R/nz.R

In spData: Datasets for Spatial Analysis

#' @name nz
#' @aliases new_zealand
#' @title Regions in New Zealand
#'
#' @description 
#' 
#' Polygons representing the 16 regions of New Zealand (2018).
#' See \url{https://en.wikipedia.org/wiki/Regions_of_New_Zealand} for a description of these regions
#' and \url{https://www.stats.govt.nz} for information on the data source
#' 
#' @format FORMAT:
#' \itemize{
#'     \item{Name: Name}
#'     \item{Island: Island}
#'     \item{Land_area: Land area}
#'     \item{Population: Population}
#'     \item{Median_income: Median income (NZD)}
#'     \item{Sex_ratio: Sex ratio (male/female)}
#'     \item{geom: sfc_MULTIPOLYGON}
#' }
#' 
#' @seealso 
#' See the nzcensus package: https://github.com/ellisp/nzelect
#' 
#' @source \url{https://www.stats.govt.nz}
#' @source \url{https://en.wikipedia.org/wiki/Regions_of_New_Zealand}
#' @docType data
#' @keywords datasets sf
#' 
#' @examples 
#' if (requireNamespace("sf", quietly = TRUE)) {
#'   library(sf)
#'   summary(nz)
#'   plot(nz)
#' }
#' \dontrun{
#' # Find "Regional Council 2018 Clipped (generalised)"
#' # select the GeoPackage option in the "Vectors/tables" dropdown
#' # at https://datafinder.stats.govt.nz/data/ (requires registration)
#' # Save the result as:
#' unzip("statsnzregional-council-2018-clipped-generalised-GPKG.zip")
#' library(sf)
#' library(tidyverse)
#' nz_full = st_read("regional-council-2018-clipped-generalised.gpkg")
#' print(object.size(nz_full), units = "Kb") # 14407.2 Kb
#' nz = rmapshaper::ms_simplify(nz_full, keep = 0.001, sys = TRUE)
#' print(object.size(nz), units = "Kb") # 39.9 Kb
#' names(nz)
#' nz$REGC2018_V1_00_NAME
#' nz = filter(nz, REGC2018_V1_00_NAME != "Area Outside Region") %>%
#'         select(Name = REGC2018_V1_00_NAME, `Land_area` = LAND_AREA_SQ_KM)
#' # regions basic info
#' # devtools::install_github("hadley/rvest")
#' library(rvest)
#' doc = read_html("https://en.wikipedia.org/wiki/Regions_of_New_Zealand") %>%
#'         html_nodes("div table")
#' tab = doc[[3]] %>% html_table()
#' tab = tab %>% select(Name = Region, Population = `Population[20]`, Island)
#' tab = tab %>% mutate(Population = str_replace_all(Population, ",", "")) %>%
#'         mutate(Population = as.numeric(Population)) %>%
#'         mutate(Name = str_remove_all(Name, " \\([1-9]\\)?.+"))
#' nz$Name = as.character(nz$Name)
#' nz$Name = str_remove(nz$Name, " Region")
#' nz$Name %in% tab$Name
#' # regions additional info
#' library(nzcensus)
#' nz_add_data = REGC2013 %>% 
#'         select(Name = REGC2013_N, Median_income = MedianIncome2013, 
#'                PropFemale2013, PropMale2013) %>% 
#'         mutate(Sex_ratio = PropMale2013 / PropFemale2013) %>% 
#'         mutate(Name = gsub(" Region", "", Name)) %>% 
#'         select(Name, Median_income, Sex_ratio)
#' # data join
#' nz = left_join(nz, tab, by = "Name") %>% 
#'         left_join(nz_add_data, by = "Name") %>% 
#'         select(Name, Island, Land_area, Population, Median_income, Sex_ratio)
#' }
"nz"