This package has multiple use cases, though they all revolve around data from the Danish Web Address API. If the below examples are not enough, please do read through the other vignettes. First we need to load the package.
library(dawaR)
#> ## {dawaR} provides data from the Danish Agency of Climate Data
#> ## Terms and conditions apply.
#> ## Read more at: https://dawadocs.dataforsyningen.dk/dok/om#vilkaarGetting regional data for Denmark
To get a dataframe of all the regions in Denmark, you can use the
get_data() function.
get_data("regioner")
#> dagi_id kode navn nuts2 ændret
#> 1 389098 1081 Region Nordjylland DK05 2024-10-04T21:02:54.978Z
#> 2 389101 1082 Region Midtjylland DK04 2024-10-11T21:03:05.131Z
#> 3 389102 1083 Region Syddanmark DK03 2024-10-04T21:02:54.978Z
#> 4 389099 1084 Region Hovedstaden DK01 2024-10-04T21:02:54.978Z
#> 5 389100 1085 Region Sjælland DK02 2024-10-22T21:04:04.354Z
#> geo_ændret geo_version bbox_xmin bbox_ymin bbox_xmax bbox_ymax
#> 1 2024-10-04T21:02:54.978Z 32 8.189517 56.53455 11.22599 57.76025
#> 2 2024-10-11T21:03:05.131Z 43 8.078876 55.64438 11.66419 56.84326
#> 3 2024-10-04T21:02:54.978Z 32 8.063203 54.71828 10.99555 55.95325
#> 4 2024-10-04T21:02:54.978Z 31 11.602116 54.98355 15.31831 56.20520
#> 5 2024-10-22T21:04:04.354Z 29 10.814805 54.54441 12.64552 56.01731
#> visueltcenter_x visueltcenter_y
#> 1 10.112829 57.30716
#> 2 9.605032 56.23399
#> 3 9.028461 55.56317
#> 4 12.279374 55.97239
#> 5 11.621319 55.43979This will return data on each of the five regions.
Using DAWA to crosstab municipalities and their regions.
The function get_data() fetches the data in
json format and by default transforms it to a
data.frame.
library(dawaR)
library(dplyr)
municipalities <- get_data("kommuner")
nordjylland <- municipalities |>
filter(regionsnavn == "Region Nordjylland") |>
pull(navn)
nordjylland
#> [1] "Morsø" "Thisted" "Brønderslev" "Frederikshavn"
#> [5] "Vesthimmerlands" "Læsø" "Rebild" "Mariagerfjord"
#> [9] "Jammerbugt" "Aalborg" "Hjørring"Here we have extracted all the municipalities that are in “Region
Nordjylland”. The same can be done for voting precincts or police
regions. It can also be done for addresses and others. Look through the
available sections with available_sections().
Using DAWA map data
The function get_map_data() fetches data in
geojson format and transforms the geometries to
sf polygons. These polygons can be drawn as nice maps
with ggplot2.
library(dawaR)
library(ggplot2)
municipalities <- get_map_data("kommuner")
#> → Getting data on `kommuner`. This usually takes 13.13s.
#> Fetching data from the API. This will take some time.
#> Reading data to `st`.
#> Converting map data to `sf` object
ggplot(municipalities, aes(fill = regionsnavn)) +
geom_sf(color = "black") +
labs(fill = "Region") +
cowplot::theme_map()
For more information on how to plot maps with dawaR
please consult vignette("printing_maps").