Data Sets with Geometries of Dutch Provinces, Municipalities and Zip Codes

Data Sets with Geometries of Dutch Provinces, Municipalities and Zip Codes

geo_gemeenten

geo_ggdregios

geo_nuts3

geo_postcodes2

geo_postcodes3

geo_postcodes4

geo_postcodes6

geo_provincies

Format

An object of class sf (inherits from data.frame) with 345 rows and 4 columns.

An object of class sf (inherits from data.frame) with 25 rows and 4 columns.

An object of class sf (inherits from data.frame) with 40 rows and 4 columns.

An object of class sf (inherits from data.frame) with 90 rows and 4 columns.

An object of class sf (inherits from data.frame) with 798 rows and 4 columns.

An object of class sf (inherits from data.frame) with 4068 rows and 4 columns.

An object of class sf (inherits from data.frame) with 58481 rows and 4 columns.

An object of class sf (inherits from data.frame) with 12 rows and 4 columns.

Source

The data in these data.frames are retrieved from, and publicly available at, Statistics Netherlands:

• Centraal Bureau voor de Statistiek (CBS), 'Gebiedsindelingen', GPKG 2022 v1, https://www.cbs.nl

• Centraal Bureau voor de Statistiek (CBS), 'Kerncijfers per postcode', ZIP 2020 v1, https://www.cbs.nl

Details

These data.frames are of additional class sf and contain 3 variables:

• ...
  name of the area, these are: –geo_gemeenten$gemeente–, –geo_ggdregios$ggdregio–, –geo_nuts3$nuts3–, –geo_postcodes2$postcode–, –geo_postcodes3$postcode–, –geo_postcodes4$postcode–, –geo_postcodes6$postcode–, –geo_provincies$provincie–

• inwoners
  number of inhabitants in the area

• oppervlakte_km2
  area in square kilometres

• geometry
  multipolygonal object of the area

All data sets have the coordinate reference system (CRS) set to EPSG:28992 ('RD New'), following the sphere of Earth. They can be flattened to e.g. EPSG:4326 ('WGS 84') using st_transform().

See the repository file to update these data sets.

NOTE: all data sets contains all areas of the whole country of the Netherlands, except for geo_postcodes6 which was cropped to only cover the Certe region (using crop_certe()).

Examples

if (require("certeplot2")) {

  geo_postcodes6 |>
    filter_geolocation(plaats == "Groningen") |>
    plot2(category = inwoners / oppervlakte_km2,
          datalabels = FALSE,
          title = "City of Groningen (PC6 level)")
  
}


if (require("certeplot2")) {

  geo_postcodes4 |>
    filter_geolocation(plaats == "Groningen") |>
    plot2(category = inwoners / oppervlakte_km2,
          datalabels = FALSE,
          title = "City of Groningen (PC4 level)")
  
}
#> ✖ No observations, returning an empty plot


if (require("sf")) {

  head(geo_gemeenten)

}
#> Loading required package: sf
#> Linking to GEOS 3.10.2, GDAL 3.4.1, PROJ 8.2.1; sf_use_s2() is TRUE
#> Simple feature collection with 6 features and 3 fields
#> Geometry type: MULTIPOLYGON
#> Dimension:     XY
#> Bounding box:  xmin: 73315.68 ymin: 408354.7 xmax: 258967.1 ymax: 587337.6
#> Projected CRS: Amersfoort / RD New
#>           gemeente inwoners oppervlakte_km2                       geometry
#> 1    's-Gravenhage   548260        85.59080 MULTIPOLYGON (((82600.18 45...
#> 2 's-Hertogenbosch   155485       117.75078 MULTIPOLYGON (((158923.7 41...
#> 3      Aa en Hunze    25405       278.77436 MULTIPOLYGON (((248973.7 56...
#> 4         Aalsmeer    31990        32.32516 MULTIPOLYGON (((113740.1 47...
#> 5           Aalten    27125        97.08071 MULTIPOLYGON (((235537.5 44...
#> 6    Achtkarspelen    28505       104.00588 MULTIPOLYGON (((210504.1 58...