| esp_get_nuts | R Documentation |
The GISCO statistical unit dataset represents the NUTS (nomenclature of territorial units for statistics) and statistical regions using multipart polygon, polyline and point topology. The NUTS geographical information is completed by attribute tables and a set of cartographic help lines to better visualise multipart polygonal regions.
The NUTS are a hierarchical system divided into 3 levels:
NUTS 1: major socio-economic regions
NUTS 2: basic regions for the application of regional policies
NUTS 3: small regions for specific diagnoses.
Also, there is a NUTS 0 level, which usually corresponds to the national boundaries.
esp_get_nuts(
year = 2024,
epsg = 4258,
cache = TRUE,
update_cache = FALSE,
cache_dir = NULL,
verbose = FALSE,
resolution = 1,
spatialtype = c("RG", "LB"),
region = NULL,
nuts_level = c("all", "0", "1", "2", "3"),
moveCAN = TRUE,
ext = "gpkg"
)
year |
year character string or number. Release year of the file. See
|
epsg |
character string or number. Projection of the map: 4-digit EPSG code. One of:
|
cache |
logical. Whether to do caching. Default is |
update_cache |
logical. Should the cached file be refreshed? Default
is |
cache_dir |
character string. A path to a cache directory. See
Caching strategies section in |
verbose |
logical. If |
resolution |
character string or number. Resolution of the geospatial data. One of:
|
spatialtype |
character string. Type of geometry to be returned. Options available are:
|
region |
Optional. A vector of region names, NUTS or ISO codes
(see |
nuts_level |
character string. NUTS level. One of |
moveCAN |
A logical |
ext |
character. Extension of the file (default |
The NUTS nomenclature is a hierarchical classification of statistical regions and subdivides the EU economic territory into regions of three different levels (NUTS 1, 2 and 3, moving respectively from larger to smaller territorial units). NUTS 1 is the most aggregated level. An additional Country level (NUTS 0) is also available for countries where the nation at statistical level does not coincide with the administrative boundaries.
The NUTS classification has been officially established through Commission Delegated Regulation 2019/1755. A non-official NUTS-like classification has been defined for the EFTA countries, candidate countries and potential candidates based on a bilateral agreement between Eurostat and the respective statistical agencies.
An introduction to the NUTS classification is available here: https://ec.europa.eu/eurostat/web/nuts/overview.
A sf object.
Please check the download and usage provisions on gisco_attributions().
https://gisco-services.ec.europa.eu/distribution/v2/.
Copyright: https://ec.europa.eu/eurostat/web/gisco/geodata/administrative-units.
giscoR::gisco_get_nuts(), esp_dict_region_code().
Other datasets representing political borders:
esp_get_capimun(),
esp_get_ccaa(),
esp_get_ccaa_siane(),
esp_get_comarca(),
esp_get_countries_siane(),
esp_get_gridmap,
esp_get_munic(),
esp_get_munic_siane(),
esp_get_prov(),
esp_get_prov_siane(),
esp_get_simpl,
esp_get_spain(),
esp_get_spain_siane(),
esp_siane_bulk_download()
Other nuts:
esp_get_spain()
Datasets provided by GISCO:
esp_get_ccaa(),
esp_get_munic(),
esp_get_prov(),
esp_get_spain()
nuts1 <- esp_get_nuts(nuts_level = 1, moveCAN = TRUE)
library(ggplot2)
ggplot(nuts1) +
geom_sf() +
labs(
title = "NUTS1: Displacing Canary Islands",
caption = giscoR::gisco_attributions()
)
nuts1_alt <- esp_get_nuts(nuts_level = 1, moveCAN = c(15, 0))
ggplot(nuts1_alt) +
geom_sf() +
labs(
title = "NUTS1: Displacing Canary Islands",
subtitle = "to the right",
caption = giscoR::gisco_attributions()
)
nuts1_orig <- esp_get_nuts(nuts_level = 1, moveCAN = FALSE)
ggplot(nuts1_orig) +
geom_sf() +
labs(
title = "NUTS1",
subtitle = "Canary Islands on the true location",
caption = giscoR::gisco_attributions()
)
and_orient <- esp_get_nuts(region = c(
"Almeria", "Granada",
"Jaen", "Malaga"
))
ggplot(and_orient) +
geom_sf()
random_regions <- esp_get_nuts(region = c("ES1", "ES300", "ES51"))
ggplot(random_regions) +
geom_sf() +
labs(title = "Random Regions")
mixing_codes <- esp_get_nuts(region = c("ES4", "ES-PV", "Valencia"))
ggplot(mixing_codes) +
geom_sf() +
labs(title = "Mixing Codes")
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