Get Census 2022 grid dataset — z22

Retrieve the values and coordinates of gridded features from the censuses 2011 and 2022.

When we are talking about a

feature, we talk about an indicator aggregated to grid cells, e.g., age or the number of dwellings.
category, we talk about the discrete classifications of features, e.g., ages 10 to 19, 20 to 20, 30 to 39, etc.
Both feature and category have to be provided to uniquely identify a dataset.

Usage

z22_data(
  feature,
  categories = NULL,
  year = 2022,
  res = "1km",
  all_cells = FALSE,
  normalize = FALSE,
  rasterize = FALSE,
  as_sf = FALSE,
  update_cache = FALSE
)

Arguments

feature: A grid feature. See z22_features for a list of available features. You can pass both English names and legacy names (i.e., variable names from the 2011 census).
categories: One or multiple feature categories. See z22_categories for a list of available categories. If NULL, retrieves all categories for a given feature. Generally, the more categories are selected, the longer the download.
year: Census year. Currently, only 2011 and 2022 are available. Defaults to 2022.
res: Resolution of the grid dataset. Can be "100m", "1km", or "10km". If year is 2011, "10km" is not available and some features are only available at certain resolutions.
all_cells: If TRUE, joins the retrieved attribute with the complete grid from z22_grid. Otherwise, the attribute grid will contain only those grid cells with one or more recorded units. Defaults to FALSE, because loading the grid and joining with it is computationally expensive.
normalize: If TRUE and feature is a counted feature, computes shares by dividing the counts by the total number of units in the grid cell. The type of unit depends on the theme of the feature, e.g., if the feature is in theme "Buildings", the feature counts are divided by the total number of buildings. Note that this operation requires an additional download (the total number of units). Also note that sometimes (possibly due to the key-cell method), shares of over 1 are computed. Defaults to FALSE.
rasterize: If TRUE and the terra package is installed, converts the attribute coordinates to a SpatRaster.
as_sf: If TRUE and the sf package is installed, converts the attribute coordinates to an sf tibble.
update_cache: By default, both functions cache attribute files for the remainder of the R session. They are downloaded to a temporary directory and - if the file to download already exists - are recovered from the cache. In other words, when rerunning the same request multiple times, the subsequent calls should be much faster. If TRUE, disables caching for this call and overwrites the currently cached attribute file (if any) with a fresh one. Defaults to FALSE, i.e. always cache.

Value

A tibble, SpatRasterDataset or sf tibble depending on the rasterize and as_sf arguments.

If a tibble is returned each category in categories is stored in a column. If a SpatRasterDataset is returned, each category is a named layer.

Details

Half of the grids cell width is added to each coordinate in the dataset internally. According to the INSPIRE guidelines, coordinates always represent the South-west of the grid cells. Centroids represent the geographic location of grid cells better which is why they are used.

Examples

# Get gridded population
pop <- z22_data("population", res = "10km", rasterize = TRUE)
terra::plot(pop$cat_0)


# Get data about the number of people born in a EU27 country
z22_data("birth_country", categories = 21, res = "1km")
#> # A tibble: 210,556 × 3
#>    cat_21       x       y
#>     <int>   <dbl>   <dbl>
#>  1      3 4338000 2690000
#>  2     NA 4342000 2690000
#>  3     NA 4342000 2691000
#>  4     NA 4341000 2692000
#>  5      3 4342000 2692000
#>  6     NA 4342000 2693000
#>  7      3 4345000 2693000
#>  8      3 4341000 2694000
#>  9     NA 4342000 2694000
#> 10     NA 4344000 2694000
#> # ℹ 210,546 more rows