur) %>%
complete(depcom, date, variable, fill = list(valeur = 0))
statut_occupation_des_rp <- bind_rows(statut_occupation_des_rp1,statut_occupation_des_rp2) %>%
pivot_wider(names_from = variable, values_from = valeur)
statut_occupation_des_rp <- bind_rows(statut_occupation_des_rp_old,statut_occupation_des_rp) %>%
distinct()
save(statut_occupation_des_rp,file="extdata/statut_occupation_des_rp.RData")
# versement dans le sgbd/datamart.portrait_territoires et metadonnées -------------
source("R/poster_documenter_data.R", encoding = "UTF-8")
poster_documenter_it(df = statut_occupation_des_rp ,
nom_table_sgbd = "source_statut_occupation_des_rp",
comm_source_en_plus = "")
rm(list = ls())
Loading