data-raw/Populations.R

In INESSSQC/INESSS: Useful functions

library(data.table)
library(readxl)
# working directory = INESS/files
setwd("~/GitHub/INESSS/files")

# Importer population révisée
revis <- as.data.table(read_xlsx("EstimRevisAnnuel_2011_2017_v20180328.xlsx",
                                 sheet = "Âge", skip = 4))
setnames(revis, c("Niveau géographique", "Code du territoire", "Année", "Sexe"),  # renommer les colonnes
         c("GEO", "CODE", "ANNEE", "SEXE"))
revis <- melt(revis,  # Variables en Observations
              id.vars = c("GEO", "CODE", "ANNEE", "SEXE"),
              measure.vars = 7:98,
              variable.name = "AGE",
              value.name = "N")
revis <- revis[SEXE != "Total" & AGE != "Tous les âges"]  # supprimer totaux
# Modifier valeurs
revis[GEO == "Québec", GEO := "QC"]  # supprimer accent
revis[  # Age
  AGE == "Moins un an", AGE := "0"
][
  AGE == "90 ans ou plus", AGE := "90"
]
revis[, AGE := as.integer(as.character(AGE))]  # convertir en integer
revis[  #   Sexe
  SEXE == "Masculin", SEXE := "M"
][
  SEXE == "Féminin", SEXE := "F"
]

# Séparer les GEO
for(geo in unique(revis$GEO)){
  dt <- revis[GEO == geo]
  assign(paste0("pop_revis_",geo), dt)
}
rm(dt, revis, geo)



# Importer population estimée
estim <- as.data.table(read_xlsx("EstimProjComp_1996_2036_v20170503.xlsx",
                                 sheet = "Âge", skip = 4))
setnames(estim, c("Niveau géographique", "Code du territoire", "Année", "Sexe"),  # renommer les colonnes
         c("GEO", "CODE", "ANNEE", "SEXE"))
estim <- melt(estim,  # Variables en Observations
              id.vars = c("GEO", "CODE", "ANNEE", "SEXE"),
              measure.vars = 7:98,
              variable.name = "AGE",
              value.name = "N")
estim <- estim[SEXE != "Total" & AGE != "Tous les âges"]  # supprimer totaux
# Modifier valeurs
estim[GEO == "Québec", GEO := "QC"]  # supprimer accent
estim[  # Age
  AGE == "Moins un an", AGE := "0"
  ][
    AGE == "90 ans ou plus", AGE := "90"
    ]
estim[, AGE := as.integer(as.character(AGE))]  # convertir en integer
estim[  #   Sexe
  SEXE == "Masculin", SEXE := "M"
  ][
    SEXE == "Féminin", SEXE := "F"
    ]

# Séparer les GEO
for(geo in unique(estim$GEO)){
  dt <- estim[GEO == geo]
  assign(paste0("pop_estim_",geo), dt)
}
rm(dt, estim, geo)



setwd("~/GitHub/INESSS/data")
usethis::use_data(pop_estim_CLSC,
                  pop_estim_QC,
                  pop_estim_RLS,
                  pop_estim_RSS,
                  pop_estim_RTS,
                  pop_estim_RUIS,
                  pop_revis_CLSC,
                  pop_revis_QC,
                  pop_revis_RLS,
                  pop_revis_RSS,
                  pop_revis_RTS,
                  pop_revis_RUIS)