## ----setup, include = FALSE--------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) library(psgc) ## ----releases----------------------------------------------------------------- list_releases() latest_release() ## ----get-psgc----------------------------------------------------------------- ph <- get_psgc() nrow(ph) head(ph) ## ----filter-region------------------------------------------------------------ regions <- get_psgc(geographic_level = "Region") regions[, c("psgc_code", "area_name")] ## ----filter-province---------------------------------------------------------- provinces <- get_psgc(geographic_level = "Province") nrow(provinces) head(provinces[, c("psgc_code", "area_name")]) ## ----filter-multiple---------------------------------------------------------- city_mun <- get_psgc(geographic_level = c("City", "Municipality")) nrow(city_mun) ## ----filter-city-mun---------------------------------------------------------- nrow(get_psgc(geographic_level = "city_mun")) ## ----older-release------------------------------------------------------------ ph_2023 <- get_psgc("Q1_2023") nrow(ph_2023) ## ----psgc-info---------------------------------------------------------------- psgc_info("0100000000") # Region I ## ----psgc-info-multi---------------------------------------------------------- psgc_info(c("0100000000", "0102800000")) ## ----psgc-info-short---------------------------------------------------------- psgc_info("01") # same as "0100000000" — Region I psgc_info("01028") # same as "0102800000" — Ilocos Norte ## ----population-basic--------------------------------------------------------- pop <- get_population() head(pop) ## ----population-details------------------------------------------------------- pop_detailed <- get_population(details = TRUE) head(pop_detailed) ## ----population-filter-------------------------------------------------------- region_pop <- get_population(geographic_level = "Region", details = TRUE) region_pop ## ----population-wide---------------------------------------------------------- region_pop_wide <- get_population( geographic_level = "Region", details = TRUE, wide = TRUE ) region_pop_wide ## ----psgc-pop-nested---------------------------------------------------------- regions_with_pop <- get_psgc( geographic_level = "Region", include_population_data = TRUE ) # Inspect the population data for the first region regions_with_pop$population_data[[1]] ## ----map-psgc----------------------------------------------------------------- map_psgc("0100000000") # forward to the latest release ## ----map-psgc-target---------------------------------------------------------- map_psgc("0100000000", to = "Q4_2023")