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Disclaimer

References

-
+
Lahti, Leo, Janne Huovari, Markus Kainu, and Przemysław Biecek. 2017. “Retrieval and Analysis of Eurostat Open Data with the eurostat Package.” The R Journal 9 (1): 385–92. https://doi.org/10.32614/RJ-2017-019.
diff --git a/pkgdown.yml b/pkgdown.yml index 84d372b5..6e0298fd 100644 --- a/pkgdown.yml +++ b/pkgdown.yml @@ -3,7 +3,7 @@ pkgdown: 2.1.1 pkgdown_sha: ~ articles: giscoR: giscoR.html -last_built: 2024-09-23T08:26Z +last_built: 2024-09-23T14:08Z urls: reference: https://ropengov.github.io/giscoR/reference article: https://ropengov.github.io/giscoR/articles diff --git a/reference/gisco_clear_cache.html b/reference/gisco_clear_cache.html index 06defb5d..7fd1f348 100644 --- a/reference/gisco_clear_cache.html +++ b/reference/gisco_clear_cache.html @@ -110,7 +110,7 @@

Examples# Don't run this! It would modify your current state # \dontrun{ gisco_clear_cache(verbose = TRUE) -#> giscoR cached data deleted: C:\Users\RUNNER~1\AppData\Local\Temp\RtmpCerdeS/giscoR +#> giscoR cached data deleted: C:\Users\RUNNER~1\AppData\Local\Temp\RtmpS07t9H/giscoR Sys.getenv("GISCO_CACHE_DIR") #> [1] "" @@ -119,15 +119,15 @@

Examplesnewcache <- file.path(tempdir(), "giscoR", "pkgdown") newcache -#> [1] "C:\\Users\\RUNNER~1\\AppData\\Local\\Temp\\RtmpCerdeS/giscoR/pkgdown" +#> [1] "C:\\Users\\RUNNER~1\\AppData\\Local\\Temp\\RtmpS07t9H/giscoR/pkgdown" gisco_set_cache_dir(newcache) -#> giscoR cache dir is: C:\Users\RUNNER~1\AppData\Local\Temp\RtmpCerdeS/giscoR/pkgdown +#> giscoR cache dir is: C:\Users\RUNNER~1\AppData\Local\Temp\RtmpS07t9H/giscoR/pkgdown #> To install your cache_dir path for use in future sessions, #> run this function with `install = TRUE`. Sys.getenv("GISCO_CACHE_DIR") -#> [1] "C:\\Users\\RUNNER~1\\AppData\\Local\\Temp\\RtmpCerdeS/giscoR/pkgdown" +#> [1] "C:\\Users\\RUNNER~1\\AppData\\Local\\Temp\\RtmpS07t9H/giscoR/pkgdown" # }

diff --git a/reference/gisco_get_grid.html b/reference/gisco_get_grid.html index 7a6ab46a..9b8eb326 100644 --- a/reference/gisco_get_grid.html +++ b/reference/gisco_get_grid.html @@ -127,7 +127,7 @@

Author<

Examples

# \donttest{
 grid <- gisco_get_grid(resolution = 20)
-#> Warning: GDAL Message 1: GPKG: unrecognized user_version=0x00000000 (0) on 'C:\Users\runneradmin\AppData\Local\Temp\RtmpCerdeS\giscoR\pkgdown\grid_20km_surf.gpkg'
+#> Warning: GDAL Message 1: GPKG: unrecognized user_version=0x00000000 (0) on 'C:\Users\runneradmin\AppData\Local\Temp\RtmpS07t9H\giscoR\pkgdown\grid_20km_surf.gpkg'
 
 # If downloaded correctly proceed
 
diff --git a/reference/gisco_set_cache_dir.html b/reference/gisco_set_cache_dir.html
index 063bae96..cf5a2dff 100644
--- a/reference/gisco_set_cache_dir.html
+++ b/reference/gisco_set_cache_dir.html
@@ -138,14 +138,14 @@ 

Examples# \dontrun{ gisco_set_cache_dir(verbose = TRUE) #> Using a temporary cache dir. Set 'cache_dir' to a value for store permanently -#> giscoR cache dir is: C:\Users\RUNNER~1\AppData\Local\Temp\RtmpCerdeS/giscoR +#> giscoR cache dir is: C:\Users\RUNNER~1\AppData\Local\Temp\RtmpS07t9H/giscoR # } Sys.getenv("GISCO_CACHE_DIR") -#> [1] "C:\\Users\\RUNNER~1\\AppData\\Local\\Temp\\RtmpCerdeS/giscoR" +#> [1] "C:\\Users\\RUNNER~1\\AppData\\Local\\Temp\\RtmpS07t9H/giscoR" gisco_detect_cache_dir() -#> [1] "C:\\Users\\RUNNER~1\\AppData\\Local\\Temp\\RtmpCerdeS/giscoR" +#> [1] "C:\\Users\\RUNNER~1\\AppData\\Local\\Temp\\RtmpS07t9H/giscoR"

diff --git a/search.json b/search.json index a01ef904..1a2c084d 100644 --- a/search.json +++ b/search.json @@ -1 +1 @@ -[{"path":"https://ropengov.github.io/giscoR/articles/giscoR.html","id":"introduction","dir":"Articles","previous_headings":"","what":"Introduction","title":"Get started with giscoR","text":"Full site examples vignettes https://ropengov.github.io/giscoR/ giscoR package designed provide clean interaction GISCO API. Within Eurostat, GISCO responsible meeting European Commission’s geographical information needs 3 levels: European Union, member countries, regions. GISCO also provides variety shapefiles different formats, focusing specially European Union area, providing also worldwide shapefiles, country polygons, labels borders coastal lines. GISCO provides data different resolutions suitable representing small areas (01M, 03M) well lightweight datasets specially useful representing wider areas (10M, 20M, 60M). Shapefiles provided 3 different projections: EPSG 4326, 3035 3857. giscoR returns sf class objects, see https://r-spatial.github.io/sf/.","code":""},{"path":"https://ropengov.github.io/giscoR/articles/giscoR.html","id":"caching","dir":"Articles","previous_headings":"","what":"Caching","title":"Get started with giscoR","text":"giscoR provides dataset caching capability, set : file available locally, downloaded directory next time need corresponding data loaded local directory. experience problems downloading, can also manually download file GISCO API website store local directory.","code":"gisco_set_cache_dir(\"./path/to/location\")"},{"path":"https://ropengov.github.io/giscoR/articles/giscoR.html","id":"downloading-data","dir":"Articles","previous_headings":"","what":"Downloading data","title":"Get started with giscoR","text":"Please aware downloading provisions apply using GISCO data: data downloaded page used printed electronic publication, addition provisions applicable whole Eurostat website, data source acknowledged legend map introductory page publication following copyright notice: EN: © EuroGeographics administrative boundaries FR: © EuroGeographics pour les limites administratives DE: © EuroGeographics bezüglich der Verwaltungsgrenzen publications languages English, French German, translation copyright notice language publication shall used. intend use data commercially, please contact EuroGeographics information regarding licence agreements. function, gisco_attributions() guide topic. also provides attributions several languages.","code":"library(giscoR) gisco_attributions(lang = \"en\") #> [1] \"© EuroGeographics for the administrative boundaries\" gisco_attributions(lang = \"fr\") #> [1] \"© EuroGeographics pour les limites administratives\" gisco_attributions(lang = \"de\") #> [1] \"© EuroGeographics bezuglich der Verwaltungsgrenzen\""},{"path":"https://ropengov.github.io/giscoR/articles/giscoR.html","id":"basic-example","dir":"Articles","previous_headings":"","what":"Basic example","title":"Get started with giscoR","text":"examples data downloads Political map Asia can select specific countries name (language), ISO 3 codes Eurostat codes. restriction can’t mix country names, ISO3 Eurostat codes one single call. possible also combine different shapefiles, just set resolution epsg (optionally year) value: Political map North Africa","code":"library(sf) library(ggplot2) # Use ggplot for plotting asia <- gisco_get_countries(region = \"Asia\") ggplot(asia) + geom_sf(fill = \"cornsilk\", color = \"#887e6a\") + theme( panel.background = element_rect(fill = \"#fffff3\"), panel.border = element_rect(colour = \"#887e6a\", fill = NA, linewidth = 1.5), axis.text = element_text( family = \"serif\", colour = \"#887e6a\", face = \"bold\" ) ) africa_north <- gisco_get_countries( country = c( \"Morocco\", \"Argelia\", \"Libia\", \"Tunisia\", \"Egypt\" ), resolution = \"20\", epsg = \"4326\", year = \"2016\" ) # Coastal lines coast <- gisco_get_coastallines(resolution = \"20\", epsg = \"4326\", year = \"2016\") # Plot ggplot(coast) + geom_sf(color = \"grey80\") + geom_sf(data = africa_north, fill = \"grey30\", color = \"white\") + coord_sf(xlim = c(-13, 37), ylim = c(18.5, 40)) + facet_wrap(vars(NAME_ENGL), ncol = 2)"},{"path":"https://ropengov.github.io/giscoR/articles/giscoR.html","id":"thematic-maps-with-giscor","dir":"Articles","previous_headings":"","what":"Thematic maps with giscoR","title":"Get started with giscoR","text":"example giscoR can play nicely Eurostat data. plotting purposes use ggplot2 package however package handles sf objects (e.g. tmap, mapsf, leaflet, etc. used). Also colorspace rcartocolor packages recommended, provide great color palettes. Disposable income private households NUTS 2 regions (2021)","code":"# EU members library(dplyr) library(eurostat) nuts2 <- gisco_get_nuts( year = \"2021\", epsg = \"3035\", resolution = \"10\", nuts_level = \"2\" ) # Borders from countries borders <- gisco_get_countries(epsg = \"3035\", year = \"2020\", resolution = \"3\") eu_bord <- borders %>% filter(CNTR_ID %in% nuts2$CNTR_CODE) # Eurostat data - Disposable income pps <- get_eurostat(\"tgs00026\") %>% filter(TIME_PERIOD == \"2021-01-01\") nuts2_sf <- nuts2 %>% left_join(pps, by = \"geo\") %>% mutate( values_th = values / 1000, categ = cut(values_th, c(0, 15, 30, 60, 90, 120, Inf)) ) # Adjust the labels labs <- levels(nuts2_sf$categ) labs[1] <- \"< 15\" labs[6] <- \"> 120\" levels(nuts2_sf$categ) <- labs # Finally the plot ggplot(nuts2_sf) + # Background geom_sf(data = borders, fill = \"#e1e1e1\", color = NA) + geom_sf(aes(fill = categ), color = \"grey20\", linewidth = .1) + geom_sf(data = eu_bord, fill = NA, color = \"black\", linewidth = .15) + # Center in Europe: EPSG 3035 coord_sf(xlim = c(2377294, 6500000), ylim = c(1413597, 5228510)) + # Legends and color scale_fill_manual( values = hcl.colors(length(labs), \"Geyser\", rev = TRUE), # Label NA labels = function(x) { ifelse(is.na(x), \"No Data\", x) }, na.value = \"#e1e1e1\" ) + guides(fill = guide_legend(nrow = 1)) + theme_void() + theme( text = element_text(colour = \"grey0\"), panel.background = element_rect(fill = \"#97dbf2\"), panel.border = element_rect(fill = NA, color = \"grey10\"), plot.title = element_text(hjust = 0.5, vjust = -1, size = 12), plot.subtitle = element_text( hjust = 0.5, vjust = -2, face = \"bold\", margin = margin(b = 10, t = 5), size = 12 ), plot.caption = element_text( size = 8, hjust = 0.5, margin = margin(b = 2, t = 13) ), legend.text = element_text(size = 7, ), legend.title = element_text(size = 7), legend.position = \"bottom\", legend.direction = \"horizontal\", legend.text.position = \"bottom\", legend.title.position = \"top\", legend.key.height = rel(0.5), legend.key.width = unit(.1, \"npc\") ) + # Annotate and labels labs( title = \"Disposable income of private households (2021)\", subtitle = \"NUTS-2 level\", fill = \"euros (thousands)\", caption = paste0( \"Source: Eurostat\\n \", gisco_attributions() ) )"},{"path":"https://ropengov.github.io/giscoR/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Diego Hernangómez. Author, maintainer, copyright holder. rOpenGov EuroGeographics. Copyright holder. administrative boundaries. Vincent Arel-Bundock. Copyright holder. gisco_countrycode dataset.","code":""},{"path":"https://ropengov.github.io/giscoR/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Hernangómez D (2024). giscoR: Download Map Data GISCO API - Eurostat. doi:10.32614/CRAN.package.giscoR, https://ropengov.github.io/giscoR/.","code":"@Manual{R-giscoR, title = {{giscoR}: Download Map Data from GISCO API - Eurostat}, doi = {10.32614/CRAN.package.giscoR}, author = {Diego Hernangómez}, year = {2024}, version = {0.6.0}, url = {https://ropengov.github.io/giscoR/}, abstract = {Tools to download data from the GISCO (Geographic Information System of the Commission) Eurostat database . Global and European map data available. This package is in no way officially related to or endorsed by Eurostat.}, }"},{"path":[]},{"path":"https://ropengov.github.io/giscoR/CONTRIBUTING.html","id":"fixing-typos","dir":"","previous_headings":"","what":"Fixing typos","title":"CONTRIBUTING","text":"Small typos grammatical errors documentation may edited directly using GitHub web interface, long changes made source file. YES ✔️: edit roxygen comment .R file R/. ❌: edit .Rd file man/.","code":""},{"path":"https://ropengov.github.io/giscoR/CONTRIBUTING.html","id":"prerequisites","dir":"","previous_headings":"","what":"Prerequisites","title":"CONTRIBUTING","text":"make substantial pull request, always file issue make sure someone team agrees ’s problem. ’ve found bug, create associated issue illustrate bug minimal reprex.","code":""},{"path":"https://ropengov.github.io/giscoR/CONTRIBUTING.html","id":"pull-request-process","dir":"","previous_headings":"","what":"Pull request process","title":"CONTRIBUTING","text":"recommend create Git branch pull request (PR). Look R-CMD-check build status . making changes, run devtools::check() ensure new Notes, Warnings Errors appearing. recommend tidyverse style guide. also use styler package apply styles, please don’t restyle code nothing PR. use roxygen2. use testthat. Contributions test cases included easier accept. user-facing changes, add bullet top NEWS.md current development version header describing changes made followed GitHub username, links relevant issue(s)/PR(s).","code":""},{"path":"https://ropengov.github.io/giscoR/CONTRIBUTING.html","id":"prefer-to-email","dir":"","previous_headings":"","what":"Prefer to Email?","title":"CONTRIBUTING","text":"Email person listed maintainer DESCRIPTION file repo. Though note private discussions email don’t help others - course email totally warranted ’s sensitive problem kind.","code":""},{"path":"https://ropengov.github.io/giscoR/CONTRIBUTING.html","id":"thanks-for-contributing","dir":"","previous_headings":"","what":"Thanks for contributing!","title":"CONTRIBUTING","text":"contributing guide adapted tidyverse contributing guide available https://raw.githubusercontent.com/r-lib/usethis/master/inst/templates/tidy-contributing.md","code":""},{"path":"https://ropengov.github.io/giscoR/index.html","id":"giscor-","dir":"","previous_headings":"","what":"giscoR | R package for download geodata from GISCO - Eurostat","title":"giscoR | R package for download geodata from GISCO - Eurostat","text":"giscoR API package helps retrieve data Eurostat - GISCO (Geographic Information System COmmission). also provides lightweight data sets ready use without downloading. GISCO geospatial open data repository including several data sets countries, coastal lines, labels NUTS levels. data sets usually provided several resolution levels (60M/20M/10M/03M/01M) 3 different projections (4326/3035/3857). Note package provide metadata downloaded files, information available API webpage. Full site examples vignettes https://ropengov.github.io/giscoR/","code":""},{"path":"https://ropengov.github.io/giscoR/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"giscoR | R package for download geodata from GISCO - Eurostat","text":"Install giscoR CRAN: can install developing version giscoR : Alternatively, can install giscoR using r-universe:","code":"install.packages(\"giscoR\") remotes::install_github(\"rOpenGov/giscoR\") install.packages(\"giscoR\", repos = c(\"https://ropengov.r-universe.dev\", \"https://cloud.r-project.org\") )"},{"path":"https://ropengov.github.io/giscoR/index.html","id":"usage","dir":"","previous_headings":"","what":"Usage","title":"giscoR | R package for download geodata from GISCO - Eurostat","text":"script highlights features giscoR :","code":"library(giscoR) library(sf) library(dplyr) # Different resolutions DNK_res60 <- gisco_get_countries(resolution = \"60\", country = \"DNK\") %>% mutate(res = \"60M\") DNK_res20 <- gisco_get_countries(resolution = \"20\", country = \"DNK\") %>% mutate(res = \"20M\") DNK_res10 <- gisco_get_countries(resolution = \"10\", country = \"DNK\") %>% mutate(res = \"10M\") DNK_res03 <- gisco_get_countries(resolution = \"03\", country = \"DNK\") %>% mutate(res = \"03M\") DNK_all <- bind_rows(DNK_res60, DNK_res20, DNK_res10, DNK_res03) # Plot ggplot2 library(ggplot2) ggplot(DNK_all) + geom_sf(fill = \"tomato\") + facet_wrap(vars(res)) + theme_minimal() # Labels and Lines available labs <- gisco_get_countries( spatialtype = \"LB\", region = \"Africa\", epsg = \"3857\" ) coast <- gisco_get_countries( spatialtype = \"COASTL\", epsg = \"3857\" ) # For zooming afr_bbox <- st_bbox(labs) ggplot(coast) + geom_sf(col = \"deepskyblue4\", linewidth = 3) + geom_sf(data = labs, fill = \"springgreen4\", col = \"darkgoldenrod1\", size = 5, shape = 21) + coord_sf( xlim = afr_bbox[c(\"xmin\", \"xmax\")], ylim = afr_bbox[c(\"ymin\", \"ymax\")] )"},{"path":"https://ropengov.github.io/giscoR/index.html","id":"labels","dir":"","previous_headings":"Usage","what":"Labels","title":"giscoR | R package for download geodata from GISCO - Eurostat","text":"example labeled map using ggplot2:","code":"ITA <- gisco_get_nuts(country = \"Italy\", nuts_level = 1) ggplot(ITA) + geom_sf() + geom_sf_text(aes(label = NAME_LATN)) + theme(axis.title = element_blank())"},{"path":"https://ropengov.github.io/giscoR/index.html","id":"thematic-maps","dir":"","previous_headings":"Usage","what":"Thematic maps","title":"giscoR | R package for download geodata from GISCO - Eurostat","text":"example thematic map plotted ggplot2 package. information extracted via eurostat package (Lahti et al. 2017). follow fantastic approach presented Milos Popovic post: start extracting corresponding geographic data: now download data Eurostat: last, merge manipulate data creating final plot:","code":"# Get shapes nuts3 <- gisco_get_nuts( year = \"2021\", epsg = \"3035\", resolution = \"10\", nuts_level = \"3\" ) # Group by NUTS by country and convert to lines country_lines <- nuts3 %>% group_by( CNTR_CODE ) %>% summarise(n = n()) %>% st_cast(\"MULTILINESTRING\") # Use eurostat library(eurostat) popdens <- get_eurostat(\"demo_r_d3dens\") %>% filter(TIME_PERIOD == \"2021-01-01\") # Merge data nuts3_sf <- nuts3 %>% left_join(popdens, by = \"geo\") nuts3_sf <- nuts3 %>% left_join(popdens, by = c(\"NUTS_ID\" = \"geo\")) # Breaks and labels br <- c(0, 25, 50, 100, 200, 500, 1000, 2500, 5000, 10000, 30000) labs <- prettyNum(br[-1], big.mark = \",\") # Label function to be used in the plot, mainly for NAs labeller_plot <- function(x) { ifelse(is.na(x), \"No Data\", x) } nuts3_sf <- nuts3_sf %>% # Cut with labels mutate(values_cut = cut(values, br, labels = labs)) # Palette pal <- hcl.colors(length(labs), \"Lajolla\") # Plot ggplot(nuts3_sf) + geom_sf(aes(fill = values_cut), linewidth = 0, color = NA, alpha = 0.9) + geom_sf(data = country_lines, col = \"black\", linewidth = 0.1) + # Center in Europe: EPSG 3035 coord_sf( xlim = c(2377294, 7453440), ylim = c(1313597, 5628510) ) + # Legends scale_fill_manual( values = pal, # Label for NA labels = labeller_plot, drop = FALSE, guide = guide_legend(direction = \"horizontal\", nrow = 1) ) + # Theming theme_void() + # Theme theme( plot.title = element_text( color = rev(pal)[2], size = rel(1.5), hjust = 0.5, vjust = -6 ), plot.subtitle = element_text( color = rev(pal)[2], size = rel(1.25), hjust = 0.5, vjust = -10, face = \"bold\" ), plot.caption = element_text(color = \"grey60\", hjust = 0.5, vjust = 0), legend.text = element_text(color = \"grey20\", hjust = .5), legend.title = element_text(color = \"grey20\", hjust = .5), legend.position = \"bottom\", legend.title.position = \"top\", legend.text.position = \"bottom\", legend.key.height = unit(.5, \"line\"), legend.key.width = unit(2.5, \"line\") ) + # Annotate and labs labs( title = \"Population density in 2021\", subtitle = \"NUTS-3 level\", fill = \"people per sq. kilometer\", caption = paste0( \"Source: Eurostat, \", gisco_attributions(), \"\\nBased on Milos Popovic: \", \"https://milospopovic.net/how-to-make-choropleth-map-in-r/\" ) )"},{"path":"https://ropengov.github.io/giscoR/index.html","id":"a-note-on-caching","dir":"","previous_headings":"","what":"A note on caching","title":"giscoR | R package for download geodata from GISCO - Eurostat","text":"data sets (Local Administrative Units - LAU, high-resolution files) may size larger 50MB. can use giscoR create local repository given local directory passing following function: can also download manually files (.geojson format) store local directory.","code":"gisco_set_cache_dir(\"./path/to/location\")"},{"path":[]},{"path":"https://ropengov.github.io/giscoR/index.html","id":"api-data-packages","dir":"","previous_headings":"Recommended packages","what":"API data packages","title":"giscoR | R package for download geodata from GISCO - Eurostat","text":"eurostat (Lahti et al. 2017): API package provides access open data Eurostat.","code":""},{"path":"https://ropengov.github.io/giscoR/index.html","id":"plotting-sf-objects","dir":"","previous_headings":"Recommended packages","what":"Plotting sf objects","title":"giscoR | R package for download geodata from GISCO - Eurostat","text":"packages recommended visualization : tmap ggplot2 + ggspatial + tidyterra mapsf leaflet","code":""},{"path":"https://ropengov.github.io/giscoR/index.html","id":"contribute","dir":"","previous_headings":"","what":"Contribute","title":"giscoR | R package for download geodata from GISCO - Eurostat","text":"Check GitHub page source code. Contributions welcome: Use issue tracker feedback bug reports. Send pull requests Star us GitHub page","code":""},{"path":"https://ropengov.github.io/giscoR/index.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"giscoR | R package for download geodata from GISCO - Eurostat","text":"cite ‘giscoR’ publications use: Hernangómez D (2024). giscoR: Download Map Data GISCO API - Eurostat. doi:10.32614/CRAN.package.giscoR https://doi.org/10.32614/CRAN.package.giscoR, https://ropengov.github.io/giscoR/. BibTeX entry LaTeX users ","code":"@Manual{R-giscoR, title = {{giscoR}: Download Map Data from GISCO API - Eurostat}, doi = {10.32614/CRAN.package.giscoR}, author = {Diego Hernangómez}, year = {2024}, version = {0.6.0}, url = {https://ropengov.github.io/giscoR/}, abstract = {Tools to download data from the GISCO (Geographic Information System of the Commission) Eurostat database . Global and European map data available. This package is in no way officially related to or endorsed by Eurostat.}, }"},{"path":"https://ropengov.github.io/giscoR/index.html","id":"copyright-notice","dir":"","previous_headings":"","what":"Copyright notice","title":"giscoR | R package for download geodata from GISCO - Eurostat","text":"data downloaded page used printed electronic publication, addition provisions applicable whole Eurostat website, data source acknowledged legend map introductory page publication following copyright notice: EN: © EuroGeographics administrative boundaries. FR: © EuroGeographics pour les limites administratives. DE: © EuroGeographics bezüglich der Verwaltungsgrenzen. publications languages English, French German, translation copyright notice language publication shall used. intend use data commercially, please contact EuroGeographics information regarding licence agreements. GISCO Web","code":""},{"path":"https://ropengov.github.io/giscoR/index.html","id":"disclaimer","dir":"","previous_headings":"","what":"Disclaimer","title":"giscoR | R package for download geodata from GISCO - Eurostat","text":"package way officially related endorsed Eurostat.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"GNU General Public License","title":"GNU General Public License","text":"Version 3, 29 June 2007Copyright © 2007 Free Software Foundation, Inc.  Everyone permitted copy distribute verbatim copies license document, changing allowed.","code":""},{"path":"https://ropengov.github.io/giscoR/LICENSE.html","id":"preamble","dir":"","previous_headings":"","what":"Preamble","title":"GNU General Public License","text":"GNU General Public License free, copyleft license software kinds works. licenses software practical works designed take away freedom share change works. contrast, GNU General Public License intended guarantee freedom share change versions program–make sure remains free software users. , Free Software Foundation, use GNU General Public License software; applies also work released way authors. can apply programs, . speak free software, referring freedom, price. 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Termination","title":"GNU General Public License","text":"may propagate modify covered work except expressly provided License. attempt otherwise propagate modify void, automatically terminate rights License (including patent licenses granted third paragraph section 11). However, cease violation License, license particular copyright holder reinstated () provisionally, unless copyright holder explicitly finally terminates license, (b) permanently, copyright holder fails notify violation reasonable means prior 60 days cessation. Moreover, license particular copyright holder reinstated permanently copyright holder notifies violation reasonable means, first time received notice violation License (work) copyright holder, cure violation prior 30 days receipt notice. 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Interpretation of Sections 15 and 16","title":"GNU General Public License","text":"disclaimer warranty limitation liability provided given local legal effect according terms, reviewing courts shall apply local law closely approximates absolute waiver civil liability connection Program, unless warranty assumption liability accompanies copy Program return fee. END TERMS CONDITIONS","code":""},{"path":"https://ropengov.github.io/giscoR/LICENSE.html","id":"how-to-apply-these-terms-to-your-new-programs","dir":"","previous_headings":"","what":"How to Apply These Terms to Your New Programs","title":"GNU General Public License","text":"develop new program, want greatest possible use public, best way achieve make free software everyone can redistribute change terms. , attach following notices program. safest attach start source file effectively state exclusion warranty; file least “copyright” line pointer full notice found. Also add information contact electronic paper mail. program terminal interaction, make output short notice like starts interactive mode: hypothetical commands show w show c show appropriate parts General Public License. course, program’s commands might different; GUI interface, use “box”. also get employer (work programmer) school, , sign “copyright disclaimer” program, necessary. information , apply follow GNU GPL, see . GNU General Public License permit incorporating program proprietary programs. program subroutine library, may consider useful permit linking proprietary applications library. want , use GNU Lesser General Public License instead License. first, please read .","code":"giscoR - Download Geospatial Data from GISCO API (Eurostat). Copyright (C) 2020 Diego Hernangómez This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program. If not, see . giscoR Copyright (C) 2020 Diego Hernangómez This program comes with ABSOLUTELY NO WARRANTY; for details type 'show w'. This is free software, and you are welcome to redistribute it under certain conditions; type 'show c' for details."},{"path":"https://ropengov.github.io/giscoR/reference/giscoR-package.html","id":null,"dir":"Reference","previous_headings":"","what":"giscoR: Download Map Data from GISCO API - Eurostat — giscoR-package","title":"giscoR: Download Map Data from GISCO API - Eurostat — giscoR-package","text":"Tools download data GISCO (Geographic Information System Commission) Eurostat database https://ec.europa.eu/eurostat/web/gisco. Global European map data available. package way officially related endorsed Eurostat.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/giscoR-package.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"giscoR: Download Map Data from GISCO API - Eurostat — giscoR-package","text":"Maintainer: Diego Hernangómez diego.hernangomezherrero@gmail.com (ORCID) (rOpenGov) [copyright holder] contributors: EuroGeographics (administrative boundaries.) [copyright holder] Vincent Arel-Bundock (ORCID) (gisco_countrycode dataset.) [copyright holder]","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_addressapi.html","id":null,"dir":"Reference","previous_headings":"","what":"GISCO Address API — gisco_addressapi","title":"GISCO Address API — gisco_addressapi","text":"Access GISCO Address API, allows carry geocoding reverse geocoding using pan-european address database. endpoint available implemented specific function, see Details. API supports fuzzy searching (also referred approximate string matching) parameters endpoint.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_addressapi.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"GISCO Address API — gisco_addressapi","text":"","code":"gisco_addressapi_search( country = NULL, province = NULL, city = NULL, road = NULL, housenumber = NULL, postcode = NULL, verbose = FALSE ) gisco_addressapi_reverse(x, y, country = NULL, verbose = FALSE) gisco_addressapi_bbox( country = NULL, province = NULL, city = NULL, road = NULL, postcode = NULL, verbose = FALSE ) gisco_addressapi_countries(verbose = FALSE) gisco_addressapi_provinces(country = NULL, city = NULL, verbose = FALSE) gisco_addressapi_cities(country = NULL, province = NULL, verbose = FALSE) gisco_addressapi_roads( country = NULL, province = NULL, city = NULL, verbose = FALSE ) gisco_addressapi_housenumbers( country = NULL, province = NULL, city = NULL, road = NULL, postcode = NULL, verbose = FALSE ) gisco_addressapi_postcodes( country = NULL, province = NULL, city = NULL, verbose = FALSE ) gisco_addressapi_copyright(verbose = FALSE)"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_addressapi.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"GISCO Address API — gisco_addressapi","text":"country Country code (country = \"LU\"). province province within country. list provinces within certain country use provinces endpoint (gisco_addressapi_provinces(country = \"LU\")). city city within province. list cities within certain province use cities endpoint (gisco_addressapi_cities(province = \"capellen\")). road road within city. housenumber house number house name within road street. postcode Can used combination previous parameters. verbose Logical, displays information. Useful debugging, default FALSE. x, y x y coordinates (longitude latitude) converted human-readable address.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_addressapi.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"GISCO Address API — gisco_addressapi","text":"data.frame object cases, except gisco_addressapi_search(), gisco_addressapi_reverse() gisco_addressapi_bbox(), return sf object.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_addressapi.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"GISCO Address API — gisco_addressapi","text":"Brief description API endpoints (source GISCO Address API \\> Endpoints: resulting object may present following variables:","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_addressapi.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"GISCO Address API — gisco_addressapi","text":"","code":"# \\donttest{ # Cities in a region gisco_addressapi_cities(country = \"PT\", province = \"LISBOA\") #> L2 #> 1 AJUDA #> 2 ALCABIDECHE #> 3 ALCOENTRE #> 4 ALCÂNTARA #> 5 ALFRAGIDE #> 6 ALGUBER #> 7 ALGUEIRÃO-MEM MARTINS #> 8 ALVALADE #> 9 AREEIRO #> 10 ARRANHÓ #> 11 ARROIOS #> 12 ARRUDA DOS VINHOS #> 13 AVEIRAS DE BAIXO #> 14 AVEIRAS DE CIMA #> 15 AVENIDAS NOVAS #> 16 AZAMBUJA #> 17 BARCARENA #> 18 BEATO #> 19 BELÉM #> 20 BENFICA #> 21 BUCELAS #> 22 CAMPO DE OURIQUE #> 23 CAMPOLIDE #> 24 CARDOSAS #> 25 CARNIDE #> 26 CARNOTA #> 27 CARVOEIRA #> 28 CASAL DE CAMBRA #> 29 COLARES #> 30 ENCARNAÇÃO #> 31 ENCOSTA DO SOL #> 32 ERICEIRA #> 33 ESTRELA #> 34 FALAGUEIRA-VENDA NOVA #> 35 FANHÕES #> 36 FREIRIA #> 37 LOURES #> 38 LOUSA #> 39 LUMIAR #> 40 MAFRA #> 41 MARVILA #> 42 MECA #> 43 MILHARADO #> 44 MINA DE ÁGUA #> 45 MISERICÓRDIA #> 46 MOITA DOS FERREIROS #> 47 ODIVELAS #> 48 OLHALVO #> 49 OLIVAIS #> 50 OTA #> 51 PARQUE DAS NAÇÕES #> 52 PENHA DE FRANÇA #> 53 PERAL #> 54 PONTE DO ROL #> 55 PORTO SALVO #> 56 RAMALHAL #> 57 REGUENGO GRANDE #> 58 RIBAMAR #> 59 RIO DE MOURO #> 60 S. TIAGO DOS VELHOS #> 61 SANTA BÁRBARA #> 62 SANTA CLARA #> 63 SANTA MARIA MAIOR #> 64 SANTA MARIA, SÃO PEDRO E MATACÃES #> 65 SANTO ANTÓNIO #> 66 SANTO ISIDORO #> 67 SANTO QUINTINO #> 68 SAPATARIA #> 69 SILVEIRA #> 70 SOBRAL DE MONTE AGRAÇO #> 71 SÃO DOMINGOS DE BENFICA #> 72 SÃO DOMINGOS DE RANA #> 73 SÃO PEDRO DA CADEIRA #> 74 SÃO VICENTE #> 75 TURCIFAL #> 76 UNIÃO DAS FREGUESIAS DE A DOS CUNHADOS E MACEIRA #> 77 UNIÃO DAS FREGUESIAS DE ABRIGADA E CABANAS DE TORRES #> 78 UNIÃO DAS FREGUESIAS DE AGUALVA E MIRA-SINTRA #> 79 UNIÃO DAS FREGUESIAS DE ALDEIA GALEGA DA MERCEANA E ALDEIA GAVINHA #> 80 UNIÃO DAS FREGUESIAS DE ALENQUER (SANTO ESTÊVÃO E TRIANA) #> 81 UNIÃO DAS FREGUESIAS DE ALGÉS, LINDA-A-VELHA E CRUZ QUEBRADA-DAFUNDO #> 82 UNIÃO DAS FREGUESIAS DE ALHANDRA, SÃO JOÃO DOS MONTES E CALHANDRIZ #> 83 UNIÃO DAS FREGUESIAS DE ALMARGEM DO BISPO, PÊRO PINHEIRO E MONTELAVAR #> 84 UNIÃO DAS FREGUESIAS DE ALVERCA DO RIBATEJO E SOBRALINHO #> 85 UNIÃO DAS FREGUESIAS DE AZUEIRA E SOBRAL DA ABELHEIRA #> 86 UNIÃO DAS FREGUESIAS DE CAMARATE, UNHOS E APELAÇÃO #> 87 UNIÃO DAS FREGUESIAS DE CAMPELOS E OUTEIRO DA CABEÇA #> 88 UNIÃO DAS FREGUESIAS DE CARCAVELOS E PAREDE #> 89 UNIÃO DAS FREGUESIAS DE CARNAXIDE E QUEIJAS #> 90 UNIÃO DAS FREGUESIAS DE CARREGADO E CADAFAIS #> 91 UNIÃO DAS FREGUESIAS DE CARVOEIRA E CARMÕES #> 92 UNIÃO DAS FREGUESIAS DE CASCAIS E ESTORIL #> 93 UNIÃO DAS FREGUESIAS DE CASTANHEIRA DO RIBATEJO E CACHOEIRAS #> 94 UNIÃO DAS FREGUESIAS DE DOIS PORTOS E RUNA #> 95 UNIÃO DAS FREGUESIAS DE ENXARA DO BISPO, GRADIL E VILA FRANCA DO ROSÁRIO #> 96 UNIÃO DAS FREGUESIAS DE IGREJA NOVA E CHELEIROS #> 97 UNIÃO DAS FREGUESIAS DE LAMAS E CERCAL #> 98 UNIÃO DAS FREGUESIAS DE LOURINHÃ E ATALAIA #> 99 UNIÃO DAS FREGUESIAS DE MALVEIRA E SÃO MIGUEL DE ALCAINÇA #> 100 UNIÃO DAS FREGUESIAS DE MANIQUE DO INTENDENTE, VILA NOVA DE SÃO PEDRO E MAÇUSSA #> 101 UNIÃO DAS FREGUESIAS DE MASSAMÁ E MONTE ABRAÃO #> 102 UNIÃO DAS FREGUESIAS DE MAXIAL E MONTE REDONDO #> 103 UNIÃO DAS FREGUESIAS DE MIRAGAIA E MARTELEIRA #> 104 UNIÃO DAS FREGUESIAS DE MOSCAVIDE E PORTELA #> 105 UNIÃO DAS FREGUESIAS DE OEIRAS E SÃO JULIÃO DA BARRA, PAÇO DE ARCOS E CAXIAS #> 106 UNIÃO DAS FREGUESIAS DE PAINHO E FIGUEIROS #> 107 UNIÃO DAS FREGUESIAS DE PONTINHA E FAMÕES #> 108 UNIÃO DAS FREGUESIAS DE PÓVOA DE SANTA IRIA E FORTE DA CASA #> 109 UNIÃO DAS FREGUESIAS DE PÓVOA DE SANTO ADRIÃO E OLIVAL BASTO #> 110 UNIÃO DAS FREGUESIAS DE QUELUZ E BELAS #> 111 UNIÃO DAS FREGUESIAS DE RAMADA E CANEÇAS #> 112 UNIÃO DAS FREGUESIAS DE RIBAFRIA E PEREIRO DE PALHACANA #> 113 UNIÃO DAS FREGUESIAS DE SACAVÉM E PRIOR VELHO #> 114 UNIÃO DAS FREGUESIAS DE SANTA IRIA DE AZOIA, SÃO JOÃO DA TALHA E BOBADELA #> 115 UNIÃO DAS FREGUESIAS DE SANTO ANTÃO E SÃO JULIÃO DO TOJAL #> 116 UNIÃO DAS FREGUESIAS DE SANTO ANTÓNIO DOS CAVALEIROS E FRIELAS #> 117 UNIÃO DAS FREGUESIAS DE SINTRA (SANTA MARIA E SÃO MIGUEL, SÃO MARTINHO E SÃO PEDRO DE PENAFERRIM) #> 118 UNIÃO DAS FREGUESIAS DE SÃO BARTOLOMEU DOS GALEGOS E MOLEDO #> 119 UNIÃO DAS FREGUESIAS DE SÃO JOÃO DAS LAMPAS E TERRUGEM #> 120 UNIÃO DAS FREGUESIAS DE VENDA DO PINHEIRO E SANTO ESTÊVÃO DAS GALÉS #> 121 UNIÃO DAS FREGUESIAS DO CACÉM E SÃO MARCOS #> 122 UNIÃO DAS FREGUESIAS DO CADAVAL E PÊRO MONIZ #> 123 VALE DO PARAÍSO #> 124 VENTEIRA #> 125 VENTOSA #> 126 VERMELHA #> 127 VIALONGA #> 128 VILA FRANCA DE XIRA #> 129 VILA NOVA DA RAINHA #> 130 VILA VERDE DOS FRANCOS #> 131 VILAR #> 132 VIMEIRO #> 133 ÁGUAS LIVRES # Geocode and reverse geocode with sf objects # Structured search struct <- gisco_addressapi_search( country = \"ES\", city = \"BARCELONA\", road = \"GRACIA\" ) struct #> Simple feature collection with 356 features and 13 fields #> Geometry type: POINT #> Dimension: XY #> Bounding box: xmin: 2.149583 ymin: 41.38821 xmax: 2.170311 ymax: 41.41935 #> Geodetic CRS: WGS 84 #> First 10 features: #> LD TF L2 L1 L0 PC N0 N1 N2 N3 #> 1 91 PS GRACIA BARCELONA CATALUÑA/CATALUNYA ES 8008 ES ES5 ES51 ES511 #> 2 93 PS GRACIA BARCELONA CATALUÑA/CATALUNYA ES 8008 ES ES5 ES51 ES511 #> 3 103 PS GRACIA BARCELONA CATALUÑA/CATALUNYA ES 8008 ES ES5 ES51 ES511 #> 4 101 PS GRACIA BARCELONA CATALUÑA/CATALUNYA ES 8008 ES ES5 ES51 ES511 #> 5 105 PS GRACIA BARCELONA CATALUÑA/CATALUNYA ES 8008 ES ES5 ES51 ES511 #> 6 107 PS GRACIA BARCELONA CATALUÑA/CATALUNYA ES 8008 ES ES5 ES51 ES511 #> 7 99 PS GRACIA BARCELONA CATALUÑA/CATALUNYA ES 8008 ES ES5 ES51 ES511 #> 8 97 PS GRACIA BARCELONA CATALUÑA/CATALUNYA ES 8008 ES ES5 ES51 ES511 #> 9 96 PS GRACIA BARCELONA CATALUÑA/CATALUNYA ES 8008 ES ES5 ES51 ES511 #> 10 94 PS GRACIA BARCELONA CATALUÑA/CATALUNYA ES 8008 ES ES5 ES51 ES511 #> OL X Y geometry #> 1 8FH495V6+WCV 2.161046 41.39487 POINT (2.161046 41.39487) #> 2 8FH495V6+X9R 2.160902 41.39499 POINT (2.160902 41.39499) #> 3 8FH495W5+7XW 2.159969 41.39574 POINT (2.159969 41.39574) #> 4 8FH495W6+727 2.160050 41.39567 POINT (2.16005 41.39567) #> 5 8FH495W5+9W3 2.159792 41.39588 POINT (2.159792 41.39588) #> 6 8FH495W5+CRJ 2.159529 41.39610 POINT (2.159529 41.3961) #> 7 8FH495W6+45H 2.160484 41.39532 POINT (2.160484 41.39532) #> 8 8FH495W6+36W 2.160582 41.39524 POINT (2.160582 41.39524) #> 9 8FH495W6+5GP 2.161332 41.39545 POINT (2.161332 41.39545) #> 10 8FH495W6+4HW 2.161452 41.39535 POINT (2.161452 41.39535) # Reverse geocoding reverse <- gisco_addressapi_reverse(x = struct$X[1], y = struct$Y[1]) reverse #> Simple feature collection with 5 features and 13 fields #> Geometry type: POINT #> Dimension: XY #> Bounding box: xmin: 2.160902 ymin: 41.39446 xmax: 2.161126 ymax: 41.39499 #> Geodetic CRS: WGS 84 #> LD TF L2 L1 L0 PC N0 N1 N2 N3 #> 1 91 PS GRACIA BARCELONA CATALUÑA/CATALUNYA ES 8008 ES ES5 ES51 ES511 #> 2 89 PS GRACIA BARCELONA CATALUÑA/CATALUNYA ES 8008 ES ES5 ES51 ES511 #> 3 93 PS GRACIA BARCELONA CATALUÑA/CATALUNYA ES 8008 ES ES5 ES51 ES511 #> 4 257 CL PROVENÇA BARCELONA CATALUÑA/CATALUNYA ES 8008 ES ES5 ES51 ES511 #> 5 255 CL PROVENÇA BARCELONA CATALUÑA/CATALUNYA ES 8008 ES ES5 ES51 ES511 #> OL X Y geometry #> 1 8FH495V6+WCV 2.161046 41.39487 POINT (2.161046 41.39487) #> 2 8FH495V6+WFC 2.161126 41.39480 POINT (2.161126 41.3948) #> 3 8FH495V6+X9R 2.160902 41.39499 POINT (2.160902 41.39499) #> 4 8FH495V6+RC2 2.161020 41.39451 POINT (2.16102 41.39451) #> 5 8FH495V6+Q9P 2.160950 41.39446 POINT (2.16095 41.39446) # }"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_attributions.html","id":null,"dir":"Reference","previous_headings":"","what":"Attribution when publishing GISCO data — gisco_attributions","title":"Attribution when publishing GISCO data — gisco_attributions","text":"Get legal text used along data downloaded package.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_attributions.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Attribution when publishing GISCO data — gisco_attributions","text":"","code":"gisco_attributions(lang = \"en\", copyright = FALSE)"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_attributions.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Attribution when publishing GISCO data — gisco_attributions","text":"lang Language (two-letter ISO code). See https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes Details. copyright Boolean TRUE/FALSE. Whether display copyright notice console.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_attributions.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Attribution when publishing GISCO data — gisco_attributions","text":"string attribution used.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_attributions.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Attribution when publishing GISCO data — gisco_attributions","text":"Current languages supported : \"en\": English. \"da\": Danish. \"de\": German. \"es\": Spanish. \"fi\": Finish. \"fr\": French. \"\": Norwegian. \"sv\": Swedish. Please consider contributing spot mistake want add new language.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_attributions.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Attribution when publishing GISCO data — gisco_attributions","text":"COPYRIGHT NOTICE data downloaded GISCO used printed electronic publication, addition provisions applicable whole Eurostat website, data source acknowledged legend map introductory page publication following copyright notice: EN: (C) EuroGeographics administrative boundaries. FR: (C) EuroGeographics pour les limites administratives. DE: (C) EuroGeographics bezuglich der Verwaltungsgrenzen. publications languages English, French German, translation copyright notice language publication shall used. intend use data commercially, please contact EuroGeographics information regarding licence agreements.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_attributions.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Attribution when publishing GISCO data — gisco_attributions","text":"","code":"gisco_attributions() #> [1] \"© EuroGeographics for the administrative boundaries\" gisco_attributions(lang = \"es\", copyright = TRUE) #> #> COPYRIGHT NOTICE #> #> When data downloaded from GISCO #> is used in any printed or electronic publication, #> in addition to any other provisions applicable to #> the whole Eurostat website, data source will have #> to be acknowledged in the legend of the map and in #> the introductory page of the publication with the #> following copyright notice: #> #> - EN: (C) EuroGeographics for the administrative boundaries #> - FR: (C) EuroGeographics pour les limites administratives #> - DE: (C) EuroGeographics bezuglich der Verwaltungsgrenzen #> #> For publications in languages other than English, #> French or German, the translation of the copyright #> notice in the language of the publication shall be #> used. #> #> If you intend to use the data commercially, please #> contact EuroGeographics for information regarding #> their licence agreements. #> #> #> [1] \"© Eurogeographics para los límites administrativos\" gisco_attributions(lang = \"XXX\") #> Language xxx not supported, switching to English. #> Consider contributing: #> https://github.com/rOpenGov/giscoR/issues #> [1] \"© EuroGeographics for the administrative boundaries\""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_bulk_download.html","id":null,"dir":"Reference","previous_headings":"","what":"Bulk download from GISCO API — gisco_bulk_download","title":"Bulk download from GISCO API — gisco_bulk_download","text":"Downloads zipped data GISCO extract cache_dir folder.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_bulk_download.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Bulk download from GISCO API — gisco_bulk_download","text":"","code":"gisco_bulk_download( id_giscoR = c(\"countries\", \"coastallines\", \"communes\", \"lau\", \"nuts\", \"urban_audit\"), year = \"2016\", cache_dir = NULL, update_cache = FALSE, verbose = FALSE, resolution = \"10\", ext = c(\"geojson\", \"shp\", \"svg\", \"json\", \"gdb\"), recursive = TRUE )"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_bulk_download.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Bulk download from GISCO API — gisco_bulk_download","text":"https://gisco-services.ec.europa.eu/distribution/v2/","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_bulk_download.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Bulk download from GISCO API — gisco_bulk_download","text":"id_giscoR Type dataset downloaded. Values supported : \"coastallines\". \"communes\". \"countries\". \"lau\". \"nuts\". \"urban_audit\". year Release year file. See Details. cache_dir path cache directory. See caching. update_cache logical whether update cache. Default FALSE. set TRUE force fresh download source .geojson file. verbose Logical, displays information. Useful debugging, default FALSE. resolution Resolution geospatial data. One \"60\": 1:60million \"20\": 1:20million \"10\": 1:10million \"03\": 1:3million \"01\": 1:1million ext Extension file(s) downloaded. Formats available \"geojson\", \"shp\", \"svg\", \"json\", \"gdb\". See Details. recursive Tries unzip recursively zip files () included initial bulk download (case ext = \"shp\").","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_bulk_download.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Bulk download from GISCO API — gisco_bulk_download","text":"Silent function.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_bulk_download.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Bulk download from GISCO API — gisco_bulk_download","text":"See years available corresponding functions: gisco_get_coastallines(). gisco_get_communes(). gisco_get_countries(). gisco_get_lau(). gisco_get_nuts(). gisco_get_urban_audit(). usual extension used across giscoR \"geojson\", however formats already available GISCO.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_bulk_download.html","id":"about-caching","dir":"Reference","previous_headings":"","what":"About caching","title":"Bulk download from GISCO API — gisco_bulk_download","text":"can set cache_dir gisco_set_cache_dir(). Sometimes cached files may corrupt. case, try re-downloading data setting update_cache = TRUE. experience problem download, try download corresponding .geojson file method save cache_dir. Use option verbose = TRUE debugging API query. complete list files available check gisco_db.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_bulk_download.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Bulk download from GISCO API — gisco_bulk_download","text":"","code":"# \\dontrun{ # Countries 2016 - It would take some time gisco_bulk_download(id_giscoR = \"countries\", resolution = \"60\") # }"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_check_access.html","id":null,"dir":"Reference","previous_headings":"","what":"Check access to GISCO API — gisco_check_access","title":"Check access to GISCO API — gisco_check_access","text":"Check R access resources https://gisco-services.ec.europa.eu/distribution/v2/.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_check_access.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check access to GISCO API — gisco_check_access","text":"","code":"gisco_check_access()"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_check_access.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check access to GISCO API — gisco_check_access","text":"logical.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_check_access.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Check access to GISCO API — gisco_check_access","text":"","code":"gisco_check_access() #> [1] TRUE"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_clear_cache.html","id":null,"dir":"Reference","previous_headings":"","what":"Clear your giscoR cache dir — gisco_clear_cache","title":"Clear your giscoR cache dir — gisco_clear_cache","text":"Use function caution. function clear cached data configuration, specifically: Deletes giscoR config directory (rappdirs::user_config_dir(\"giscoR\", \"R\")). Deletes cache_dir directory. Deletes values stored Sys.getenv(\"GISCO_CACHE_DIR\") options(gisco_cache_dir).","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_clear_cache.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Clear your giscoR cache dir — gisco_clear_cache","text":"","code":"gisco_clear_cache(config = FALSE, cached_data = TRUE, verbose = FALSE)"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_clear_cache.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Clear your giscoR cache dir — gisco_clear_cache","text":"config TRUE, delete configuration folder giscoR. cached_data set TRUE, delete cache_dir content. verbose Logical, displays information. Useful debugging, default FALSE.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_clear_cache.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Clear your giscoR cache dir — gisco_clear_cache","text":"Invisible. function called side effects.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_clear_cache.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Clear your giscoR cache dir — gisco_clear_cache","text":"overkill function intended reset status never installed /used giscoR.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_clear_cache.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Clear your giscoR cache dir — gisco_clear_cache","text":"","code":"# Don't run this! It would modify your current state # \\dontrun{ gisco_clear_cache(verbose = TRUE) #> giscoR cached data deleted: C:\\Users\\RUNNER~1\\AppData\\Local\\Temp\\RtmpCerdeS/giscoR Sys.getenv(\"GISCO_CACHE_DIR\") #> [1] \"\" # Set new cache on a temp dir newcache <- file.path(tempdir(), \"giscoR\", \"pkgdown\") newcache #> [1] \"C:\\\\Users\\\\RUNNER~1\\\\AppData\\\\Local\\\\Temp\\\\RtmpCerdeS/giscoR/pkgdown\" gisco_set_cache_dir(newcache) #> giscoR cache dir is: C:\\Users\\RUNNER~1\\AppData\\Local\\Temp\\RtmpCerdeS/giscoR/pkgdown #> To install your cache_dir path for use in future sessions, #> run this function with `install = TRUE`. Sys.getenv(\"GISCO_CACHE_DIR\") #> [1] \"C:\\\\Users\\\\RUNNER~1\\\\AppData\\\\Local\\\\Temp\\\\RtmpCerdeS/giscoR/pkgdown\" # }"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_coastallines.html","id":null,"dir":"Reference","previous_headings":"","what":"World coastal lines POLYGON object — gisco_coastallines","title":"World coastal lines POLYGON object — gisco_coastallines","text":"sf object provided GISCO (2016 version).","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_coastallines.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"World coastal lines POLYGON object — gisco_coastallines","text":"POLYGON sf object (resolution: 1:20million, EPSG:4326) 3 variables: COAS_ID Coast ID. FID FID. geometry geometry field.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_coastallines.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"World coastal lines POLYGON object — gisco_coastallines","text":"COAS_RG_20M_2016_4326.geojson file.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_coastallines.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"World coastal lines POLYGON object — gisco_coastallines","text":"","code":"data(\"gisco_coastallines\") head(gisco_coastallines) #> Simple feature collection with 6 features and 2 fields #> Geometry type: POLYGON #> Dimension: XY #> Bounding box: xmin: -180 ymin: -89 xmax: 179.9948 ymax: 83.65187 #> Geodetic CRS: WGS 84 #> COAS_ID FID geometry #> 1 1 1 POLYGON ((113.6472 22.70988... #> 2 2 2 POLYGON ((-58.83353 -63.552... #> 3 3 3 POLYGON ((-94.64807 74.0768... #> 4 4 4 POLYGON ((143.5061 -12.9617... #> 5 6 6 POLYGON ((-76.4565 83.10617... #> 6 5 5 POLYGON ((-34.8436 83.57385..."},{"path":"https://ropengov.github.io/giscoR/reference/gisco_countries.html","id":null,"dir":"Reference","previous_headings":"","what":"World countries POLYGON sf object — gisco_countries","title":"World countries POLYGON sf object — gisco_countries","text":"sf object including countries provided GISCO (2016 version).","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_countries.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"World countries POLYGON sf object — gisco_countries","text":"MULTIPOLYGON data frame (resolution: 1:20million, EPSG:4326) object 257 rows 7 variables: id row ID. CNTR_NAME Official country name local language. ISO3_CODE ISO 3166-1 alpha-3 code country, provided GISCO. CNTR_ID Country ID. NAME_ENGL Country name English. FID FID. geometry geometry field.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_countries.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"World countries POLYGON sf object — gisco_countries","text":"CNTR_RG_20M_2016_4326.geojson file.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_countries.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"World countries POLYGON sf object — gisco_countries","text":"","code":"data(\"gisco_countries\") head(gisco_countries) #> Simple feature collection with 6 features and 5 fields #> Geometry type: MULTIPOLYGON #> Dimension: XY #> Bounding box: xmin: -63.09693 ymin: 17.00297 xmax: 74.88986 ymax: 42.63545 #> Geodetic CRS: WGS 84 #> CNTR_ID CNTR_NAME ISO3_CODE NAME_ENGL FID #> 1 AE الإمارات العربية المتحدة ARE United Arab Emirates AE #> 2 AF افغانستان-افغانستان AFG Afghanistan AF #> 3 AG Antigua and Barbuda ATG Antigua and Barbuda AG #> 4 AI Anguilla AIA Anguilla AI #> 5 AL Shqipëria ALB Albania AL #> 6 AM Հայաստան ARM Armenia AM #> geometry #> 1 MULTIPOLYGON (((56.35462 25... #> 2 MULTIPOLYGON (((74.7055 37.... #> 3 MULTIPOLYGON (((-61.80237 1... #> 4 MULTIPOLYGON (((-63.05444 1... #> 5 MULTIPOLYGON (((19.831 42.4... #> 6 MULTIPOLYGON (((46.45984 39..."},{"path":"https://ropengov.github.io/giscoR/reference/gisco_countrycode.html","id":null,"dir":"Reference","previous_headings":"","what":"Data frame with different country code schemes and world regions — gisco_countrycode","title":"Data frame with different country code schemes and world regions — gisco_countrycode","text":"data frame containing conversions different country code schemes (Eurostat/ISO2 3) well geographic regions provided World Bank UN (M49). data set extracted countrycode package.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_countrycode.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data frame with different country code schemes and world regions — gisco_countrycode","text":"data frame object 249 rows 13 variables: ISO3_CODE Eurostat code country. CNTR_CODE ISO 3166-1 alpha-2 code country. iso2c ISO 3166-1 alpha-3 code country. iso.name.en ISO English short name. cldr.short.en English short name provided Unicode Common Locale Data Repository. continent provided World Bank. un.region.code Numeric region code UN (M49). un.region.name Region name UN (M49). un.regionintermediate.code Numeric intermediate Region. un.regionintermediate.name Intermediate Region name UN (M49). un.regionsub.code Numeric sub-region code UN (M49). un.regionsub.name Sub-Region name UN (M49). eu Logical indicating country belongs European Union.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_countrycode.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Data frame with different country code schemes and world regions — gisco_countrycode","text":"countrycode::codelist v1.2.0.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_countrycode.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Data frame with different country code schemes and world regions — gisco_countrycode","text":"","code":"data(\"gisco_countrycode\") dplyr::glimpse(gisco_countrycode) #> Rows: 249 #> Columns: 13 #> $ ISO3_CODE \"ABW\", \"AFG\", \"AGO\", \"AIA\", \"ALA\", \"ALB\", \"… #> $ CNTR_CODE \"AW\", \"AF\", \"AO\", \"AI\", NA, \"AL\", \"AD\", \"AE… #> $ iso2c \"AW\", \"AF\", \"AO\", \"AI\", \"AX\", \"AL\", \"AD\", \"… #> $ iso.name.en \"Aruba\", \"Afghanistan\", \"Angola\", \"Anguilla… #> $ cldr.short.en \"Aruba\", \"Afghanistan\", \"Angola\", \"Anguilla… #> $ continent \"Americas\", \"Asia\", \"Africa\", \"Americas\", \"… #> $ un.region.code 19, 142, 2, 19, 150, 150, 150, 142, 19, 142… #> $ un.region.name \"Americas\", \"Asia\", \"Africa\", \"Americas\", \"… #> $ un.regionintermediate.code 29, NA, 17, 29, NA, NA, NA, NA, 5, NA, NA, … #> $ un.regionintermediate.name \"Caribbean\", NA, \"Middle Africa\", \"Caribbea… #> $ un.regionsub.code 419, 34, 202, 419, 154, 39, 39, 145, 419, 1… #> $ un.regionsub.name \"Latin America and the Caribbean\", \"Souther… #> $ eu FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, F…"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_db.html","id":null,"dir":"Reference","previous_headings":"","what":"GISCO database — gisco_db","title":"GISCO database — gisco_db","text":"Database list files package can load.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_db.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"GISCO database — gisco_db","text":"data frame","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_db.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"GISCO database — gisco_db","text":"GISCO API datasets.json.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_db.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"GISCO database — gisco_db","text":"data frame used check validity API calls.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_db.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"GISCO database — gisco_db","text":"","code":"data(gisco_db)"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get.html","id":null,"dir":"Reference","previous_headings":"","what":"Get GISCO world country sf polygons, points and lines — gisco_get_countries","title":"Get GISCO world country sf polygons, points and lines — gisco_get_countries","text":"Returns world country polygons, lines points specified scale, provided GISCO. Also, specific areas Gibraltar Antarctica presented separately. definition country used GISCO correspond roughly territories official ISO-3166 code.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get GISCO world country sf polygons, points and lines — gisco_get_countries","text":"","code":"gisco_get_countries( year = \"2016\", epsg = \"4326\", cache = TRUE, update_cache = FALSE, cache_dir = NULL, verbose = FALSE, resolution = \"20\", spatialtype = \"RG\", country = NULL, region = NULL )"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Get GISCO world country sf polygons, points and lines — gisco_get_countries","text":"https://gisco-services.ec.europa.eu/distribution/v2/","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get GISCO world country sf polygons, points and lines — gisco_get_countries","text":"year Release year file. One \"2001\", \"2006\", \"2010\", \"2013\", \"2016\", \"2020\" \"2024\". epsg projection map: 4-digit EPSG code. One : \"4258\": ETRS89 \"4326\": WGS84 \"3035\": ETRS89 / ETRS-LAEA \"3857\": Pseudo-Mercator cache logical whether caching. Default TRUE. See caching. update_cache logical whether update cache. Default FALSE. set TRUE force fresh download source .geojson file. cache_dir path cache directory. See caching. verbose Logical, displays information. Useful debugging, default FALSE. resolution Resolution geospatial data. One \"60\": 1:60million \"20\": 1:20million \"10\": 1:10million \"03\": 1:3million \"01\": 1:1million spatialtype Type geometry returned: \"BN\": Boundaries - LINESTRING object. \"COASTL\": coastlines - LINESTRING object. \"INLAND\": inland boundaries - LINESTRING object. \"LB\": Labels - POINT object. \"RG\": Regions - MULTIPOLYGON/POLYGON object. Note parameters country region applied spatialtype \"BN\" \"RG\". country Optional. character vector country codes. either vector country names, vector ISO3 country codes vector Eurostat country codes. Mixed types (c(\"Italy\",\"ES\",\"FRA\")) work. See also countrycode::countrycode(). region Optional. character vector UN M49 region codes European Union membership. Possible values \"Africa\", \"Americas\", \"Asia\", \"Europe\", \"Oceania\" \"EU\" countries belonging European Union (per 2021). See world regions gisco_countrycode.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get GISCO world country sf polygons, points and lines — gisco_get_countries","text":"sf object specified spatialtype.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Get GISCO world country sf polygons, points and lines — gisco_get_countries","text":"Please check download usage provisions gisco_attributions().","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get.html","id":"about-caching","dir":"Reference","previous_headings":"","what":"About caching","title":"Get GISCO world country sf polygons, points and lines — gisco_get_countries","text":"can set cache_dir gisco_set_cache_dir(). Sometimes cached files may corrupt. case, try re-downloading data setting update_cache = TRUE. experience problem download, try download corresponding .geojson file method save cache_dir. Use option verbose = TRUE debugging API query. complete list files available check gisco_db.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get.html","id":"world-regions","dir":"Reference","previous_headings":"","what":"World Regions","title":"Get GISCO world country sf polygons, points and lines — gisco_get_countries","text":"Regions defined per geographic regions defined UN (see https://unstats.un.org/unsd/methodology/m49/. scheme Cyprus assigned Asia. may use region = \"EU\" get EU members (reference date: 2021).","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get GISCO world country sf polygons, points and lines — gisco_get_countries","text":"","code":"cntries <- gisco_get_countries() library(ggplot2) ggplot(cntries) + geom_sf() # Get a region africa <- gisco_get_countries(region = \"Africa\") ggplot(africa) + geom_sf(fill = \"#078930\", col = \"white\") + theme_minimal()"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_airports.html","id":null,"dir":"Reference","previous_headings":"","what":"Get location of airports and ports from GISCO API — gisco_get_airports","title":"Get location of airports and ports from GISCO API — gisco_get_airports","text":"Loads sf object GISCO API local library.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_airports.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get location of airports and ports from GISCO API — gisco_get_airports","text":"","code":"gisco_get_airports( year = \"2013\", country = NULL, cache_dir = NULL, update_cache = FALSE, verbose = FALSE ) gisco_get_ports( year = \"2013\", country = NULL, cache_dir = NULL, update_cache = FALSE, verbose = FALSE )"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_airports.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Get location of airports and ports from GISCO API — gisco_get_airports","text":"https://ec.europa.eu/eurostat/web/gisco/geodata/transport-networks","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_airports.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get location of airports and ports from GISCO API — gisco_get_airports","text":"year Year reference. year available right now \"2013\". country Optional. character vector country codes. either vector country names, vector ISO3 country codes vector Eurostat country codes. Mixed types (c(\"Italy\",\"ES\",\"FRA\")) work. See also countrycode::countrycode(). cache_dir path cache directory. See caching. update_cache logical whether update cache. Default FALSE. set TRUE force fresh download source .geojson file. verbose Logical, displays information. Useful debugging, default FALSE.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_airports.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get location of airports and ports from GISCO API — gisco_get_airports","text":"POINT object EPSG:4326.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_airports.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get location of airports and ports from GISCO API — gisco_get_airports","text":"gisco_get_airports() refer Europe. shapefiles provided EPSG:4326. gisco_get_ports() adds new field CNTR_ISO2 original data identifying country port. Worldwide information available. port codes aligned UN/LOCODE standard.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_airports.html","id":"about-caching","dir":"Reference","previous_headings":"","what":"About caching","title":"Get location of airports and ports from GISCO API — gisco_get_airports","text":"can set cache_dir gisco_set_cache_dir(). Sometimes cached files may corrupt. case, try re-downloading data setting update_cache = TRUE. experience problem download, try download corresponding .geojson file method save cache_dir. Use option verbose = TRUE debugging API query. complete list files available check gisco_db.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_airports.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get location of airports and ports from GISCO API — gisco_get_airports","text":"","code":"# \\donttest{ library(sf) #> Linking to GEOS 3.12.1, GDAL 3.8.4, PROJ 9.3.1; sf_use_s2() is TRUE greece <- gisco_get_countries(country = \"EL\", resolution = 3) airp_gc <- gisco_get_airports(country = \"EL\") library(ggplot2) if (inherits(airp_gc, \"sf\")) { ggplot(greece) + geom_sf(fill = \"grey80\") + geom_sf(data = airp_gc, color = \"blue\") + labs( title = \"Airports on Greece\", shape = NULL, color = NULL, caption = gisco_attributions() ) } ############################## # Plot ports # ############################## ports <- gisco_get_ports() coast <- giscoR::gisco_coastallines # To Robinson projection :) library(sf) coast <- st_transform(coast, \"ESRI:54030\") ports <- st_transform(ports, st_crs(coast)) if (inherits(ports, \"sf\")) { ggplot(coast) + geom_sf(fill = \"#F6E1B9\", color = \"#0978AB\") + geom_sf(data = ports, fill = \"red\", shape = 21) + theme_void() + theme( panel.background = element_rect(fill = \"#C6ECFF\"), panel.grid = element_blank(), plot.title = element_text(face = \"bold\", hjust = 0.5), plot.subtitle = element_text(face = \"italic\", hjust = 0.5) ) + labs( title = \"Ports Worldwide\", subtitle = \"Year 2013\", caption = \"(c) European Union, 1995 - today\" ) } # }"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_coastallines.html","id":null,"dir":"Reference","previous_headings":"","what":"Get GISCO coastlines sf polygons — gisco_get_coastallines","title":"Get GISCO coastlines sf polygons — gisco_get_coastallines","text":"Downloads worldwide coastlines","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_coastallines.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get GISCO coastlines sf polygons — gisco_get_coastallines","text":"","code":"gisco_get_coastallines( year = \"2016\", epsg = \"4326\", cache = TRUE, update_cache = FALSE, cache_dir = NULL, verbose = FALSE, resolution = \"20\" )"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_coastallines.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Get GISCO coastlines sf polygons — gisco_get_coastallines","text":"https://gisco-services.ec.europa.eu/distribution/v2/","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_coastallines.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get GISCO coastlines sf polygons — gisco_get_coastallines","text":"year Release year. One \"2006\", \"2010\", \"2013\" \"2016\". epsg projection map: 4-digit EPSG code. One : \"4258\": ETRS89 \"4326\": WGS84 \"3035\": ETRS89 / ETRS-LAEA \"3857\": Pseudo-Mercator cache logical whether caching. Default TRUE. See caching. update_cache logical whether update cache. Default FALSE. set TRUE force fresh download source .geojson file. cache_dir path cache directory. See caching. verbose Logical, displays information. Useful debugging, default FALSE. resolution Resolution geospatial data. One \"60\": 1:60million \"20\": 1:20million \"10\": 1:10million \"03\": 1:3million \"01\": 1:1million","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_coastallines.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get GISCO coastlines sf polygons — gisco_get_coastallines","text":"sf POLYGON object.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_coastallines.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Get GISCO coastlines sf polygons — gisco_get_coastallines","text":"Please check download usage provisions gisco_attributions().","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_coastallines.html","id":"about-caching","dir":"Reference","previous_headings":"","what":"About caching","title":"Get GISCO coastlines sf polygons — gisco_get_coastallines","text":"can set cache_dir gisco_set_cache_dir(). Sometimes cached files may corrupt. case, try re-downloading data setting update_cache = TRUE. experience problem download, try download corresponding .geojson file method save cache_dir. Use option verbose = TRUE debugging API query. complete list files available check gisco_db.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_coastallines.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get GISCO coastlines sf polygons — gisco_get_coastallines","text":"","code":"coast <- gisco_get_coastallines() library(ggplot2) ggplot(coast) + geom_sf(color = \"#1278AB\", fill = \"#FDFBEA\") + # Zoom on Caribe coord_sf( xlim = c(-99, -49), ylim = c(4, 30) ) + theme_minimal() + theme( panel.background = element_rect(fill = \"#C7E7FB\", color = NA), panel.border = element_rect(colour = \"black\", fill = NA) )"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_education.html","id":null,"dir":"Reference","previous_headings":"","what":"Get locations of education services in Europe — gisco_get_education","title":"Get locations of education services in Europe — gisco_get_education","text":"dataset contains information main education services Member States.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_education.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get locations of education services in Europe — gisco_get_education","text":"","code":"gisco_get_education( year = c(\"2023\", \"2020\"), cache = TRUE, update_cache = FALSE, cache_dir = NULL, verbose = FALSE, country = NULL )"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_education.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Get locations of education services in Europe — gisco_get_education","text":"https://ec.europa.eu/eurostat/web/gisco/geodata/basic-services","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_education.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get locations of education services in Europe — gisco_get_education","text":"year Release year file. One \"2020\", \"2023\" (default). cache logical whether caching. Default TRUE. See caching. update_cache logical whether update cache. Default FALSE. set TRUE force fresh download source .geojson file. cache_dir path cache directory. See caching. verbose Logical, displays information. Useful debugging, default FALSE. country Optional. character vector country codes. either vector country names, vector ISO3 country codes vector Eurostat country codes. Mixed types (c(\"Italy\",\"ES\",\"FRA\")) work. See also countrycode::countrycode().","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_education.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get locations of education services in Europe — gisco_get_education","text":"POINT sf object.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_education.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get locations of education services in Europe — gisco_get_education","text":"Files distributed EPSG:4326. Metadata available https://gisco-services.ec.europa.eu/pub/education/metadata.pdf.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_education.html","id":"about-caching","dir":"Reference","previous_headings":"","what":"About caching","title":"Get locations of education services in Europe — gisco_get_education","text":"can set cache_dir gisco_set_cache_dir(). Sometimes cached files may corrupt. case, try re-downloading data setting update_cache = TRUE. experience problem download, try download corresponding .geojson file method save cache_dir. Use option verbose = TRUE debugging API query. complete list files available check gisco_db.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_education.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Get locations of education services in Europe — gisco_get_education","text":"dieghernan, https://github.com/dieghernan/","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_education.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get locations of education services in Europe — gisco_get_education","text":"","code":"# \\donttest{ edu_BEL <- gisco_get_education(country = \"Belgium\") # Plot if downloaded if (nrow(edu_BEL) > 3) { library(ggplot2) ggplot(edu_BEL) + geom_sf(shape = 21, size = 0.15) } # }"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_grid.html","id":null,"dir":"Reference","previous_headings":"","what":"Get grid cells covering covering Europe for various resolutions — gisco_get_grid","title":"Get grid cells covering covering Europe for various resolutions — gisco_get_grid","text":"datasets contain grid cells covering European land territory, various resolutions 1km 100km. Base statistics population figures provided cells.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_grid.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get grid cells covering covering Europe for various resolutions — gisco_get_grid","text":"","code":"gisco_get_grid( resolution = \"20\", spatialtype = c(\"REGION\", \"POINT\"), cache_dir = NULL, update_cache = FALSE, verbose = FALSE )"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_grid.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Get grid cells covering covering Europe for various resolutions — gisco_get_grid","text":"https://ec.europa.eu/eurostat/web/gisco/geodata/grids","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_grid.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get grid cells covering covering Europe for various resolutions — gisco_get_grid","text":"resolution Resolution grid cells kms. Available values \"1\", \"2\", \"5\", \"10\", \"20\", \"50\", \"100\". See Details. spatialtype Select one \"REGION\" \"POINT\". cache_dir path cache directory. See caching. update_cache logical whether update cache. Default FALSE. set TRUE force fresh download source .geojson file. verbose Logical, displays information. Useful debugging, default FALSE.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_grid.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get grid cells covering covering Europe for various resolutions — gisco_get_grid","text":"POLYGON/POINT sf object.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_grid.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get grid cells covering covering Europe for various resolutions — gisco_get_grid","text":"Files distributed EPSG:3035. file sizes range 428Kb (resolution = \"100\") 1.7Gb resolution = \"1\". resolutions 1km 2km need confirm download.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_grid.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Get grid cells covering covering Europe for various resolutions — gisco_get_grid","text":"specific downloading provisions, please see https://ec.europa.eu/eurostat/web/gisco/geodata/grids","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_grid.html","id":"about-caching","dir":"Reference","previous_headings":"","what":"About caching","title":"Get grid cells covering covering Europe for various resolutions — gisco_get_grid","text":"can set cache_dir gisco_set_cache_dir(). Sometimes cached files may corrupt. case, try re-downloading data setting update_cache = TRUE. experience problem download, try download corresponding .geojson file method save cache_dir. Use option verbose = TRUE debugging API query. complete list files available check gisco_db.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_grid.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Get grid cells covering covering Europe for various resolutions — gisco_get_grid","text":"dieghernan, https://github.com/dieghernan/","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_grid.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get grid cells covering covering Europe for various resolutions — gisco_get_grid","text":"","code":"# \\donttest{ grid <- gisco_get_grid(resolution = 20) #> Warning: GDAL Message 1: GPKG: unrecognized user_version=0x00000000 (0) on 'C:\\Users\\runneradmin\\AppData\\Local\\Temp\\RtmpCerdeS\\giscoR\\pkgdown\\grid_20km_surf.gpkg' # If downloaded correctly proceed if (!is.null(grid)) { library(dplyr) grid <- grid %>% mutate(popdens = TOT_P_2021 / 20) breaks <- c(0, 0.1, 100, 500, 1000, 5000, 10000, Inf) # Cut groups grid <- grid %>% mutate(popdens_cut = cut(popdens, breaks = breaks, include.lowest = TRUE )) cut_labs <- prettyNum(breaks, big.mark = \" \")[-1] cut_labs[1] <- \"0\" cut_labs[7] <- \"> 10 000\" pal <- c(\"black\", hcl.colors(length(breaks) - 2, palette = \"Spectral\", alpha = 0.9 )) library(ggplot2) ggplot(grid) + geom_sf(aes(fill = popdens_cut), color = NA, linewidth = 0) + coord_sf( xlim = c(2500000, 7000000), ylim = c(1500000, 5200000) ) + scale_fill_manual( values = pal, na.value = \"black\", name = \"people per sq. kilometer\", labels = cut_labs, guide = guide_legend( direction = \"horizontal\", nrow = 1 ) ) + theme_void() + labs( title = \"Population density in Europe (2021)\", subtitle = \"Grid: 20 km.\", caption = gisco_attributions() ) + theme( text = element_text(colour = \"white\"), plot.background = element_rect(fill = \"grey2\"), plot.title = element_text(hjust = 0.5), plot.subtitle = element_text(hjust = 0.5, face = \"bold\"), plot.caption = element_text( color = \"grey60\", hjust = 0.5, vjust = 0, margin = margin(t = 5, b = 10) ), legend.position = \"bottom\", legend.title.position = \"top\", legend.text.position = \"bottom\", legend.key.height = unit(0.5, \"lines\"), legend.key.width = unit(1, \"lines\") ) } #> #> Attaching package: 'dplyr' #> The following objects are masked from 'package:stats': #> #> filter, lag #> The following objects are masked from 'package:base': #> #> intersect, setdiff, setequal, union # }"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_healthcare.html","id":null,"dir":"Reference","previous_headings":"","what":"Get locations of healthcare services in Europe — gisco_get_healthcare","title":"Get locations of healthcare services in Europe — gisco_get_healthcare","text":"dataset contains information main healthcare services considered 'hospitals' Member States.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_healthcare.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get locations of healthcare services in Europe — gisco_get_healthcare","text":"","code":"gisco_get_healthcare( year = c(\"2023\", \"2020\"), cache = TRUE, update_cache = FALSE, cache_dir = NULL, verbose = FALSE, country = NULL )"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_healthcare.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Get locations of healthcare services in Europe — gisco_get_healthcare","text":"https://ec.europa.eu/eurostat/web/gisco/geodata/basic-services","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_healthcare.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get locations of healthcare services in Europe — gisco_get_healthcare","text":"year Release year file. One \"2020\", \"2023\" (default). cache logical whether caching. Default TRUE. See caching. update_cache logical whether update cache. Default FALSE. set TRUE force fresh download source .geojson file. cache_dir path cache directory. See caching. verbose Logical, displays information. Useful debugging, default FALSE. country Optional. character vector country codes. either vector country names, vector ISO3 country codes vector Eurostat country codes. Mixed types (c(\"Italy\",\"ES\",\"FRA\")) work. See also countrycode::countrycode().","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_healthcare.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get locations of healthcare services in Europe — gisco_get_healthcare","text":"POINT sf object.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_healthcare.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get locations of healthcare services in Europe — gisco_get_healthcare","text":"Files distributed EPSG:4326. Metadata available https://gisco-services.ec.europa.eu/pub/healthcare/metadata.pdf.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_healthcare.html","id":"about-caching","dir":"Reference","previous_headings":"","what":"About caching","title":"Get locations of healthcare services in Europe — gisco_get_healthcare","text":"can set cache_dir gisco_set_cache_dir(). Sometimes cached files may corrupt. case, try re-downloading data setting update_cache = TRUE. experience problem download, try download corresponding .geojson file method save cache_dir. Use option verbose = TRUE debugging API query. complete list files available check gisco_db.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_healthcare.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Get locations of healthcare services in Europe — gisco_get_healthcare","text":"dieghernan, https://github.com/dieghernan/","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_healthcare.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get locations of healthcare services in Europe — gisco_get_healthcare","text":"","code":"# \\donttest{ health_be <- gisco_get_healthcare(country = \"Belgium\") # Plot if downloaded if (inherits(health_be, \"sf\")) { library(ggplot2) ggplot(health_be) + geom_sf() } # }"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_lau.html","id":null,"dir":"Reference","previous_headings":"","what":"Get GISCO urban areas sf polygons, points and lines — gisco_get_lau","title":"Get GISCO urban areas sf polygons, points and lines — gisco_get_lau","text":"gisco_get_communes() gisco_get_lau() download shapes Local Urban Areas, correspond roughly towns cities.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_lau.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get GISCO urban areas sf polygons, points and lines — gisco_get_lau","text":"","code":"gisco_get_communes( year = \"2016\", epsg = \"4326\", cache = TRUE, update_cache = FALSE, cache_dir = NULL, verbose = FALSE, spatialtype = \"RG\", country = NULL ) gisco_get_lau( year = \"2021\", epsg = \"4326\", cache = TRUE, update_cache = FALSE, cache_dir = NULL, verbose = FALSE, country = NULL, gisco_id = NULL )"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_lau.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get GISCO urban areas sf polygons, points and lines — gisco_get_lau","text":"year Release year file: gisco_get_communes() one \"2001\", \"2004\", \"2006\", \"2008\", \"2010\", \"2013\" \"2016\". gisco_get_lau() one \"2011\", \"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", \"2018\", \"2019\", \"2020\" \"2021\". epsg projection map: 4-digit EPSG code. One : \"4258\": ETRS89 \"4326\": WGS84 \"3035\": ETRS89 / ETRS-LAEA \"3857\": Pseudo-Mercator cache logical whether caching. Default TRUE. See caching. update_cache logical whether update cache. Default FALSE. set TRUE force fresh download source .geojson file. cache_dir path cache directory. See caching. verbose Logical, displays information. Useful debugging, default FALSE. spatialtype Type geometry returned: \"BN\": Boundaries - LINESTRING object. \"COASTL\": coastlines - LINESTRING object. \"INLAND\": inland boundaries - LINESTRING object. \"LB\": Labels - POINT object. \"RG\": Regions - MULTIPOLYGON/POLYGON object. Note parameters country region applied spatialtype \"BN\" \"RG\". country Optional. character vector country codes. either vector country names, vector ISO3 country codes vector Eurostat country codes. Mixed types (c(\"Italy\",\"ES\",\"FRA\")) work. See also countrycode::countrycode(). gisco_id Optional. character vector GISCO_ID LAU values.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_lau.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get GISCO urban areas sf polygons, points and lines — gisco_get_lau","text":"sf object specified spatialtype. case gisco_get_lau(), POLYGON object.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_lau.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Get GISCO urban areas sf polygons, points and lines — gisco_get_lau","text":"Please check download usage provisions gisco_attributions().","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_lau.html","id":"about-caching","dir":"Reference","previous_headings":"","what":"About caching","title":"Get GISCO urban areas sf polygons, points and lines — gisco_get_lau","text":"can set cache_dir gisco_set_cache_dir(). Sometimes cached files may corrupt. case, try re-downloading data setting update_cache = TRUE. experience problem download, try download corresponding .geojson file method save cache_dir. Use option verbose = TRUE debugging API query. complete list files available check gisco_db.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_lau.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get GISCO urban areas sf polygons, points and lines — gisco_get_lau","text":"","code":"# \\donttest{ ire_lau <- gisco_get_communes(spatialtype = \"LB\", country = \"Ireland\") if (!is.null(ire_lau)) { library(ggplot2) ggplot(ire_lau) + geom_sf(shape = 21, col = \"#009A44\", size = 0.5) + labs( title = \"Communes in Ireland\", subtitle = \"Year 2016\", caption = gisco_attributions() ) + theme_void() + theme(text = element_text( colour = \"#009A44\", family = \"serif\", face = \"bold\" )) } # }"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_nuts.html","id":null,"dir":"Reference","previous_headings":"","what":"Get GISCO NUTS sf polygons, points and lines — gisco_get_nuts","title":"Get GISCO NUTS sf polygons, points and lines — gisco_get_nuts","text":"Returns NUTS regions polygons, lines points specified scale, provided GISCO. NUTS provided three different levels: \"0\": Country level \"1\": Groups states/regions \"2\": States/regions \"3\": Counties/provinces/districts Note NUTS-level definition may vary across countries. See also https://ec.europa.eu/eurostat/web/gisco/geodata//statistical-units/territorial-units-statistics.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_nuts.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get GISCO NUTS sf polygons, points and lines — gisco_get_nuts","text":"","code":"gisco_get_nuts( year = \"2016\", epsg = \"4326\", cache = TRUE, update_cache = FALSE, cache_dir = NULL, verbose = FALSE, resolution = \"20\", spatialtype = \"RG\", country = NULL, nuts_id = NULL, nuts_level = \"all\" )"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_nuts.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Get GISCO NUTS sf polygons, points and lines — gisco_get_nuts","text":"https://gisco-services.ec.europa.eu/distribution/v2/","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_nuts.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get GISCO NUTS sf polygons, points and lines — gisco_get_nuts","text":"year Release year file. One \"2003\", \"2006\", \"2010\", \"2013\", \"2016\", \"2021\" \"2024\". epsg projection map: 4-digit EPSG code. One : \"4258\": ETRS89 \"4326\": WGS84 \"3035\": ETRS89 / ETRS-LAEA \"3857\": Pseudo-Mercator cache logical whether caching. Default TRUE. See caching. update_cache logical whether update cache. Default FALSE. set TRUE force fresh download source .geojson file. cache_dir path cache directory. See caching. verbose Logical, displays information. Useful debugging, default FALSE. resolution Resolution geospatial data. One \"60\": 1:60million \"20\": 1:20million \"10\": 1:10million \"03\": 1:3million \"01\": 1:1million spatialtype Type geometry returned: \"BN\": Boundaries - LINESTRING object. \"LB\": Labels - POINT object. \"RG\": Regions - MULTIPOLYGON/POLYGON object. Note parameters country, nuts_level nuts_id applied spatialtype \"BN\" \"RG\". country Optional. character vector country codes. either vector country names, vector ISO3 country codes vector Eurostat country codes. Mixed types (c(\"Italy\",\"ES\",\"FRA\")) work. See also countrycode::countrycode(). nuts_id Optional. character vector NUTS IDs. nuts_level NUTS level. One \"0\", \"1\", \"2\" \"3\". See Description.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_nuts.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get GISCO NUTS sf polygons, points and lines — gisco_get_nuts","text":"sf object specified spatialtype. resulting sf object present additional column geo (equal NUTS_ID) improving compatibility eurostat package. See eurostat::get_eurostat_geospatial()). See also gisco_nuts understand columns values provided.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_nuts.html","id":"about-caching","dir":"Reference","previous_headings":"","what":"About caching","title":"Get GISCO NUTS sf polygons, points and lines — gisco_get_nuts","text":"can set cache_dir gisco_set_cache_dir(). Sometimes cached files may corrupt. case, try re-downloading data setting update_cache = TRUE. experience problem download, try download corresponding .geojson file method save cache_dir. Use option verbose = TRUE debugging API query. complete list files available check gisco_db.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_nuts.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get GISCO NUTS sf polygons, points and lines — gisco_get_nuts","text":"","code":"nuts2 <- gisco_get_nuts(nuts_level = 2) library(ggplot2) ggplot(nuts2) + geom_sf() + # ETRS89 / ETRS-LAEA coord_sf( crs = 3035, xlim = c(2377294, 7453440), ylim = c(1313597, 5628510) ) + labs(title = \"NUTS-2 levels\") # \\donttest{ # NUTS-3 for Germany germany_nuts3 <- gisco_get_nuts(nuts_level = 3, country = \"Germany\") ggplot(germany_nuts3) + geom_sf() + labs( title = \"NUTS-3 levels\", subtitle = \"Germany\", caption = gisco_attributions() ) # Select specific regions select_nuts <- gisco_get_nuts(nuts_id = c(\"ES2\", \"FRJ\", \"FRL\", \"ITC\")) ggplot(select_nuts) + geom_sf(aes(fill = CNTR_CODE)) + scale_fill_viridis_d() # }"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_postalcodes.html","id":null,"dir":"Reference","previous_headings":"","what":"Get postal code points from GISCO — gisco_get_postalcodes","title":"Get postal code points from GISCO — gisco_get_postalcodes","text":"Get postal codes points EU, EFTA candidate countries.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_postalcodes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get postal code points from GISCO — gisco_get_postalcodes","text":"","code":"gisco_get_postalcodes( year = \"2020\", country = NULL, cache_dir = NULL, update_cache = FALSE, verbose = FALSE )"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_postalcodes.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Get postal code points from GISCO — gisco_get_postalcodes","text":"https://ec.europa.eu/eurostat/web/gisco/geodata//administrative-units/postal-codes.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_postalcodes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get postal code points from GISCO — gisco_get_postalcodes","text":"year Year reference. Currently \"2020\" available. country Optional. character vector country codes. either vector country names, vector ISO3 country codes vector Eurostat country codes. Mixed types (c(\"Italy\",\"ES\",\"FRA\")) work. See also countrycode::countrycode(). cache_dir path cache directory. See caching. update_cache logical whether update cache. Default FALSE. set TRUE force fresh download source .geojson file. verbose Logical, displays information. Useful debugging, default FALSE.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_postalcodes.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get postal code points from GISCO — gisco_get_postalcodes","text":"POINT sf object EPSG:4326.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_postalcodes.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get postal code points from GISCO — gisco_get_postalcodes","text":"postal code point dataset shows location postal codes, NUTS codes Degree Urbanisation classification across EU, EFTA candidate countries variety sources. primary purpose create correspondence tables NUTS classification (EC) 1059/2003 part Tercet Regulation (EU) 2017/2391","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_postalcodes.html","id":"copyright","dir":"Reference","previous_headings":"","what":"Copyright","title":"Get postal code points from GISCO — gisco_get_postalcodes","text":"dataset released CC--SA-4.0 licence requires following attribution whenever used: (c) European Union - GISCO, 2021, postal code point dataset, Licence CC--SA 4.0 available https://ec.europa.eu/eurostat/web/gisco/geodata//administrative-units/postal-codes. Shapefiles provided ETRS89 (EPSG:4258).","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_postalcodes.html","id":"about-caching","dir":"Reference","previous_headings":"","what":"About caching","title":"Get postal code points from GISCO — gisco_get_postalcodes","text":"can set cache_dir gisco_set_cache_dir(). Sometimes cached files may corrupt. case, try re-downloading data setting update_cache = TRUE. experience problem download, try download corresponding .geojson file method save cache_dir. Use option verbose = TRUE debugging API query. complete list files available check gisco_db.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_postalcodes.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get postal code points from GISCO — gisco_get_postalcodes","text":"","code":"# Heavy-weight download! # \\dontrun{ pc_bel <- gisco_get_postalcodes(country = \"BE\") if (!is.null(pc_bel)) { library(ggplot2) ggplot(pc_bel) + geom_sf(color = \"gold\") + theme_bw() + labs( title = \"Postcodes of Belgium\", subtitle = \"2020\", caption = paste(\"(c) European Union - GISCO, 2021,\", \"postal code point dataset\", \"Licence CC-BY-SA 4.0\", sep = \"\\n\" ) ) } # }"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_units.html","id":null,"dir":"Reference","previous_headings":"","what":"Get geospatial units data from GISCO API — gisco_get_units","title":"Get geospatial units data from GISCO API — gisco_get_units","text":"Download individual shapefiles units. Unlike gisco_get_countries(), gisco_get_nuts() gisco_get_urban_audit(), downloads full dataset applies filters, gisco_get_units() downloads single shapefile unit.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_units.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get geospatial units data from GISCO API — gisco_get_units","text":"","code":"gisco_get_units( id_giscoR = c(\"nuts\", \"countries\", \"urban_audit\"), unit = \"ES4\", mode = c(\"sf\", \"df\"), year = \"2016\", epsg = \"4326\", cache = TRUE, update_cache = FALSE, cache_dir = NULL, verbose = FALSE, resolution = \"20\", spatialtype = \"RG\" )"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_units.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Get geospatial units data from GISCO API — gisco_get_units","text":"https://gisco-services.ec.europa.eu/distribution/v2/","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_units.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get geospatial units data from GISCO API — gisco_get_units","text":"id_giscoR Select unit type downloaded. Accepted values \"nuts\", \"countries\" \"urban_audit\". unit Unit ID downloaded. See Details. mode Controls output function. Possible values \"sf\" \"df\". See Value Details. year Release year file. One \"2001\", \"2006\", \"2010\", \"2013\", \"2016\", \"2020\" \"2024\". epsg projection map: 4-digit EPSG code. One : \"4258\": ETRS89 \"4326\": WGS84 \"3035\": ETRS89 / ETRS-LAEA \"3857\": Pseudo-Mercator cache logical whether caching. Default TRUE. See caching. update_cache logical whether update cache. Default FALSE. set TRUE force fresh download source .geojson file. cache_dir path cache directory. See caching. verbose Logical, displays information. Useful debugging, default FALSE. resolution Resolution geospatial data. One \"60\": 1:60million \"20\": 1:20million \"10\": 1:10million \"03\": 1:3million \"01\": 1:1million spatialtype Type geometry returned: \"RG\", POLYGON \"LB\" POINT.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_units.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get geospatial units data from GISCO API — gisco_get_units","text":"sf object mode = \"sf\" data frame mode = \"df\".","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_units.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get geospatial units data from GISCO API — gisco_get_units","text":"function can return data frame mode = \"df\" sf object mode = \"sf\". order see available unit ids required combination spatialtype, year, first run function \"df\" mode. get data frame can select required ids unit parameter. mode = \"df\" relevant parameters spatialtype, year.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_units.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Get geospatial units data from GISCO API — gisco_get_units","text":"Country-level files renamed cache_dir avoid naming conflicts NUTS-0 datasets. Please check download usage provisions gisco_attributions().","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_units.html","id":"about-caching","dir":"Reference","previous_headings":"","what":"About caching","title":"Get geospatial units data from GISCO API — gisco_get_units","text":"can set cache_dir gisco_set_cache_dir(). Sometimes cached files may corrupt. case, try re-downloading data setting update_cache = TRUE. experience problem download, try download corresponding .geojson file method save cache_dir. Use option verbose = TRUE debugging API query. complete list files available check gisco_db.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_units.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Get geospatial units data from GISCO API — gisco_get_units","text":"dieghernan, https://github.com/dieghernan/","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_units.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get geospatial units data from GISCO API — gisco_get_units","text":"","code":"# \\donttest{ cities <- gisco_get_units( id_giscoR = \"urban_audit\", mode = \"df\", year = \"2020\" ) VAL <- cities[grep(\"Valencia\", cities$URAU_NAME), ] # Order from big to small VAL <- VAL[order(as.double(VAL$AREA_SQM), decreasing = TRUE), ] VAL.sf <- gisco_get_units( id_giscoR = \"urban_audit\", year = \"2020\", unit = VAL$URAU_CODE ) # Provincia Provincia <- gisco_get_units( id_giscoR = \"nuts\", unit = c(\"ES523\"), resolution = \"01\" ) # Reorder VAL.sf$URAU_CATG <- factor(VAL.sf$URAU_CATG, levels = c(\"F\", \"K\", \"C\")) # Plot library(ggplot2) ggplot(Provincia) + geom_sf(fill = \"gray1\") + geom_sf(data = VAL.sf, aes(fill = URAU_CATG)) + scale_fill_viridis_d() + labs( title = \"Valencia\", subtitle = \"Urban Audit\", fill = \"Urban Audit\\ncategory\" ) # }"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_urban_audit.html","id":null,"dir":"Reference","previous_headings":"","what":"Get GISCO greater cities and metropolitan areas sf objects — gisco_get_urban_audit","title":"Get GISCO greater cities and metropolitan areas sf objects — gisco_get_urban_audit","text":"Returns polygons points corresponding cities, greater cities metropolitan areas included Urban Audit report Eurostat.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_urban_audit.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get GISCO greater cities and metropolitan areas sf objects — gisco_get_urban_audit","text":"","code":"gisco_get_urban_audit( year = \"2021\", epsg = \"4326\", cache = TRUE, update_cache = FALSE, cache_dir = NULL, verbose = FALSE, spatialtype = \"RG\", country = NULL, level = NULL )"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_urban_audit.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Get GISCO greater cities and metropolitan areas sf objects — gisco_get_urban_audit","text":"https://gisco-services.ec.europa.eu/distribution/v2/","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_urban_audit.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get GISCO greater cities and metropolitan areas sf objects — gisco_get_urban_audit","text":"year Release year file. One \"2001\", \"2004\", \"2014\", \"2018\", \"2020\" \"2021\". epsg projection map: 4-digit EPSG code. One : \"4258\": ETRS89 \"4326\": WGS84 \"3035\": ETRS89 / ETRS-LAEA \"3857\": Pseudo-Mercator cache logical whether caching. Default TRUE. See caching. update_cache logical whether update cache. Default FALSE. set TRUE force fresh download source .geojson file. cache_dir path cache directory. See caching. verbose Logical, displays information. Useful debugging, default FALSE. spatialtype Type geometry returned: \"LB\": Labels - POINT object. \"RG\": Regions - MULTIPOLYGON/POLYGON object. country Optional. character vector country codes. either vector country names, vector ISO3 country codes vector Eurostat country codes. Mixed types (c(\"Italy\",\"ES\",\"FRA\")) work. See also countrycode::countrycode(). level Level Urban Audit. Possible values \"CITIES\", \"FUA\", \"GREATER_CITIES\" NULL, download full dataset.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_urban_audit.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get GISCO greater cities and metropolitan areas sf objects — gisco_get_urban_audit","text":"sf object specified spatialtype.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_urban_audit.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Get GISCO greater cities and metropolitan areas sf objects — gisco_get_urban_audit","text":"Please check download usage provisions gisco_attributions().","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_urban_audit.html","id":"about-caching","dir":"Reference","previous_headings":"","what":"About caching","title":"Get GISCO greater cities and metropolitan areas sf objects — gisco_get_urban_audit","text":"can set cache_dir gisco_set_cache_dir(). Sometimes cached files may corrupt. case, try re-downloading data setting update_cache = TRUE. experience problem download, try download corresponding .geojson file method save cache_dir. Use option verbose = TRUE debugging API query. complete list files available check gisco_db.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_urban_audit.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get GISCO greater cities and metropolitan areas sf objects — gisco_get_urban_audit","text":"","code":"# \\donttest{ cities <- gisco_get_urban_audit(year = \"2020\", level = \"CITIES\") if (!is.null(cities)) { bcn <- cities[cities$URAU_NAME == \"Barcelona\", ] library(ggplot2) ggplot(bcn) + geom_sf() } # }"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_nuts.html","id":null,"dir":"Reference","previous_headings":"","what":"All NUTS POLYGON object — gisco_nuts","title":"All NUTS POLYGON object — gisco_nuts","text":"sf object including NUTS levels provided GISCO (2016 version).","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_nuts.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"All NUTS POLYGON object — gisco_nuts","text":"POLYGON data frame (resolution: 1:20million, EPSG:4326) object 2,016 rows 11 variables: NUTS_ID NUTS identifier. LEVL_CODE NUTS level code (0,1,2,3). URBN_TYPE Urban Type, see Details. CNTR_CODE Eurostat Country code. NAME_LATN NUTS name Latin characters. NUTS_NAME NUTS name local alphabet. MOUNT_TYPE Mount Type, see Details. COAST_TYPE Coast Type, see Details. FID FID. geo NUTS_ID, provided compatibility eurostat. geometry geometry field.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_nuts.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"All NUTS POLYGON object — gisco_nuts","text":"NUTS_RG_20M_2016_4326.geojson file.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_nuts.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"All NUTS POLYGON object — gisco_nuts","text":"MOUNT_TYPE: Mountain typology: 1: 50 % surface covered topographic mountain areas. 2: 50 % regional population lives topographic mountain areas. 3: 50 % surface covered topographic mountain areas 50 % regional population lives mountain areas. 4: Non-mountain region / regions. 0: classification provided. URBN_TYPE: Urban-rural typology: 1: Predominantly urban region. 2: Intermediate region. 3: Predominantly rural region. 0: classification provided. COAST_TYPE: Coastal typology: 1: Coastal (coast). 2: Coastal (less 50% population living within 50 km. coastline). 3: Non-coastal region. 0: classification provided.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_nuts.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"All NUTS POLYGON object — gisco_nuts","text":"","code":"data(\"gisco_nuts\") head(gisco_nuts) #> Simple feature collection with 6 features and 10 fields #> Geometry type: MULTIPOLYGON #> Dimension: XY #> Bounding box: xmin: -63.08825 ymin: -21.39077 xmax: 55.83808 ymax: 70.08134 #> Geodetic CRS: WGS 84 #> NUTS_ID LEVL_CODE URBN_TYPE CNTR_CODE NAME_LATN #> 1 ES 0 0 ES ESPAÑA #> 2 FI 0 0 FI SUOMI / FINLAND #> 3 IS 0 0 IS ÍSLAND #> 4 PT2 1 0 PT REGIÃO AUTÓNOMA DOS AÇORES #> 5 FR 0 0 FR FRANCE #> 6 HR 0 0 HR HRVATSKA #> NUTS_NAME MOUNT_TYPE COAST_TYPE FID geo #> 1 ESPAÑA 0 0 ES ES #> 2 SUOMI / FINLAND 0 0 FI FI #> 3 ÍSLAND 0 0 IS IS #> 4 REGIÃO AUTÓNOMA DOS AÇORES 0 0 PT2 PT2 #> 5 FRANCE 0 0 FR FR #> 6 HRVATSKA 0 0 HR HR #> geometry #> 1 MULTIPOLYGON (((4.17069 40.... #> 2 MULTIPOLYGON (((28.8195 69.... #> 3 MULTIPOLYGON (((-21.25398 6... #> 4 MULTIPOLYGON (((-25.18988 3... #> 5 MULTIPOLYGON (((55.32105 -2... #> 6 MULTIPOLYGON (((16.37339 46..."},{"path":"https://ropengov.github.io/giscoR/reference/gisco_set_cache_dir.html","id":null,"dir":"Reference","previous_headings":"","what":"Set your giscoR cache dir — gisco_set_cache_dir","title":"Set your giscoR cache dir — gisco_set_cache_dir","text":"function store cache_dir path local machine load future sessions. Type Sys.getenv(\"GISCO_CACHE_DIR\") find cached path use gisco_detect_cache_dir(). Alternatively, can store cache_dir manually following options: Run Sys.setenv(GISCO_CACHE_DIR = \"cache_dir\"). need run command session (Similar install = FALSE). Write line .Renviron file: GISCO_CACHE_DIR = \"value_for_cache_dir\" (behavior install = TRUE). store cache_dir permanently. See also usethis::edit_r_environ().","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_set_cache_dir.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Set your giscoR cache dir — gisco_set_cache_dir","text":"","code":"gisco_set_cache_dir( cache_dir, overwrite = FALSE, install = FALSE, verbose = TRUE ) gisco_detect_cache_dir(...)"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_set_cache_dir.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Set your giscoR cache dir — gisco_set_cache_dir","text":"cache_dir path cache directory. missing value function store cached files temporary dir (See base::tempdir()). overwrite set TRUE, overwrite existing GISCO_CACHE_DIR already local machine. install TRUE, install key local machine use future sessions. Defaults FALSE. cache_dir FALSE parameter set FALSE automatically. verbose Logical, displays information. Useful debugging, default FALSE. ... Ignored","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_set_cache_dir.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Set your giscoR cache dir — gisco_set_cache_dir","text":"gisco_set_cache_dir() returns (invisible) character path cache_dir, mainly called side effect. gisco_detect_cache_dir() returns path cache_dir used session.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_set_cache_dir.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Set your giscoR cache dir — gisco_set_cache_dir","text":"","code":"# Don't run this! It would modify your current state # \\dontrun{ gisco_set_cache_dir(verbose = TRUE) #> Using a temporary cache dir. Set 'cache_dir' to a value for store permanently #> giscoR cache dir is: C:\\Users\\RUNNER~1\\AppData\\Local\\Temp\\RtmpCerdeS/giscoR # } Sys.getenv(\"GISCO_CACHE_DIR\") #> [1] \"C:\\\\Users\\\\RUNNER~1\\\\AppData\\\\Local\\\\Temp\\\\RtmpCerdeS/giscoR\" gisco_detect_cache_dir() #> [1] \"C:\\\\Users\\\\RUNNER~1\\\\AppData\\\\Local\\\\Temp\\\\RtmpCerdeS/giscoR\""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"giscor-060","dir":"Changelog","previous_headings":"","what":"giscoR 0.6.0","title":"giscoR 0.6.0","text":"CRAN release: 2024-08-28","code":""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"update-with-latest-data-available-0-6-0","dir":"Changelog","previous_headings":"","what":"Update with latest data available","title":"giscoR 0.6.0","text":"gisco_get_education() gisco_get_healthcare() gains new year argument: years available now 2020 2023 versions dataset. gisco_get_nuts() gisco_get_countries() now can download 2024 version datasets (#93 @hannesaddec).","code":""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"giscor-051","dir":"Changelog","previous_headings":"","what":"giscoR 0.5.1","title":"giscoR 0.5.1","text":"CRAN release: 2024-07-06 Use CRAN DOI: https://doi.org/10.32614/CRAN.package.giscoR. gisco_get_education(): Fix API entry points. Review failing examples.","code":""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"giscor-050","dir":"Changelog","previous_headings":"","what":"giscoR 0.5.0","title":"giscoR 0.5.0","text":"CRAN release: 2024-05-29 gisco_get_education(). Add access GISCO Address API new functions. See ?gisco_addressapi know (#84). New dependency: jsonlite added ‘Imports’. Update gisco_db --date released data. gisco_get_lau() gisco_get_urban_audit() default year now \"2021\". Update urls documentation.","code":""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"giscor-042","dir":"Changelog","previous_headings":"","what":"giscoR 0.4.2","title":"giscoR 0.4.2","text":"CRAN release: 2024-03-27 Update docs avoid warnings CRAN (#81). Rebuild datasets.","code":""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"giscor-041","dir":"Changelog","previous_headings":"","what":"giscoR 0.4.1","title":"giscoR 0.4.1","text":"CRAN release: 2024-03-15 Improve documentation, stating parameters country region applies (#50, #75). Migrate httr2 instead httr. Removed tgs00026 dataset, use eurostat::get_eurostat(\"tgs00026\") instead.","code":""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"giscor-040","dir":"Changelog","previous_headings":"","what":"giscoR 0.4.0","title":"giscoR 0.4.0","text":"CRAN release: 2023-10-30 gisco_get_nuts(): Add additional geo column (identical NUTS_ID) enhanced compatibility eurostat package (#62). Adjust examples CRAN. Add dependency httr.","code":""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"giscor-035","dir":"Changelog","previous_headings":"","what":"giscoR 0.3.5","title":"giscoR 0.3.5","text":"CRAN release: 2023-06-30 Review examples avoid CRAN errors notes. New helper function: gisco_detect_cache_dir(). Now functions fail gracefully informative message, instead error, return NULL.","code":""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"giscor-034","dir":"Changelog","previous_headings":"","what":"giscoR 0.3.4","title":"giscoR 0.3.4","text":"CRAN release: 2023-05-26 Update tests documentation.","code":""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"giscor-033","dir":"Changelog","previous_headings":"","what":"giscoR 0.3.3","title":"giscoR 0.3.3","text":"CRAN release: 2023-02-16 Fix broken urls gisco_get_healthcare() (#51).","code":""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"giscor-032","dir":"Changelog","previous_headings":"","what":"giscoR 0.3.2","title":"giscoR 0.3.2","text":"CRAN release: 2022-08-13 Fix HTML5 issue requested CRAN.","code":""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"giscor-031","dir":"Changelog","previous_headings":"","what":"giscoR 0.3.1","title":"giscoR 0.3.1","text":"CRAN release: 2021-10-06 Add Copyright DESCRIPTION. Add lwgeom ‘Suggests’. year available 2013. Now information downloaded instead using internal data. New function: gisco_get_postalcodes(). Update gisco_db.","code":""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"giscor-030","dir":"Changelog","previous_headings":"","what":"giscoR 0.3.0","title":"giscoR 0.3.0","text":"CRAN release: 2021-09-27 Now giscoR part rOpenGov. Repo transferred. Caching improvements: new function gisco_set_cache_dir() based rappdirs::user_cache_dir(). Now cache_dir path stored necessary set new session. Also added gisco_clear_cache(). Fix error cache = FALSE. Now files loaded instead throwing error. New tests testthat. Update docs. New examples Refactor documents codes previous gisco_get doc. Add eurostat package ’ Suggests’. lwgeom dependency removed. Update internal grid object. tmap package replaced ggplot2 vignettes examples.","code":""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"giscor-024","dir":"Changelog","previous_headings":"","what":"giscoR 0.2.4","title":"giscoR 0.2.4","text":"CRAN release: 2021-04-13 New eu field giscoR::gisco_countrycode. Fix typos documentation. Include vignette package. Move docs roxygen2. lwgeom moved ‘Imports’ field. cartography package replaced tmap vignettes.","code":""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"giscor-023","dir":"Changelog","previous_headings":"","what":"giscoR 0.2.3","title":"giscoR 0.2.3","text":"Update docs Release DOI","code":""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"giscor-022","dir":"Changelog","previous_headings":"","what":"giscoR 0.2.2","title":"giscoR 0.2.2","text":"CRAN release: 2020-11-23 Remove vignette","code":""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"giscor-021","dir":"Changelog","previous_headings":"","what":"giscoR 0.2.1","title":"giscoR 0.2.1","text":"Remove CRAN notes. Improve docs. Fix CRAN checks.","code":""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"giscor-020","dir":"Changelog","previous_headings":"","what":"giscoR 0.2.0","title":"giscoR 0.2.0","text":"CRAN release: 2020-11-12 Remove colorspace dependency. Bump R minimal version 3.6.0. Change order parameters gisco_get() functions. Rewriting internal functions utils. Add verbose parameter functions. Rewriting giscoR::gisco_db. gisco_bulk_download() gisco_check_access() gisco_get_airports() gisco_get_grid() gisco_get_ports() gisco_get_units() Now gisco_get_countries() gisco_get_nuts() uses gisco_get_units() individual files, making call much faster.","code":""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"giscor-011","dir":"Changelog","previous_headings":"","what":"giscoR 0.1.1","title":"giscoR 0.1.1","text":"CRAN release: 2020-10-28 Added giscoR::tgs00026 dataset. Remove eurostat dependency.","code":""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"giscor-010","dir":"Changelog","previous_headings":"","what":"giscoR 0.1.0","title":"giscoR 0.1.0","text":"CRAN release: 2020-10-13 First stable release.","code":""}] +[{"path":"https://ropengov.github.io/giscoR/articles/giscoR.html","id":"introduction","dir":"Articles","previous_headings":"","what":"Introduction","title":"Get started with giscoR","text":"Full site examples vignettes https://ropengov.github.io/giscoR/ giscoR package designed provide clean interaction GISCO API. Within Eurostat, GISCO responsible meeting European Commission’s geographical information needs 3 levels: European Union, member countries, regions. GISCO also provides variety shapefiles different formats, focusing specially European Union area, providing also worldwide shapefiles, country polygons, labels borders coastal lines. GISCO provides data different resolutions suitable representing small areas (01M, 03M) well lightweight datasets specially useful representing wider areas (10M, 20M, 60M). Shapefiles provided 3 different projections: EPSG 4326, 3035 3857. giscoR returns sf class objects, see https://r-spatial.github.io/sf/.","code":""},{"path":"https://ropengov.github.io/giscoR/articles/giscoR.html","id":"caching","dir":"Articles","previous_headings":"","what":"Caching","title":"Get started with giscoR","text":"giscoR provides dataset caching capability, set : file available locally, downloaded directory next time need corresponding data loaded local directory. experience problems downloading, can also manually download file GISCO API website store local directory.","code":"gisco_set_cache_dir(\"./path/to/location\")"},{"path":"https://ropengov.github.io/giscoR/articles/giscoR.html","id":"downloading-data","dir":"Articles","previous_headings":"","what":"Downloading data","title":"Get started with giscoR","text":"Please aware downloading provisions apply using GISCO data: data downloaded page used printed electronic publication, addition provisions applicable whole Eurostat website, data source acknowledged legend map introductory page publication following copyright notice: EN: © EuroGeographics administrative boundaries FR: © EuroGeographics pour les limites administratives DE: © EuroGeographics bezüglich der Verwaltungsgrenzen publications languages English, French German, translation copyright notice language publication shall used. intend use data commercially, please contact EuroGeographics information regarding licence agreements. function, gisco_attributions() guide topic. also provides attributions several languages.","code":"library(giscoR) gisco_attributions(lang = \"en\") #> [1] \"© EuroGeographics for the administrative boundaries\" gisco_attributions(lang = \"fr\") #> [1] \"© EuroGeographics pour les limites administratives\" gisco_attributions(lang = \"de\") #> [1] \"© EuroGeographics bezuglich der Verwaltungsgrenzen\""},{"path":"https://ropengov.github.io/giscoR/articles/giscoR.html","id":"basic-example","dir":"Articles","previous_headings":"","what":"Basic example","title":"Get started with giscoR","text":"examples data downloads Political map Asia can select specific countries name (language), ISO 3 codes Eurostat codes. restriction can’t mix country names, ISO3 Eurostat codes one single call. possible also combine different shapefiles, just set resolution epsg (optionally year) value: Political map North Africa","code":"library(sf) library(ggplot2) # Use ggplot for plotting asia <- gisco_get_countries(region = \"Asia\") ggplot(asia) + geom_sf(fill = \"cornsilk\", color = \"#887e6a\") + theme( panel.background = element_rect(fill = \"#fffff3\"), panel.border = element_rect(colour = \"#887e6a\", fill = NA, linewidth = 1.5), axis.text = element_text( family = \"serif\", colour = \"#887e6a\", face = \"bold\" ) ) africa_north <- gisco_get_countries( country = c( \"Morocco\", \"Argelia\", \"Libia\", \"Tunisia\", \"Egypt\" ), resolution = \"20\", epsg = \"4326\", year = \"2016\" ) # Coastal lines coast <- gisco_get_coastallines(resolution = \"20\", epsg = \"4326\", year = \"2016\") # Plot ggplot(coast) + geom_sf(color = \"grey80\") + geom_sf(data = africa_north, fill = \"grey30\", color = \"white\") + coord_sf(xlim = c(-13, 37), ylim = c(18.5, 40)) + facet_wrap(vars(NAME_ENGL), ncol = 2)"},{"path":"https://ropengov.github.io/giscoR/articles/giscoR.html","id":"thematic-maps-with-giscor","dir":"Articles","previous_headings":"","what":"Thematic maps with giscoR","title":"Get started with giscoR","text":"example giscoR can play nicely Eurostat data. plotting purposes use ggplot2 package however package handles sf objects (e.g. tmap, mapsf, leaflet, etc. used). Also colorspace rcartocolor packages recommended, provide great color palettes. Disposable income private households NUTS 2 regions (2021)","code":"# EU members library(dplyr) library(eurostat) nuts2 <- gisco_get_nuts( year = \"2021\", epsg = \"3035\", resolution = \"10\", nuts_level = \"2\" ) # Borders from countries borders <- gisco_get_countries(epsg = \"3035\", year = \"2020\", resolution = \"3\") eu_bord <- borders %>% filter(CNTR_ID %in% nuts2$CNTR_CODE) # Eurostat data - Disposable income pps <- get_eurostat(\"tgs00026\") %>% filter(TIME_PERIOD == \"2021-01-01\") nuts2_sf <- nuts2 %>% left_join(pps, by = \"geo\") %>% mutate( values_th = values / 1000, categ = cut(values_th, c(0, 15, 30, 60, 90, 120, Inf)) ) # Adjust the labels labs <- levels(nuts2_sf$categ) labs[1] <- \"< 15\" labs[6] <- \"> 120\" levels(nuts2_sf$categ) <- labs # Finally the plot ggplot(nuts2_sf) + # Background geom_sf(data = borders, fill = \"#e1e1e1\", color = NA) + geom_sf(aes(fill = categ), color = \"grey20\", linewidth = .1) + geom_sf(data = eu_bord, fill = NA, color = \"black\", linewidth = .15) + # Center in Europe: EPSG 3035 coord_sf(xlim = c(2377294, 6500000), ylim = c(1413597, 5228510)) + # Legends and color scale_fill_manual( values = hcl.colors(length(labs), \"Geyser\", rev = TRUE), # Label NA labels = function(x) { ifelse(is.na(x), \"No Data\", x) }, na.value = \"#e1e1e1\" ) + guides(fill = guide_legend(nrow = 1)) + theme_void() + theme( text = element_text(colour = \"grey0\"), panel.background = element_rect(fill = \"#97dbf2\"), panel.border = element_rect(fill = NA, color = \"grey10\"), plot.title = element_text(hjust = 0.5, vjust = -1, size = 12), plot.subtitle = element_text( hjust = 0.5, vjust = -2, face = \"bold\", margin = margin(b = 10, t = 5), size = 12 ), plot.caption = element_text( size = 8, hjust = 0.5, margin = margin(b = 2, t = 13) ), legend.text = element_text(size = 7, ), legend.title = element_text(size = 7), legend.position = \"bottom\", legend.direction = \"horizontal\", legend.text.position = \"bottom\", legend.title.position = \"top\", legend.key.height = rel(0.5), legend.key.width = unit(.1, \"npc\") ) + # Annotate and labels labs( title = \"Disposable income of private households (2021)\", subtitle = \"NUTS-2 level\", fill = \"euros (thousands)\", caption = paste0( \"Source: Eurostat\\n \", gisco_attributions() ) )"},{"path":"https://ropengov.github.io/giscoR/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Diego Hernangómez. Author, maintainer, copyright holder. rOpenGov EuroGeographics. Copyright holder. administrative boundaries. Vincent Arel-Bundock. Copyright holder. gisco_countrycode dataset.","code":""},{"path":"https://ropengov.github.io/giscoR/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Hernangómez D (2024). giscoR: Download Map Data GISCO API - Eurostat. doi:10.32614/CRAN.package.giscoR, https://ropengov.github.io/giscoR/.","code":"@Manual{R-giscoR, title = {{giscoR}: Download Map Data from GISCO API - Eurostat}, doi = {10.32614/CRAN.package.giscoR}, author = {Diego Hernangómez}, year = {2024}, version = {0.6.0}, url = {https://ropengov.github.io/giscoR/}, abstract = {Tools to download data from the GISCO (Geographic Information System of the Commission) Eurostat database . Global and European map data available. This package is in no way officially related to or endorsed by Eurostat.}, }"},{"path":[]},{"path":"https://ropengov.github.io/giscoR/CONTRIBUTING.html","id":"fixing-typos","dir":"","previous_headings":"","what":"Fixing typos","title":"CONTRIBUTING","text":"Small typos grammatical errors documentation may edited directly using GitHub web interface, long changes made source file. YES ✔️: edit roxygen comment .R file R/. ❌: edit .Rd file man/.","code":""},{"path":"https://ropengov.github.io/giscoR/CONTRIBUTING.html","id":"prerequisites","dir":"","previous_headings":"","what":"Prerequisites","title":"CONTRIBUTING","text":"make substantial pull request, always file issue make sure someone team agrees ’s problem. ’ve found bug, create associated issue illustrate bug minimal reprex.","code":""},{"path":"https://ropengov.github.io/giscoR/CONTRIBUTING.html","id":"pull-request-process","dir":"","previous_headings":"","what":"Pull request process","title":"CONTRIBUTING","text":"recommend create Git branch pull request (PR). Look R-CMD-check build status . making changes, run devtools::check() ensure new Notes, Warnings Errors appearing. recommend tidyverse style guide. also use styler package apply styles, please don’t restyle code nothing PR. use roxygen2. use testthat. Contributions test cases included easier accept. user-facing changes, add bullet top NEWS.md current development version header describing changes made followed GitHub username, links relevant issue(s)/PR(s).","code":""},{"path":"https://ropengov.github.io/giscoR/CONTRIBUTING.html","id":"prefer-to-email","dir":"","previous_headings":"","what":"Prefer to Email?","title":"CONTRIBUTING","text":"Email person listed maintainer DESCRIPTION file repo. Though note private discussions email don’t help others - course email totally warranted ’s sensitive problem kind.","code":""},{"path":"https://ropengov.github.io/giscoR/CONTRIBUTING.html","id":"thanks-for-contributing","dir":"","previous_headings":"","what":"Thanks for contributing!","title":"CONTRIBUTING","text":"contributing guide adapted tidyverse contributing guide available https://raw.githubusercontent.com/r-lib/usethis/master/inst/templates/tidy-contributing.md","code":""},{"path":"https://ropengov.github.io/giscoR/index.html","id":"giscor-","dir":"","previous_headings":"","what":"giscoR | R package for download geodata from GISCO - Eurostat","title":"giscoR | R package for download geodata from GISCO - Eurostat","text":"giscoR API package helps retrieve data Eurostat - GISCO (Geographic Information System COmmission). also provides lightweight data sets ready use without downloading. GISCO geospatial open data repository including several data sets countries, coastal lines, labels NUTS levels. data sets usually provided several resolution levels (60M/20M/10M/03M/01M) 3 different projections (4326/3035/3857). Note package provide metadata downloaded files, information available API webpage. Full site examples vignettes https://ropengov.github.io/giscoR/","code":""},{"path":"https://ropengov.github.io/giscoR/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"giscoR | R package for download geodata from GISCO - Eurostat","text":"Install giscoR CRAN: can install developing version giscoR : Alternatively, can install giscoR using r-universe:","code":"install.packages(\"giscoR\") remotes::install_github(\"rOpenGov/giscoR\") install.packages(\"giscoR\", repos = c(\"https://ropengov.r-universe.dev\", \"https://cloud.r-project.org\") )"},{"path":"https://ropengov.github.io/giscoR/index.html","id":"usage","dir":"","previous_headings":"","what":"Usage","title":"giscoR | R package for download geodata from GISCO - Eurostat","text":"script highlights features giscoR :","code":"library(giscoR) library(sf) library(dplyr) # Different resolutions DNK_res60 <- gisco_get_countries(resolution = \"60\", country = \"DNK\") %>% mutate(res = \"60M\") DNK_res20 <- gisco_get_countries(resolution = \"20\", country = \"DNK\") %>% mutate(res = \"20M\") DNK_res10 <- gisco_get_countries(resolution = \"10\", country = \"DNK\") %>% mutate(res = \"10M\") DNK_res03 <- gisco_get_countries(resolution = \"03\", country = \"DNK\") %>% mutate(res = \"03M\") DNK_all <- bind_rows(DNK_res60, DNK_res20, DNK_res10, DNK_res03) # Plot ggplot2 library(ggplot2) ggplot(DNK_all) + geom_sf(fill = \"tomato\") + facet_wrap(vars(res)) + theme_minimal() # Labels and Lines available labs <- gisco_get_countries( spatialtype = \"LB\", region = \"Africa\", epsg = \"3857\" ) coast <- gisco_get_countries( spatialtype = \"COASTL\", epsg = \"3857\" ) # For zooming afr_bbox <- st_bbox(labs) ggplot(coast) + geom_sf(col = \"deepskyblue4\", linewidth = 3) + geom_sf(data = labs, fill = \"springgreen4\", col = \"darkgoldenrod1\", size = 5, shape = 21) + coord_sf( xlim = afr_bbox[c(\"xmin\", \"xmax\")], ylim = afr_bbox[c(\"ymin\", \"ymax\")] )"},{"path":"https://ropengov.github.io/giscoR/index.html","id":"labels","dir":"","previous_headings":"Usage","what":"Labels","title":"giscoR | R package for download geodata from GISCO - Eurostat","text":"example labeled map using ggplot2:","code":"ITA <- gisco_get_nuts(country = \"Italy\", nuts_level = 1) ggplot(ITA) + geom_sf() + geom_sf_text(aes(label = NAME_LATN)) + theme(axis.title = element_blank())"},{"path":"https://ropengov.github.io/giscoR/index.html","id":"thematic-maps","dir":"","previous_headings":"Usage","what":"Thematic maps","title":"giscoR | R package for download geodata from GISCO - Eurostat","text":"example thematic map plotted ggplot2 package. information extracted via eurostat package (Lahti et al. 2017). follow fantastic approach presented Milos Popovic post: start extracting corresponding geographic data: now download data Eurostat: last, merge manipulate data creating final plot:","code":"# Get shapes nuts3 <- gisco_get_nuts( year = \"2021\", epsg = \"3035\", resolution = \"10\", nuts_level = \"3\" ) # Group by NUTS by country and convert to lines country_lines <- nuts3 %>% group_by( CNTR_CODE ) %>% summarise(n = n()) %>% st_cast(\"MULTILINESTRING\") # Use eurostat library(eurostat) popdens <- get_eurostat(\"demo_r_d3dens\") %>% filter(TIME_PERIOD == \"2021-01-01\") # Merge data nuts3_sf <- nuts3 %>% left_join(popdens, by = \"geo\") nuts3_sf <- nuts3 %>% left_join(popdens, by = c(\"NUTS_ID\" = \"geo\")) # Breaks and labels br <- c(0, 25, 50, 100, 200, 500, 1000, 2500, 5000, 10000, 30000) labs <- prettyNum(br[-1], big.mark = \",\") # Label function to be used in the plot, mainly for NAs labeller_plot <- function(x) { ifelse(is.na(x), \"No Data\", x) } nuts3_sf <- nuts3_sf %>% # Cut with labels mutate(values_cut = cut(values, br, labels = labs)) # Palette pal <- hcl.colors(length(labs), \"Lajolla\") # Plot ggplot(nuts3_sf) + geom_sf(aes(fill = values_cut), linewidth = 0, color = NA, alpha = 0.9) + geom_sf(data = country_lines, col = \"black\", linewidth = 0.1) + # Center in Europe: EPSG 3035 coord_sf( xlim = c(2377294, 7453440), ylim = c(1313597, 5628510) ) + # Legends scale_fill_manual( values = pal, # Label for NA labels = labeller_plot, drop = FALSE, guide = guide_legend(direction = \"horizontal\", nrow = 1) ) + # Theming theme_void() + # Theme theme( plot.title = element_text( color = rev(pal)[2], size = rel(1.5), hjust = 0.5, vjust = -6 ), plot.subtitle = element_text( color = rev(pal)[2], size = rel(1.25), hjust = 0.5, vjust = -10, face = \"bold\" ), plot.caption = element_text(color = \"grey60\", hjust = 0.5, vjust = 0), legend.text = element_text(color = \"grey20\", hjust = .5), legend.title = element_text(color = \"grey20\", hjust = .5), legend.position = \"bottom\", legend.title.position = \"top\", legend.text.position = \"bottom\", legend.key.height = unit(.5, \"line\"), legend.key.width = unit(2.5, \"line\") ) + # Annotate and labs labs( title = \"Population density in 2021\", subtitle = \"NUTS-3 level\", fill = \"people per sq. kilometer\", caption = paste0( \"Source: Eurostat, \", gisco_attributions(), \"\\nBased on Milos Popovic: \", \"https://milospopovic.net/how-to-make-choropleth-map-in-r/\" ) )"},{"path":"https://ropengov.github.io/giscoR/index.html","id":"a-note-on-caching","dir":"","previous_headings":"","what":"A note on caching","title":"giscoR | R package for download geodata from GISCO - Eurostat","text":"data sets (Local Administrative Units - LAU, high-resolution files) may size larger 50MB. can use giscoR create local repository given local directory passing following function: can also download manually files (.geojson format) store local directory.","code":"gisco_set_cache_dir(\"./path/to/location\")"},{"path":[]},{"path":"https://ropengov.github.io/giscoR/index.html","id":"api-data-packages","dir":"","previous_headings":"Recommended packages","what":"API data packages","title":"giscoR | R package for download geodata from GISCO - Eurostat","text":"eurostat (Lahti et al. 2017): API package provides access open data Eurostat.","code":""},{"path":"https://ropengov.github.io/giscoR/index.html","id":"plotting-sf-objects","dir":"","previous_headings":"Recommended packages","what":"Plotting sf objects","title":"giscoR | R package for download geodata from GISCO - Eurostat","text":"packages recommended visualization : tmap ggplot2 + ggspatial + tidyterra mapsf leaflet","code":""},{"path":"https://ropengov.github.io/giscoR/index.html","id":"contribute","dir":"","previous_headings":"","what":"Contribute","title":"giscoR | R package for download geodata from GISCO - Eurostat","text":"Check GitHub page source code. Contributions welcome: Use issue tracker feedback bug reports. Send pull requests Star us GitHub page","code":""},{"path":"https://ropengov.github.io/giscoR/index.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"giscoR | R package for download geodata from GISCO - Eurostat","text":"cite ‘giscoR’ publications use: Hernangómez D (2024). giscoR: Download Map Data GISCO API - Eurostat. doi:10.32614/CRAN.package.giscoR https://doi.org/10.32614/CRAN.package.giscoR, https://ropengov.github.io/giscoR/. BibTeX entry LaTeX users ","code":"@Manual{R-giscoR, title = {{giscoR}: Download Map Data from GISCO API - Eurostat}, doi = {10.32614/CRAN.package.giscoR}, author = {Diego Hernangómez}, year = {2024}, version = {0.6.0}, url = {https://ropengov.github.io/giscoR/}, abstract = {Tools to download data from the GISCO (Geographic Information System of the Commission) Eurostat database . Global and European map data available. This package is in no way officially related to or endorsed by Eurostat.}, }"},{"path":"https://ropengov.github.io/giscoR/index.html","id":"copyright-notice","dir":"","previous_headings":"","what":"Copyright notice","title":"giscoR | R package for download geodata from GISCO - Eurostat","text":"data downloaded page used printed electronic publication, addition provisions applicable whole Eurostat website, data source acknowledged legend map introductory page publication following copyright notice: EN: © EuroGeographics administrative boundaries. FR: © EuroGeographics pour les limites administratives. DE: © EuroGeographics bezüglich der Verwaltungsgrenzen. publications languages English, French German, translation copyright notice language publication shall used. intend use data commercially, please contact EuroGeographics information regarding licence agreements. GISCO Web","code":""},{"path":"https://ropengov.github.io/giscoR/index.html","id":"disclaimer","dir":"","previous_headings":"","what":"Disclaimer","title":"giscoR | R package for download geodata from GISCO - Eurostat","text":"package way officially related endorsed Eurostat.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"GNU General Public License","title":"GNU General Public License","text":"Version 3, 29 June 2007Copyright © 2007 Free Software Foundation, Inc.  Everyone permitted copy distribute verbatim copies license document, changing allowed.","code":""},{"path":"https://ropengov.github.io/giscoR/LICENSE.html","id":"preamble","dir":"","previous_headings":"","what":"Preamble","title":"GNU General Public License","text":"GNU General Public License free, copyleft license software kinds works. licenses software practical works designed take away freedom share change works. contrast, GNU General Public License intended guarantee freedom share change versions program–make sure remains free software users. , Free Software Foundation, use GNU General Public License software; applies also work released way authors. can apply programs, . speak free software, referring freedom, price. 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Termination","title":"GNU General Public License","text":"may propagate modify covered work except expressly provided License. attempt otherwise propagate modify void, automatically terminate rights License (including patent licenses granted third paragraph section 11). However, cease violation License, license particular copyright holder reinstated () provisionally, unless copyright holder explicitly finally terminates license, (b) permanently, copyright holder fails notify violation reasonable means prior 60 days cessation. Moreover, license particular copyright holder reinstated permanently copyright holder notifies violation reasonable means, first time received notice violation License (work) copyright holder, cure violation prior 30 days receipt notice. 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Interpretation of Sections 15 and 16","title":"GNU General Public License","text":"disclaimer warranty limitation liability provided given local legal effect according terms, reviewing courts shall apply local law closely approximates absolute waiver civil liability connection Program, unless warranty assumption liability accompanies copy Program return fee. END TERMS CONDITIONS","code":""},{"path":"https://ropengov.github.io/giscoR/LICENSE.html","id":"how-to-apply-these-terms-to-your-new-programs","dir":"","previous_headings":"","what":"How to Apply These Terms to Your New Programs","title":"GNU General Public License","text":"develop new program, want greatest possible use public, best way achieve make free software everyone can redistribute change terms. , attach following notices program. safest attach start source file effectively state exclusion warranty; file least “copyright” line pointer full notice found. Also add information contact electronic paper mail. program terminal interaction, make output short notice like starts interactive mode: hypothetical commands show w show c show appropriate parts General Public License. course, program’s commands might different; GUI interface, use “box”. also get employer (work programmer) school, , sign “copyright disclaimer” program, necessary. information , apply follow GNU GPL, see . GNU General Public License permit incorporating program proprietary programs. program subroutine library, may consider useful permit linking proprietary applications library. want , use GNU Lesser General Public License instead License. first, please read .","code":"giscoR - Download Geospatial Data from GISCO API (Eurostat). Copyright (C) 2020 Diego Hernangómez This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program. If not, see . giscoR Copyright (C) 2020 Diego Hernangómez This program comes with ABSOLUTELY NO WARRANTY; for details type 'show w'. This is free software, and you are welcome to redistribute it under certain conditions; type 'show c' for details."},{"path":"https://ropengov.github.io/giscoR/reference/giscoR-package.html","id":null,"dir":"Reference","previous_headings":"","what":"giscoR: Download Map Data from GISCO API - Eurostat — giscoR-package","title":"giscoR: Download Map Data from GISCO API - Eurostat — giscoR-package","text":"Tools download data GISCO (Geographic Information System Commission) Eurostat database https://ec.europa.eu/eurostat/web/gisco. Global European map data available. package way officially related endorsed Eurostat.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/giscoR-package.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"giscoR: Download Map Data from GISCO API - Eurostat — giscoR-package","text":"Maintainer: Diego Hernangómez diego.hernangomezherrero@gmail.com (ORCID) (rOpenGov) [copyright holder] contributors: EuroGeographics (administrative boundaries.) [copyright holder] Vincent Arel-Bundock (ORCID) (gisco_countrycode dataset.) [copyright holder]","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_addressapi.html","id":null,"dir":"Reference","previous_headings":"","what":"GISCO Address API — gisco_addressapi","title":"GISCO Address API — gisco_addressapi","text":"Access GISCO Address API, allows carry geocoding reverse geocoding using pan-european address database. endpoint available implemented specific function, see Details. API supports fuzzy searching (also referred approximate string matching) parameters endpoint.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_addressapi.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"GISCO Address API — gisco_addressapi","text":"","code":"gisco_addressapi_search( country = NULL, province = NULL, city = NULL, road = NULL, housenumber = NULL, postcode = NULL, verbose = FALSE ) gisco_addressapi_reverse(x, y, country = NULL, verbose = FALSE) gisco_addressapi_bbox( country = NULL, province = NULL, city = NULL, road = NULL, postcode = NULL, verbose = FALSE ) gisco_addressapi_countries(verbose = FALSE) gisco_addressapi_provinces(country = NULL, city = NULL, verbose = FALSE) gisco_addressapi_cities(country = NULL, province = NULL, verbose = FALSE) gisco_addressapi_roads( country = NULL, province = NULL, city = NULL, verbose = FALSE ) gisco_addressapi_housenumbers( country = NULL, province = NULL, city = NULL, road = NULL, postcode = NULL, verbose = FALSE ) gisco_addressapi_postcodes( country = NULL, province = NULL, city = NULL, verbose = FALSE ) gisco_addressapi_copyright(verbose = FALSE)"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_addressapi.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"GISCO Address API — gisco_addressapi","text":"country Country code (country = \"LU\"). province province within country. list provinces within certain country use provinces endpoint (gisco_addressapi_provinces(country = \"LU\")). city city within province. list cities within certain province use cities endpoint (gisco_addressapi_cities(province = \"capellen\")). road road within city. housenumber house number house name within road street. postcode Can used combination previous parameters. verbose Logical, displays information. Useful debugging, default FALSE. x, y x y coordinates (longitude latitude) converted human-readable address.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_addressapi.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"GISCO Address API — gisco_addressapi","text":"data.frame object cases, except gisco_addressapi_search(), gisco_addressapi_reverse() gisco_addressapi_bbox(), return sf object.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_addressapi.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"GISCO Address API — gisco_addressapi","text":"Brief description API endpoints (source GISCO Address API \\> Endpoints: resulting object may present following variables:","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_addressapi.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"GISCO Address API — gisco_addressapi","text":"","code":"# \\donttest{ # Cities in a region gisco_addressapi_cities(country = \"PT\", province = \"LISBOA\") #> L2 #> 1 AJUDA #> 2 ALCABIDECHE #> 3 ALCOENTRE #> 4 ALCÂNTARA #> 5 ALFRAGIDE #> 6 ALGUBER #> 7 ALGUEIRÃO-MEM MARTINS #> 8 ALVALADE #> 9 AREEIRO #> 10 ARRANHÓ #> 11 ARROIOS #> 12 ARRUDA DOS VINHOS #> 13 AVEIRAS DE BAIXO #> 14 AVEIRAS DE CIMA #> 15 AVENIDAS NOVAS #> 16 AZAMBUJA #> 17 BARCARENA #> 18 BEATO #> 19 BELÉM #> 20 BENFICA #> 21 BUCELAS #> 22 CAMPO DE OURIQUE #> 23 CAMPOLIDE #> 24 CARDOSAS #> 25 CARNIDE #> 26 CARNOTA #> 27 CARVOEIRA #> 28 CASAL DE CAMBRA #> 29 COLARES #> 30 ENCARNAÇÃO #> 31 ENCOSTA DO SOL #> 32 ERICEIRA #> 33 ESTRELA #> 34 FALAGUEIRA-VENDA NOVA #> 35 FANHÕES #> 36 FREIRIA #> 37 LOURES #> 38 LOUSA #> 39 LUMIAR #> 40 MAFRA #> 41 MARVILA #> 42 MECA #> 43 MILHARADO #> 44 MINA DE ÁGUA #> 45 MISERICÓRDIA #> 46 MOITA DOS FERREIROS #> 47 ODIVELAS #> 48 OLHALVO #> 49 OLIVAIS #> 50 OTA #> 51 PARQUE DAS NAÇÕES #> 52 PENHA DE FRANÇA #> 53 PERAL #> 54 PONTE DO ROL #> 55 PORTO SALVO #> 56 RAMALHAL #> 57 REGUENGO GRANDE #> 58 RIBAMAR #> 59 RIO DE MOURO #> 60 S. TIAGO DOS VELHOS #> 61 SANTA BÁRBARA #> 62 SANTA CLARA #> 63 SANTA MARIA MAIOR #> 64 SANTA MARIA, SÃO PEDRO E MATACÃES #> 65 SANTO ANTÓNIO #> 66 SANTO ISIDORO #> 67 SANTO QUINTINO #> 68 SAPATARIA #> 69 SILVEIRA #> 70 SOBRAL DE MONTE AGRAÇO #> 71 SÃO DOMINGOS DE BENFICA #> 72 SÃO DOMINGOS DE RANA #> 73 SÃO PEDRO DA CADEIRA #> 74 SÃO VICENTE #> 75 TURCIFAL #> 76 UNIÃO DAS FREGUESIAS DE A DOS CUNHADOS E MACEIRA #> 77 UNIÃO DAS FREGUESIAS DE ABRIGADA E CABANAS DE TORRES #> 78 UNIÃO DAS FREGUESIAS DE AGUALVA E MIRA-SINTRA #> 79 UNIÃO DAS FREGUESIAS DE ALDEIA GALEGA DA MERCEANA E ALDEIA GAVINHA #> 80 UNIÃO DAS FREGUESIAS DE ALENQUER (SANTO ESTÊVÃO E TRIANA) #> 81 UNIÃO DAS FREGUESIAS DE ALGÉS, LINDA-A-VELHA E CRUZ QUEBRADA-DAFUNDO #> 82 UNIÃO DAS FREGUESIAS DE ALHANDRA, SÃO JOÃO DOS MONTES E CALHANDRIZ #> 83 UNIÃO DAS FREGUESIAS DE ALMARGEM DO BISPO, PÊRO PINHEIRO E MONTELAVAR #> 84 UNIÃO DAS FREGUESIAS DE ALVERCA DO RIBATEJO E SOBRALINHO #> 85 UNIÃO DAS FREGUESIAS DE AZUEIRA E SOBRAL DA ABELHEIRA #> 86 UNIÃO DAS FREGUESIAS DE CAMARATE, UNHOS E APELAÇÃO #> 87 UNIÃO DAS FREGUESIAS DE CAMPELOS E OUTEIRO DA CABEÇA #> 88 UNIÃO DAS FREGUESIAS DE CARCAVELOS E PAREDE #> 89 UNIÃO DAS FREGUESIAS DE CARNAXIDE E QUEIJAS #> 90 UNIÃO DAS FREGUESIAS DE CARREGADO E CADAFAIS #> 91 UNIÃO DAS FREGUESIAS DE CARVOEIRA E CARMÕES #> 92 UNIÃO DAS FREGUESIAS DE CASCAIS E ESTORIL #> 93 UNIÃO DAS FREGUESIAS DE CASTANHEIRA DO RIBATEJO E CACHOEIRAS #> 94 UNIÃO DAS FREGUESIAS DE DOIS PORTOS E RUNA #> 95 UNIÃO DAS FREGUESIAS DE ENXARA DO BISPO, GRADIL E VILA FRANCA DO ROSÁRIO #> 96 UNIÃO DAS FREGUESIAS DE IGREJA NOVA E CHELEIROS #> 97 UNIÃO DAS FREGUESIAS DE LAMAS E CERCAL #> 98 UNIÃO DAS FREGUESIAS DE LOURINHÃ E ATALAIA #> 99 UNIÃO DAS FREGUESIAS DE MALVEIRA E SÃO MIGUEL DE ALCAINÇA #> 100 UNIÃO DAS FREGUESIAS DE MANIQUE DO INTENDENTE, VILA NOVA DE SÃO PEDRO E MAÇUSSA #> 101 UNIÃO DAS FREGUESIAS DE MASSAMÁ E MONTE ABRAÃO #> 102 UNIÃO DAS FREGUESIAS DE MAXIAL E MONTE REDONDO #> 103 UNIÃO DAS FREGUESIAS DE MIRAGAIA E MARTELEIRA #> 104 UNIÃO DAS FREGUESIAS DE MOSCAVIDE E PORTELA #> 105 UNIÃO DAS FREGUESIAS DE OEIRAS E SÃO JULIÃO DA BARRA, PAÇO DE ARCOS E CAXIAS #> 106 UNIÃO DAS FREGUESIAS DE PAINHO E FIGUEIROS #> 107 UNIÃO DAS FREGUESIAS DE PONTINHA E FAMÕES #> 108 UNIÃO DAS FREGUESIAS DE PÓVOA DE SANTA IRIA E FORTE DA CASA #> 109 UNIÃO DAS FREGUESIAS DE PÓVOA DE SANTO ADRIÃO E OLIVAL BASTO #> 110 UNIÃO DAS FREGUESIAS DE QUELUZ E BELAS #> 111 UNIÃO DAS FREGUESIAS DE RAMADA E CANEÇAS #> 112 UNIÃO DAS FREGUESIAS DE RIBAFRIA E PEREIRO DE PALHACANA #> 113 UNIÃO DAS FREGUESIAS DE SACAVÉM E PRIOR VELHO #> 114 UNIÃO DAS FREGUESIAS DE SANTA IRIA DE AZOIA, SÃO JOÃO DA TALHA E BOBADELA #> 115 UNIÃO DAS FREGUESIAS DE SANTO ANTÃO E SÃO JULIÃO DO TOJAL #> 116 UNIÃO DAS FREGUESIAS DE SANTO ANTÓNIO DOS CAVALEIROS E FRIELAS #> 117 UNIÃO DAS FREGUESIAS DE SINTRA (SANTA MARIA E SÃO MIGUEL, SÃO MARTINHO E SÃO PEDRO DE PENAFERRIM) #> 118 UNIÃO DAS FREGUESIAS DE SÃO BARTOLOMEU DOS GALEGOS E MOLEDO #> 119 UNIÃO DAS FREGUESIAS DE SÃO JOÃO DAS LAMPAS E TERRUGEM #> 120 UNIÃO DAS FREGUESIAS DE VENDA DO PINHEIRO E SANTO ESTÊVÃO DAS GALÉS #> 121 UNIÃO DAS FREGUESIAS DO CACÉM E SÃO MARCOS #> 122 UNIÃO DAS FREGUESIAS DO CADAVAL E PÊRO MONIZ #> 123 VALE DO PARAÍSO #> 124 VENTEIRA #> 125 VENTOSA #> 126 VERMELHA #> 127 VIALONGA #> 128 VILA FRANCA DE XIRA #> 129 VILA NOVA DA RAINHA #> 130 VILA VERDE DOS FRANCOS #> 131 VILAR #> 132 VIMEIRO #> 133 ÁGUAS LIVRES # Geocode and reverse geocode with sf objects # Structured search struct <- gisco_addressapi_search( country = \"ES\", city = \"BARCELONA\", road = \"GRACIA\" ) struct #> Simple feature collection with 356 features and 13 fields #> Geometry type: POINT #> Dimension: XY #> Bounding box: xmin: 2.149583 ymin: 41.38821 xmax: 2.170311 ymax: 41.41935 #> Geodetic CRS: WGS 84 #> First 10 features: #> LD TF L2 L1 L0 PC N0 N1 N2 N3 #> 1 91 PS GRACIA BARCELONA CATALUÑA/CATALUNYA ES 8008 ES ES5 ES51 ES511 #> 2 93 PS GRACIA BARCELONA CATALUÑA/CATALUNYA ES 8008 ES ES5 ES51 ES511 #> 3 103 PS GRACIA BARCELONA CATALUÑA/CATALUNYA ES 8008 ES ES5 ES51 ES511 #> 4 101 PS GRACIA BARCELONA CATALUÑA/CATALUNYA ES 8008 ES ES5 ES51 ES511 #> 5 105 PS GRACIA BARCELONA CATALUÑA/CATALUNYA ES 8008 ES ES5 ES51 ES511 #> 6 107 PS GRACIA BARCELONA CATALUÑA/CATALUNYA ES 8008 ES ES5 ES51 ES511 #> 7 99 PS GRACIA BARCELONA CATALUÑA/CATALUNYA ES 8008 ES ES5 ES51 ES511 #> 8 97 PS GRACIA BARCELONA CATALUÑA/CATALUNYA ES 8008 ES ES5 ES51 ES511 #> 9 96 PS GRACIA BARCELONA CATALUÑA/CATALUNYA ES 8008 ES ES5 ES51 ES511 #> 10 94 PS GRACIA BARCELONA CATALUÑA/CATALUNYA ES 8008 ES ES5 ES51 ES511 #> OL X Y geometry #> 1 8FH495V6+WCV 2.161046 41.39487 POINT (2.161046 41.39487) #> 2 8FH495V6+X9R 2.160902 41.39499 POINT (2.160902 41.39499) #> 3 8FH495W5+7XW 2.159969 41.39574 POINT (2.159969 41.39574) #> 4 8FH495W6+727 2.160050 41.39567 POINT (2.16005 41.39567) #> 5 8FH495W5+9W3 2.159792 41.39588 POINT (2.159792 41.39588) #> 6 8FH495W5+CRJ 2.159529 41.39610 POINT (2.159529 41.3961) #> 7 8FH495W6+45H 2.160484 41.39532 POINT (2.160484 41.39532) #> 8 8FH495W6+36W 2.160582 41.39524 POINT (2.160582 41.39524) #> 9 8FH495W6+5GP 2.161332 41.39545 POINT (2.161332 41.39545) #> 10 8FH495W6+4HW 2.161452 41.39535 POINT (2.161452 41.39535) # Reverse geocoding reverse <- gisco_addressapi_reverse(x = struct$X[1], y = struct$Y[1]) reverse #> Simple feature collection with 5 features and 13 fields #> Geometry type: POINT #> Dimension: XY #> Bounding box: xmin: 2.160902 ymin: 41.39446 xmax: 2.161126 ymax: 41.39499 #> Geodetic CRS: WGS 84 #> LD TF L2 L1 L0 PC N0 N1 N2 N3 #> 1 91 PS GRACIA BARCELONA CATALUÑA/CATALUNYA ES 8008 ES ES5 ES51 ES511 #> 2 89 PS GRACIA BARCELONA CATALUÑA/CATALUNYA ES 8008 ES ES5 ES51 ES511 #> 3 93 PS GRACIA BARCELONA CATALUÑA/CATALUNYA ES 8008 ES ES5 ES51 ES511 #> 4 257 CL PROVENÇA BARCELONA CATALUÑA/CATALUNYA ES 8008 ES ES5 ES51 ES511 #> 5 255 CL PROVENÇA BARCELONA CATALUÑA/CATALUNYA ES 8008 ES ES5 ES51 ES511 #> OL X Y geometry #> 1 8FH495V6+WCV 2.161046 41.39487 POINT (2.161046 41.39487) #> 2 8FH495V6+WFC 2.161126 41.39480 POINT (2.161126 41.3948) #> 3 8FH495V6+X9R 2.160902 41.39499 POINT (2.160902 41.39499) #> 4 8FH495V6+RC2 2.161020 41.39451 POINT (2.16102 41.39451) #> 5 8FH495V6+Q9P 2.160950 41.39446 POINT (2.16095 41.39446) # }"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_attributions.html","id":null,"dir":"Reference","previous_headings":"","what":"Attribution when publishing GISCO data — gisco_attributions","title":"Attribution when publishing GISCO data — gisco_attributions","text":"Get legal text used along data downloaded package.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_attributions.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Attribution when publishing GISCO data — gisco_attributions","text":"","code":"gisco_attributions(lang = \"en\", copyright = FALSE)"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_attributions.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Attribution when publishing GISCO data — gisco_attributions","text":"lang Language (two-letter ISO code). See https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes Details. copyright Boolean TRUE/FALSE. Whether display copyright notice console.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_attributions.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Attribution when publishing GISCO data — gisco_attributions","text":"string attribution used.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_attributions.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Attribution when publishing GISCO data — gisco_attributions","text":"Current languages supported : \"en\": English. \"da\": Danish. \"de\": German. \"es\": Spanish. \"fi\": Finish. \"fr\": French. \"\": Norwegian. \"sv\": Swedish. Please consider contributing spot mistake want add new language.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_attributions.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Attribution when publishing GISCO data — gisco_attributions","text":"COPYRIGHT NOTICE data downloaded GISCO used printed electronic publication, addition provisions applicable whole Eurostat website, data source acknowledged legend map introductory page publication following copyright notice: EN: (C) EuroGeographics administrative boundaries. FR: (C) EuroGeographics pour les limites administratives. DE: (C) EuroGeographics bezuglich der Verwaltungsgrenzen. publications languages English, French German, translation copyright notice language publication shall used. intend use data commercially, please contact EuroGeographics information regarding licence agreements.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_attributions.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Attribution when publishing GISCO data — gisco_attributions","text":"","code":"gisco_attributions() #> [1] \"© EuroGeographics for the administrative boundaries\" gisco_attributions(lang = \"es\", copyright = TRUE) #> #> COPYRIGHT NOTICE #> #> When data downloaded from GISCO #> is used in any printed or electronic publication, #> in addition to any other provisions applicable to #> the whole Eurostat website, data source will have #> to be acknowledged in the legend of the map and in #> the introductory page of the publication with the #> following copyright notice: #> #> - EN: (C) EuroGeographics for the administrative boundaries #> - FR: (C) EuroGeographics pour les limites administratives #> - DE: (C) EuroGeographics bezuglich der Verwaltungsgrenzen #> #> For publications in languages other than English, #> French or German, the translation of the copyright #> notice in the language of the publication shall be #> used. #> #> If you intend to use the data commercially, please #> contact EuroGeographics for information regarding #> their licence agreements. #> #> #> [1] \"© Eurogeographics para los límites administrativos\" gisco_attributions(lang = \"XXX\") #> Language xxx not supported, switching to English. #> Consider contributing: #> https://github.com/rOpenGov/giscoR/issues #> [1] \"© EuroGeographics for the administrative boundaries\""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_bulk_download.html","id":null,"dir":"Reference","previous_headings":"","what":"Bulk download from GISCO API — gisco_bulk_download","title":"Bulk download from GISCO API — gisco_bulk_download","text":"Downloads zipped data GISCO extract cache_dir folder.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_bulk_download.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Bulk download from GISCO API — gisco_bulk_download","text":"","code":"gisco_bulk_download( id_giscoR = c(\"countries\", \"coastallines\", \"communes\", \"lau\", \"nuts\", \"urban_audit\"), year = \"2016\", cache_dir = NULL, update_cache = FALSE, verbose = FALSE, resolution = \"10\", ext = c(\"geojson\", \"shp\", \"svg\", \"json\", \"gdb\"), recursive = TRUE )"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_bulk_download.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Bulk download from GISCO API — gisco_bulk_download","text":"https://gisco-services.ec.europa.eu/distribution/v2/","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_bulk_download.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Bulk download from GISCO API — gisco_bulk_download","text":"id_giscoR Type dataset downloaded. Values supported : \"coastallines\". \"communes\". \"countries\". \"lau\". \"nuts\". \"urban_audit\". year Release year file. See Details. cache_dir path cache directory. See caching. update_cache logical whether update cache. Default FALSE. set TRUE force fresh download source .geojson file. verbose Logical, displays information. Useful debugging, default FALSE. resolution Resolution geospatial data. One \"60\": 1:60million \"20\": 1:20million \"10\": 1:10million \"03\": 1:3million \"01\": 1:1million ext Extension file(s) downloaded. Formats available \"geojson\", \"shp\", \"svg\", \"json\", \"gdb\". See Details. recursive Tries unzip recursively zip files () included initial bulk download (case ext = \"shp\").","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_bulk_download.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Bulk download from GISCO API — gisco_bulk_download","text":"Silent function.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_bulk_download.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Bulk download from GISCO API — gisco_bulk_download","text":"See years available corresponding functions: gisco_get_coastallines(). gisco_get_communes(). gisco_get_countries(). gisco_get_lau(). gisco_get_nuts(). gisco_get_urban_audit(). usual extension used across giscoR \"geojson\", however formats already available GISCO.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_bulk_download.html","id":"about-caching","dir":"Reference","previous_headings":"","what":"About caching","title":"Bulk download from GISCO API — gisco_bulk_download","text":"can set cache_dir gisco_set_cache_dir(). Sometimes cached files may corrupt. case, try re-downloading data setting update_cache = TRUE. experience problem download, try download corresponding .geojson file method save cache_dir. Use option verbose = TRUE debugging API query. complete list files available check gisco_db.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_bulk_download.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Bulk download from GISCO API — gisco_bulk_download","text":"","code":"# \\dontrun{ # Countries 2016 - It would take some time gisco_bulk_download(id_giscoR = \"countries\", resolution = \"60\") # }"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_check_access.html","id":null,"dir":"Reference","previous_headings":"","what":"Check access to GISCO API — gisco_check_access","title":"Check access to GISCO API — gisco_check_access","text":"Check R access resources https://gisco-services.ec.europa.eu/distribution/v2/.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_check_access.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check access to GISCO API — gisco_check_access","text":"","code":"gisco_check_access()"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_check_access.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check access to GISCO API — gisco_check_access","text":"logical.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_check_access.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Check access to GISCO API — gisco_check_access","text":"","code":"gisco_check_access() #> [1] TRUE"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_clear_cache.html","id":null,"dir":"Reference","previous_headings":"","what":"Clear your giscoR cache dir — gisco_clear_cache","title":"Clear your giscoR cache dir — gisco_clear_cache","text":"Use function caution. function clear cached data configuration, specifically: Deletes giscoR config directory (rappdirs::user_config_dir(\"giscoR\", \"R\")). Deletes cache_dir directory. Deletes values stored Sys.getenv(\"GISCO_CACHE_DIR\") options(gisco_cache_dir).","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_clear_cache.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Clear your giscoR cache dir — gisco_clear_cache","text":"","code":"gisco_clear_cache(config = FALSE, cached_data = TRUE, verbose = FALSE)"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_clear_cache.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Clear your giscoR cache dir — gisco_clear_cache","text":"config TRUE, delete configuration folder giscoR. cached_data set TRUE, delete cache_dir content. verbose Logical, displays information. Useful debugging, default FALSE.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_clear_cache.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Clear your giscoR cache dir — gisco_clear_cache","text":"Invisible. function called side effects.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_clear_cache.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Clear your giscoR cache dir — gisco_clear_cache","text":"overkill function intended reset status never installed /used giscoR.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_clear_cache.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Clear your giscoR cache dir — gisco_clear_cache","text":"","code":"# Don't run this! It would modify your current state # \\dontrun{ gisco_clear_cache(verbose = TRUE) #> giscoR cached data deleted: C:\\Users\\RUNNER~1\\AppData\\Local\\Temp\\RtmpS07t9H/giscoR Sys.getenv(\"GISCO_CACHE_DIR\") #> [1] \"\" # Set new cache on a temp dir newcache <- file.path(tempdir(), \"giscoR\", \"pkgdown\") newcache #> [1] \"C:\\\\Users\\\\RUNNER~1\\\\AppData\\\\Local\\\\Temp\\\\RtmpS07t9H/giscoR/pkgdown\" gisco_set_cache_dir(newcache) #> giscoR cache dir is: C:\\Users\\RUNNER~1\\AppData\\Local\\Temp\\RtmpS07t9H/giscoR/pkgdown #> To install your cache_dir path for use in future sessions, #> run this function with `install = TRUE`. Sys.getenv(\"GISCO_CACHE_DIR\") #> [1] \"C:\\\\Users\\\\RUNNER~1\\\\AppData\\\\Local\\\\Temp\\\\RtmpS07t9H/giscoR/pkgdown\" # }"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_coastallines.html","id":null,"dir":"Reference","previous_headings":"","what":"World coastal lines POLYGON object — gisco_coastallines","title":"World coastal lines POLYGON object — gisco_coastallines","text":"sf object provided GISCO (2016 version).","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_coastallines.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"World coastal lines POLYGON object — gisco_coastallines","text":"POLYGON sf object (resolution: 1:20million, EPSG:4326) 3 variables: COAS_ID Coast ID. FID FID. geometry geometry field.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_coastallines.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"World coastal lines POLYGON object — gisco_coastallines","text":"COAS_RG_20M_2016_4326.geojson file.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_coastallines.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"World coastal lines POLYGON object — gisco_coastallines","text":"","code":"data(\"gisco_coastallines\") head(gisco_coastallines) #> Simple feature collection with 6 features and 2 fields #> Geometry type: POLYGON #> Dimension: XY #> Bounding box: xmin: -180 ymin: -89 xmax: 179.9948 ymax: 83.65187 #> Geodetic CRS: WGS 84 #> COAS_ID FID geometry #> 1 1 1 POLYGON ((113.6472 22.70988... #> 2 2 2 POLYGON ((-58.83353 -63.552... #> 3 3 3 POLYGON ((-94.64807 74.0768... #> 4 4 4 POLYGON ((143.5061 -12.9617... #> 5 6 6 POLYGON ((-76.4565 83.10617... #> 6 5 5 POLYGON ((-34.8436 83.57385..."},{"path":"https://ropengov.github.io/giscoR/reference/gisco_countries.html","id":null,"dir":"Reference","previous_headings":"","what":"World countries POLYGON sf object — gisco_countries","title":"World countries POLYGON sf object — gisco_countries","text":"sf object including countries provided GISCO (2016 version).","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_countries.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"World countries POLYGON sf object — gisco_countries","text":"MULTIPOLYGON data frame (resolution: 1:20million, EPSG:4326) object 257 rows 7 variables: id row ID. CNTR_NAME Official country name local language. ISO3_CODE ISO 3166-1 alpha-3 code country, provided GISCO. CNTR_ID Country ID. NAME_ENGL Country name English. FID FID. geometry geometry field.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_countries.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"World countries POLYGON sf object — gisco_countries","text":"CNTR_RG_20M_2016_4326.geojson file.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_countries.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"World countries POLYGON sf object — gisco_countries","text":"","code":"data(\"gisco_countries\") head(gisco_countries) #> Simple feature collection with 6 features and 5 fields #> Geometry type: MULTIPOLYGON #> Dimension: XY #> Bounding box: xmin: -63.09693 ymin: 17.00297 xmax: 74.88986 ymax: 42.63545 #> Geodetic CRS: WGS 84 #> CNTR_ID CNTR_NAME ISO3_CODE NAME_ENGL FID #> 1 AE الإمارات العربية المتحدة ARE United Arab Emirates AE #> 2 AF افغانستان-افغانستان AFG Afghanistan AF #> 3 AG Antigua and Barbuda ATG Antigua and Barbuda AG #> 4 AI Anguilla AIA Anguilla AI #> 5 AL Shqipëria ALB Albania AL #> 6 AM Հայաստան ARM Armenia AM #> geometry #> 1 MULTIPOLYGON (((56.35462 25... #> 2 MULTIPOLYGON (((74.7055 37.... #> 3 MULTIPOLYGON (((-61.80237 1... #> 4 MULTIPOLYGON (((-63.05444 1... #> 5 MULTIPOLYGON (((19.831 42.4... #> 6 MULTIPOLYGON (((46.45984 39..."},{"path":"https://ropengov.github.io/giscoR/reference/gisco_countrycode.html","id":null,"dir":"Reference","previous_headings":"","what":"Data frame with different country code schemes and world regions — gisco_countrycode","title":"Data frame with different country code schemes and world regions — gisco_countrycode","text":"data frame containing conversions different country code schemes (Eurostat/ISO2 3) well geographic regions provided World Bank UN (M49). data set extracted countrycode package.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_countrycode.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Data frame with different country code schemes and world regions — gisco_countrycode","text":"data frame object 249 rows 13 variables: ISO3_CODE Eurostat code country. CNTR_CODE ISO 3166-1 alpha-2 code country. iso2c ISO 3166-1 alpha-3 code country. iso.name.en ISO English short name. cldr.short.en English short name provided Unicode Common Locale Data Repository. continent provided World Bank. un.region.code Numeric region code UN (M49). un.region.name Region name UN (M49). un.regionintermediate.code Numeric intermediate Region. un.regionintermediate.name Intermediate Region name UN (M49). un.regionsub.code Numeric sub-region code UN (M49). un.regionsub.name Sub-Region name UN (M49). eu Logical indicating country belongs European Union.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_countrycode.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Data frame with different country code schemes and world regions — gisco_countrycode","text":"countrycode::codelist v1.2.0.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_countrycode.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Data frame with different country code schemes and world regions — gisco_countrycode","text":"","code":"data(\"gisco_countrycode\") dplyr::glimpse(gisco_countrycode) #> Rows: 249 #> Columns: 13 #> $ ISO3_CODE \"ABW\", \"AFG\", \"AGO\", \"AIA\", \"ALA\", \"ALB\", \"… #> $ CNTR_CODE \"AW\", \"AF\", \"AO\", \"AI\", NA, \"AL\", \"AD\", \"AE… #> $ iso2c \"AW\", \"AF\", \"AO\", \"AI\", \"AX\", \"AL\", \"AD\", \"… #> $ iso.name.en \"Aruba\", \"Afghanistan\", \"Angola\", \"Anguilla… #> $ cldr.short.en \"Aruba\", \"Afghanistan\", \"Angola\", \"Anguilla… #> $ continent \"Americas\", \"Asia\", \"Africa\", \"Americas\", \"… #> $ un.region.code 19, 142, 2, 19, 150, 150, 150, 142, 19, 142… #> $ un.region.name \"Americas\", \"Asia\", \"Africa\", \"Americas\", \"… #> $ un.regionintermediate.code 29, NA, 17, 29, NA, NA, NA, NA, 5, NA, NA, … #> $ un.regionintermediate.name \"Caribbean\", NA, \"Middle Africa\", \"Caribbea… #> $ un.regionsub.code 419, 34, 202, 419, 154, 39, 39, 145, 419, 1… #> $ un.regionsub.name \"Latin America and the Caribbean\", \"Souther… #> $ eu FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, F…"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_db.html","id":null,"dir":"Reference","previous_headings":"","what":"GISCO database — gisco_db","title":"GISCO database — gisco_db","text":"Database list files package can load.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_db.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"GISCO database — gisco_db","text":"data frame","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_db.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"GISCO database — gisco_db","text":"GISCO API datasets.json.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_db.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"GISCO database — gisco_db","text":"data frame used check validity API calls.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_db.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"GISCO database — gisco_db","text":"","code":"data(gisco_db)"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get.html","id":null,"dir":"Reference","previous_headings":"","what":"Get GISCO world country sf polygons, points and lines — gisco_get_countries","title":"Get GISCO world country sf polygons, points and lines — gisco_get_countries","text":"Returns world country polygons, lines points specified scale, provided GISCO. Also, specific areas Gibraltar Antarctica presented separately. definition country used GISCO correspond roughly territories official ISO-3166 code.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get GISCO world country sf polygons, points and lines — gisco_get_countries","text":"","code":"gisco_get_countries( year = \"2016\", epsg = \"4326\", cache = TRUE, update_cache = FALSE, cache_dir = NULL, verbose = FALSE, resolution = \"20\", spatialtype = \"RG\", country = NULL, region = NULL )"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Get GISCO world country sf polygons, points and lines — gisco_get_countries","text":"https://gisco-services.ec.europa.eu/distribution/v2/","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get GISCO world country sf polygons, points and lines — gisco_get_countries","text":"year Release year file. One \"2001\", \"2006\", \"2010\", \"2013\", \"2016\", \"2020\" \"2024\". epsg projection map: 4-digit EPSG code. One : \"4258\": ETRS89 \"4326\": WGS84 \"3035\": ETRS89 / ETRS-LAEA \"3857\": Pseudo-Mercator cache logical whether caching. Default TRUE. See caching. update_cache logical whether update cache. Default FALSE. set TRUE force fresh download source .geojson file. cache_dir path cache directory. See caching. verbose Logical, displays information. Useful debugging, default FALSE. resolution Resolution geospatial data. One \"60\": 1:60million \"20\": 1:20million \"10\": 1:10million \"03\": 1:3million \"01\": 1:1million spatialtype Type geometry returned: \"BN\": Boundaries - LINESTRING object. \"COASTL\": coastlines - LINESTRING object. \"INLAND\": inland boundaries - LINESTRING object. \"LB\": Labels - POINT object. \"RG\": Regions - MULTIPOLYGON/POLYGON object. Note parameters country region applied spatialtype \"BN\" \"RG\". country Optional. character vector country codes. either vector country names, vector ISO3 country codes vector Eurostat country codes. Mixed types (c(\"Italy\",\"ES\",\"FRA\")) work. See also countrycode::countrycode(). region Optional. character vector UN M49 region codes European Union membership. Possible values \"Africa\", \"Americas\", \"Asia\", \"Europe\", \"Oceania\" \"EU\" countries belonging European Union (per 2021). See world regions gisco_countrycode.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get GISCO world country sf polygons, points and lines — gisco_get_countries","text":"sf object specified spatialtype.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Get GISCO world country sf polygons, points and lines — gisco_get_countries","text":"Please check download usage provisions gisco_attributions().","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get.html","id":"about-caching","dir":"Reference","previous_headings":"","what":"About caching","title":"Get GISCO world country sf polygons, points and lines — gisco_get_countries","text":"can set cache_dir gisco_set_cache_dir(). Sometimes cached files may corrupt. case, try re-downloading data setting update_cache = TRUE. experience problem download, try download corresponding .geojson file method save cache_dir. Use option verbose = TRUE debugging API query. complete list files available check gisco_db.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get.html","id":"world-regions","dir":"Reference","previous_headings":"","what":"World Regions","title":"Get GISCO world country sf polygons, points and lines — gisco_get_countries","text":"Regions defined per geographic regions defined UN (see https://unstats.un.org/unsd/methodology/m49/. scheme Cyprus assigned Asia. may use region = \"EU\" get EU members (reference date: 2021).","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get GISCO world country sf polygons, points and lines — gisco_get_countries","text":"","code":"cntries <- gisco_get_countries() library(ggplot2) ggplot(cntries) + geom_sf() # Get a region africa <- gisco_get_countries(region = \"Africa\") ggplot(africa) + geom_sf(fill = \"#078930\", col = \"white\") + theme_minimal()"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_airports.html","id":null,"dir":"Reference","previous_headings":"","what":"Get location of airports and ports from GISCO API — gisco_get_airports","title":"Get location of airports and ports from GISCO API — gisco_get_airports","text":"Loads sf object GISCO API local library.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_airports.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get location of airports and ports from GISCO API — gisco_get_airports","text":"","code":"gisco_get_airports( year = \"2013\", country = NULL, cache_dir = NULL, update_cache = FALSE, verbose = FALSE ) gisco_get_ports( year = \"2013\", country = NULL, cache_dir = NULL, update_cache = FALSE, verbose = FALSE )"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_airports.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Get location of airports and ports from GISCO API — gisco_get_airports","text":"https://ec.europa.eu/eurostat/web/gisco/geodata/transport-networks","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_airports.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get location of airports and ports from GISCO API — gisco_get_airports","text":"year Year reference. year available right now \"2013\". country Optional. character vector country codes. either vector country names, vector ISO3 country codes vector Eurostat country codes. Mixed types (c(\"Italy\",\"ES\",\"FRA\")) work. See also countrycode::countrycode(). cache_dir path cache directory. See caching. update_cache logical whether update cache. Default FALSE. set TRUE force fresh download source .geojson file. verbose Logical, displays information. Useful debugging, default FALSE.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_airports.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get location of airports and ports from GISCO API — gisco_get_airports","text":"POINT object EPSG:4326.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_airports.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get location of airports and ports from GISCO API — gisco_get_airports","text":"gisco_get_airports() refer Europe. shapefiles provided EPSG:4326. gisco_get_ports() adds new field CNTR_ISO2 original data identifying country port. Worldwide information available. port codes aligned UN/LOCODE standard.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_airports.html","id":"about-caching","dir":"Reference","previous_headings":"","what":"About caching","title":"Get location of airports and ports from GISCO API — gisco_get_airports","text":"can set cache_dir gisco_set_cache_dir(). Sometimes cached files may corrupt. case, try re-downloading data setting update_cache = TRUE. experience problem download, try download corresponding .geojson file method save cache_dir. Use option verbose = TRUE debugging API query. complete list files available check gisco_db.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_airports.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get location of airports and ports from GISCO API — gisco_get_airports","text":"","code":"# \\donttest{ library(sf) #> Linking to GEOS 3.12.1, GDAL 3.8.4, PROJ 9.3.1; sf_use_s2() is TRUE greece <- gisco_get_countries(country = \"EL\", resolution = 3) airp_gc <- gisco_get_airports(country = \"EL\") library(ggplot2) if (inherits(airp_gc, \"sf\")) { ggplot(greece) + geom_sf(fill = \"grey80\") + geom_sf(data = airp_gc, color = \"blue\") + labs( title = \"Airports on Greece\", shape = NULL, color = NULL, caption = gisco_attributions() ) } ############################## # Plot ports # ############################## ports <- gisco_get_ports() coast <- giscoR::gisco_coastallines # To Robinson projection :) library(sf) coast <- st_transform(coast, \"ESRI:54030\") ports <- st_transform(ports, st_crs(coast)) if (inherits(ports, \"sf\")) { ggplot(coast) + geom_sf(fill = \"#F6E1B9\", color = \"#0978AB\") + geom_sf(data = ports, fill = \"red\", shape = 21) + theme_void() + theme( panel.background = element_rect(fill = \"#C6ECFF\"), panel.grid = element_blank(), plot.title = element_text(face = \"bold\", hjust = 0.5), plot.subtitle = element_text(face = \"italic\", hjust = 0.5) ) + labs( title = \"Ports Worldwide\", subtitle = \"Year 2013\", caption = \"(c) European Union, 1995 - today\" ) } # }"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_coastallines.html","id":null,"dir":"Reference","previous_headings":"","what":"Get GISCO coastlines sf polygons — gisco_get_coastallines","title":"Get GISCO coastlines sf polygons — gisco_get_coastallines","text":"Downloads worldwide coastlines","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_coastallines.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get GISCO coastlines sf polygons — gisco_get_coastallines","text":"","code":"gisco_get_coastallines( year = \"2016\", epsg = \"4326\", cache = TRUE, update_cache = FALSE, cache_dir = NULL, verbose = FALSE, resolution = \"20\" )"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_coastallines.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Get GISCO coastlines sf polygons — gisco_get_coastallines","text":"https://gisco-services.ec.europa.eu/distribution/v2/","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_coastallines.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get GISCO coastlines sf polygons — gisco_get_coastallines","text":"year Release year. One \"2006\", \"2010\", \"2013\" \"2016\". epsg projection map: 4-digit EPSG code. One : \"4258\": ETRS89 \"4326\": WGS84 \"3035\": ETRS89 / ETRS-LAEA \"3857\": Pseudo-Mercator cache logical whether caching. Default TRUE. See caching. update_cache logical whether update cache. Default FALSE. set TRUE force fresh download source .geojson file. cache_dir path cache directory. See caching. verbose Logical, displays information. Useful debugging, default FALSE. resolution Resolution geospatial data. One \"60\": 1:60million \"20\": 1:20million \"10\": 1:10million \"03\": 1:3million \"01\": 1:1million","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_coastallines.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get GISCO coastlines sf polygons — gisco_get_coastallines","text":"sf POLYGON object.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_coastallines.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Get GISCO coastlines sf polygons — gisco_get_coastallines","text":"Please check download usage provisions gisco_attributions().","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_coastallines.html","id":"about-caching","dir":"Reference","previous_headings":"","what":"About caching","title":"Get GISCO coastlines sf polygons — gisco_get_coastallines","text":"can set cache_dir gisco_set_cache_dir(). Sometimes cached files may corrupt. case, try re-downloading data setting update_cache = TRUE. experience problem download, try download corresponding .geojson file method save cache_dir. Use option verbose = TRUE debugging API query. complete list files available check gisco_db.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_coastallines.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get GISCO coastlines sf polygons — gisco_get_coastallines","text":"","code":"coast <- gisco_get_coastallines() library(ggplot2) ggplot(coast) + geom_sf(color = \"#1278AB\", fill = \"#FDFBEA\") + # Zoom on Caribe coord_sf( xlim = c(-99, -49), ylim = c(4, 30) ) + theme_minimal() + theme( panel.background = element_rect(fill = \"#C7E7FB\", color = NA), panel.border = element_rect(colour = \"black\", fill = NA) )"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_education.html","id":null,"dir":"Reference","previous_headings":"","what":"Get locations of education services in Europe — gisco_get_education","title":"Get locations of education services in Europe — gisco_get_education","text":"dataset contains information main education services Member States.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_education.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get locations of education services in Europe — gisco_get_education","text":"","code":"gisco_get_education( year = c(\"2023\", \"2020\"), cache = TRUE, update_cache = FALSE, cache_dir = NULL, verbose = FALSE, country = NULL )"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_education.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Get locations of education services in Europe — gisco_get_education","text":"https://ec.europa.eu/eurostat/web/gisco/geodata/basic-services","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_education.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get locations of education services in Europe — gisco_get_education","text":"year Release year file. One \"2020\", \"2023\" (default). cache logical whether caching. Default TRUE. See caching. update_cache logical whether update cache. Default FALSE. set TRUE force fresh download source .geojson file. cache_dir path cache directory. See caching. verbose Logical, displays information. Useful debugging, default FALSE. country Optional. character vector country codes. either vector country names, vector ISO3 country codes vector Eurostat country codes. Mixed types (c(\"Italy\",\"ES\",\"FRA\")) work. See also countrycode::countrycode().","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_education.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get locations of education services in Europe — gisco_get_education","text":"POINT sf object.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_education.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get locations of education services in Europe — gisco_get_education","text":"Files distributed EPSG:4326. Metadata available https://gisco-services.ec.europa.eu/pub/education/metadata.pdf.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_education.html","id":"about-caching","dir":"Reference","previous_headings":"","what":"About caching","title":"Get locations of education services in Europe — gisco_get_education","text":"can set cache_dir gisco_set_cache_dir(). Sometimes cached files may corrupt. case, try re-downloading data setting update_cache = TRUE. experience problem download, try download corresponding .geojson file method save cache_dir. Use option verbose = TRUE debugging API query. complete list files available check gisco_db.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_education.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Get locations of education services in Europe — gisco_get_education","text":"dieghernan, https://github.com/dieghernan/","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_education.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get locations of education services in Europe — gisco_get_education","text":"","code":"# \\donttest{ edu_BEL <- gisco_get_education(country = \"Belgium\") # Plot if downloaded if (nrow(edu_BEL) > 3) { library(ggplot2) ggplot(edu_BEL) + geom_sf(shape = 21, size = 0.15) } # }"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_grid.html","id":null,"dir":"Reference","previous_headings":"","what":"Get grid cells covering covering Europe for various resolutions — gisco_get_grid","title":"Get grid cells covering covering Europe for various resolutions — gisco_get_grid","text":"datasets contain grid cells covering European land territory, various resolutions 1km 100km. Base statistics population figures provided cells.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_grid.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get grid cells covering covering Europe for various resolutions — gisco_get_grid","text":"","code":"gisco_get_grid( resolution = \"20\", spatialtype = c(\"REGION\", \"POINT\"), cache_dir = NULL, update_cache = FALSE, verbose = FALSE )"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_grid.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Get grid cells covering covering Europe for various resolutions — gisco_get_grid","text":"https://ec.europa.eu/eurostat/web/gisco/geodata/grids","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_grid.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get grid cells covering covering Europe for various resolutions — gisco_get_grid","text":"resolution Resolution grid cells kms. Available values \"1\", \"2\", \"5\", \"10\", \"20\", \"50\", \"100\". See Details. spatialtype Select one \"REGION\" \"POINT\". cache_dir path cache directory. See caching. update_cache logical whether update cache. Default FALSE. set TRUE force fresh download source .geojson file. verbose Logical, displays information. Useful debugging, default FALSE.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_grid.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get grid cells covering covering Europe for various resolutions — gisco_get_grid","text":"POLYGON/POINT sf object.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_grid.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get grid cells covering covering Europe for various resolutions — gisco_get_grid","text":"Files distributed EPSG:3035. file sizes range 428Kb (resolution = \"100\") 1.7Gb resolution = \"1\". resolutions 1km 2km need confirm download.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_grid.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Get grid cells covering covering Europe for various resolutions — gisco_get_grid","text":"specific downloading provisions, please see https://ec.europa.eu/eurostat/web/gisco/geodata/grids","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_grid.html","id":"about-caching","dir":"Reference","previous_headings":"","what":"About caching","title":"Get grid cells covering covering Europe for various resolutions — gisco_get_grid","text":"can set cache_dir gisco_set_cache_dir(). Sometimes cached files may corrupt. case, try re-downloading data setting update_cache = TRUE. experience problem download, try download corresponding .geojson file method save cache_dir. Use option verbose = TRUE debugging API query. complete list files available check gisco_db.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_grid.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Get grid cells covering covering Europe for various resolutions — gisco_get_grid","text":"dieghernan, https://github.com/dieghernan/","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_grid.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get grid cells covering covering Europe for various resolutions — gisco_get_grid","text":"","code":"# \\donttest{ grid <- gisco_get_grid(resolution = 20) #> Warning: GDAL Message 1: GPKG: unrecognized user_version=0x00000000 (0) on 'C:\\Users\\runneradmin\\AppData\\Local\\Temp\\RtmpS07t9H\\giscoR\\pkgdown\\grid_20km_surf.gpkg' # If downloaded correctly proceed if (!is.null(grid)) { library(dplyr) grid <- grid %>% mutate(popdens = TOT_P_2021 / 20) breaks <- c(0, 0.1, 100, 500, 1000, 5000, 10000, Inf) # Cut groups grid <- grid %>% mutate(popdens_cut = cut(popdens, breaks = breaks, include.lowest = TRUE )) cut_labs <- prettyNum(breaks, big.mark = \" \")[-1] cut_labs[1] <- \"0\" cut_labs[7] <- \"> 10 000\" pal <- c(\"black\", hcl.colors(length(breaks) - 2, palette = \"Spectral\", alpha = 0.9 )) library(ggplot2) ggplot(grid) + geom_sf(aes(fill = popdens_cut), color = NA, linewidth = 0) + coord_sf( xlim = c(2500000, 7000000), ylim = c(1500000, 5200000) ) + scale_fill_manual( values = pal, na.value = \"black\", name = \"people per sq. kilometer\", labels = cut_labs, guide = guide_legend( direction = \"horizontal\", nrow = 1 ) ) + theme_void() + labs( title = \"Population density in Europe (2021)\", subtitle = \"Grid: 20 km.\", caption = gisco_attributions() ) + theme( text = element_text(colour = \"white\"), plot.background = element_rect(fill = \"grey2\"), plot.title = element_text(hjust = 0.5), plot.subtitle = element_text(hjust = 0.5, face = \"bold\"), plot.caption = element_text( color = \"grey60\", hjust = 0.5, vjust = 0, margin = margin(t = 5, b = 10) ), legend.position = \"bottom\", legend.title.position = \"top\", legend.text.position = \"bottom\", legend.key.height = unit(0.5, \"lines\"), legend.key.width = unit(1, \"lines\") ) } #> #> Attaching package: 'dplyr' #> The following objects are masked from 'package:stats': #> #> filter, lag #> The following objects are masked from 'package:base': #> #> intersect, setdiff, setequal, union # }"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_healthcare.html","id":null,"dir":"Reference","previous_headings":"","what":"Get locations of healthcare services in Europe — gisco_get_healthcare","title":"Get locations of healthcare services in Europe — gisco_get_healthcare","text":"dataset contains information main healthcare services considered 'hospitals' Member States.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_healthcare.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get locations of healthcare services in Europe — gisco_get_healthcare","text":"","code":"gisco_get_healthcare( year = c(\"2023\", \"2020\"), cache = TRUE, update_cache = FALSE, cache_dir = NULL, verbose = FALSE, country = NULL )"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_healthcare.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Get locations of healthcare services in Europe — gisco_get_healthcare","text":"https://ec.europa.eu/eurostat/web/gisco/geodata/basic-services","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_healthcare.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get locations of healthcare services in Europe — gisco_get_healthcare","text":"year Release year file. One \"2020\", \"2023\" (default). cache logical whether caching. Default TRUE. See caching. update_cache logical whether update cache. Default FALSE. set TRUE force fresh download source .geojson file. cache_dir path cache directory. See caching. verbose Logical, displays information. Useful debugging, default FALSE. country Optional. character vector country codes. either vector country names, vector ISO3 country codes vector Eurostat country codes. Mixed types (c(\"Italy\",\"ES\",\"FRA\")) work. See also countrycode::countrycode().","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_healthcare.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get locations of healthcare services in Europe — gisco_get_healthcare","text":"POINT sf object.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_healthcare.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get locations of healthcare services in Europe — gisco_get_healthcare","text":"Files distributed EPSG:4326. Metadata available https://gisco-services.ec.europa.eu/pub/healthcare/metadata.pdf.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_healthcare.html","id":"about-caching","dir":"Reference","previous_headings":"","what":"About caching","title":"Get locations of healthcare services in Europe — gisco_get_healthcare","text":"can set cache_dir gisco_set_cache_dir(). Sometimes cached files may corrupt. case, try re-downloading data setting update_cache = TRUE. experience problem download, try download corresponding .geojson file method save cache_dir. Use option verbose = TRUE debugging API query. complete list files available check gisco_db.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_healthcare.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Get locations of healthcare services in Europe — gisco_get_healthcare","text":"dieghernan, https://github.com/dieghernan/","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_healthcare.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get locations of healthcare services in Europe — gisco_get_healthcare","text":"","code":"# \\donttest{ health_be <- gisco_get_healthcare(country = \"Belgium\") # Plot if downloaded if (inherits(health_be, \"sf\")) { library(ggplot2) ggplot(health_be) + geom_sf() } # }"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_lau.html","id":null,"dir":"Reference","previous_headings":"","what":"Get GISCO urban areas sf polygons, points and lines — gisco_get_lau","title":"Get GISCO urban areas sf polygons, points and lines — gisco_get_lau","text":"gisco_get_communes() gisco_get_lau() download shapes Local Urban Areas, correspond roughly towns cities.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_lau.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get GISCO urban areas sf polygons, points and lines — gisco_get_lau","text":"","code":"gisco_get_communes( year = \"2016\", epsg = \"4326\", cache = TRUE, update_cache = FALSE, cache_dir = NULL, verbose = FALSE, spatialtype = \"RG\", country = NULL ) gisco_get_lau( year = \"2021\", epsg = \"4326\", cache = TRUE, update_cache = FALSE, cache_dir = NULL, verbose = FALSE, country = NULL, gisco_id = NULL )"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_lau.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get GISCO urban areas sf polygons, points and lines — gisco_get_lau","text":"year Release year file: gisco_get_communes() one \"2001\", \"2004\", \"2006\", \"2008\", \"2010\", \"2013\" \"2016\". gisco_get_lau() one \"2011\", \"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\", \"2018\", \"2019\", \"2020\" \"2021\". epsg projection map: 4-digit EPSG code. One : \"4258\": ETRS89 \"4326\": WGS84 \"3035\": ETRS89 / ETRS-LAEA \"3857\": Pseudo-Mercator cache logical whether caching. Default TRUE. See caching. update_cache logical whether update cache. Default FALSE. set TRUE force fresh download source .geojson file. cache_dir path cache directory. See caching. verbose Logical, displays information. Useful debugging, default FALSE. spatialtype Type geometry returned: \"BN\": Boundaries - LINESTRING object. \"COASTL\": coastlines - LINESTRING object. \"INLAND\": inland boundaries - LINESTRING object. \"LB\": Labels - POINT object. \"RG\": Regions - MULTIPOLYGON/POLYGON object. Note parameters country region applied spatialtype \"BN\" \"RG\". country Optional. character vector country codes. either vector country names, vector ISO3 country codes vector Eurostat country codes. Mixed types (c(\"Italy\",\"ES\",\"FRA\")) work. See also countrycode::countrycode(). gisco_id Optional. character vector GISCO_ID LAU values.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_lau.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get GISCO urban areas sf polygons, points and lines — gisco_get_lau","text":"sf object specified spatialtype. case gisco_get_lau(), POLYGON object.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_lau.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Get GISCO urban areas sf polygons, points and lines — gisco_get_lau","text":"Please check download usage provisions gisco_attributions().","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_lau.html","id":"about-caching","dir":"Reference","previous_headings":"","what":"About caching","title":"Get GISCO urban areas sf polygons, points and lines — gisco_get_lau","text":"can set cache_dir gisco_set_cache_dir(). Sometimes cached files may corrupt. case, try re-downloading data setting update_cache = TRUE. experience problem download, try download corresponding .geojson file method save cache_dir. Use option verbose = TRUE debugging API query. complete list files available check gisco_db.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_lau.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get GISCO urban areas sf polygons, points and lines — gisco_get_lau","text":"","code":"# \\donttest{ ire_lau <- gisco_get_communes(spatialtype = \"LB\", country = \"Ireland\") if (!is.null(ire_lau)) { library(ggplot2) ggplot(ire_lau) + geom_sf(shape = 21, col = \"#009A44\", size = 0.5) + labs( title = \"Communes in Ireland\", subtitle = \"Year 2016\", caption = gisco_attributions() ) + theme_void() + theme(text = element_text( colour = \"#009A44\", family = \"serif\", face = \"bold\" )) } # }"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_nuts.html","id":null,"dir":"Reference","previous_headings":"","what":"Get GISCO NUTS sf polygons, points and lines — gisco_get_nuts","title":"Get GISCO NUTS sf polygons, points and lines — gisco_get_nuts","text":"Returns NUTS regions polygons, lines points specified scale, provided GISCO. NUTS provided three different levels: \"0\": Country level \"1\": Groups states/regions \"2\": States/regions \"3\": Counties/provinces/districts Note NUTS-level definition may vary across countries. See also https://ec.europa.eu/eurostat/web/gisco/geodata//statistical-units/territorial-units-statistics.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_nuts.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get GISCO NUTS sf polygons, points and lines — gisco_get_nuts","text":"","code":"gisco_get_nuts( year = \"2016\", epsg = \"4326\", cache = TRUE, update_cache = FALSE, cache_dir = NULL, verbose = FALSE, resolution = \"20\", spatialtype = \"RG\", country = NULL, nuts_id = NULL, nuts_level = \"all\" )"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_nuts.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Get GISCO NUTS sf polygons, points and lines — gisco_get_nuts","text":"https://gisco-services.ec.europa.eu/distribution/v2/","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_nuts.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get GISCO NUTS sf polygons, points and lines — gisco_get_nuts","text":"year Release year file. One \"2003\", \"2006\", \"2010\", \"2013\", \"2016\", \"2021\" \"2024\". epsg projection map: 4-digit EPSG code. One : \"4258\": ETRS89 \"4326\": WGS84 \"3035\": ETRS89 / ETRS-LAEA \"3857\": Pseudo-Mercator cache logical whether caching. Default TRUE. See caching. update_cache logical whether update cache. Default FALSE. set TRUE force fresh download source .geojson file. cache_dir path cache directory. See caching. verbose Logical, displays information. Useful debugging, default FALSE. resolution Resolution geospatial data. One \"60\": 1:60million \"20\": 1:20million \"10\": 1:10million \"03\": 1:3million \"01\": 1:1million spatialtype Type geometry returned: \"BN\": Boundaries - LINESTRING object. \"LB\": Labels - POINT object. \"RG\": Regions - MULTIPOLYGON/POLYGON object. Note parameters country, nuts_level nuts_id applied spatialtype \"BN\" \"RG\". country Optional. character vector country codes. either vector country names, vector ISO3 country codes vector Eurostat country codes. Mixed types (c(\"Italy\",\"ES\",\"FRA\")) work. See also countrycode::countrycode(). nuts_id Optional. character vector NUTS IDs. nuts_level NUTS level. One \"0\", \"1\", \"2\" \"3\". See Description.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_nuts.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get GISCO NUTS sf polygons, points and lines — gisco_get_nuts","text":"sf object specified spatialtype. resulting sf object present additional column geo (equal NUTS_ID) improving compatibility eurostat package. See eurostat::get_eurostat_geospatial()). See also gisco_nuts understand columns values provided.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_nuts.html","id":"about-caching","dir":"Reference","previous_headings":"","what":"About caching","title":"Get GISCO NUTS sf polygons, points and lines — gisco_get_nuts","text":"can set cache_dir gisco_set_cache_dir(). Sometimes cached files may corrupt. case, try re-downloading data setting update_cache = TRUE. experience problem download, try download corresponding .geojson file method save cache_dir. Use option verbose = TRUE debugging API query. complete list files available check gisco_db.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_nuts.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get GISCO NUTS sf polygons, points and lines — gisco_get_nuts","text":"","code":"nuts2 <- gisco_get_nuts(nuts_level = 2) library(ggplot2) ggplot(nuts2) + geom_sf() + # ETRS89 / ETRS-LAEA coord_sf( crs = 3035, xlim = c(2377294, 7453440), ylim = c(1313597, 5628510) ) + labs(title = \"NUTS-2 levels\") # \\donttest{ # NUTS-3 for Germany germany_nuts3 <- gisco_get_nuts(nuts_level = 3, country = \"Germany\") ggplot(germany_nuts3) + geom_sf() + labs( title = \"NUTS-3 levels\", subtitle = \"Germany\", caption = gisco_attributions() ) # Select specific regions select_nuts <- gisco_get_nuts(nuts_id = c(\"ES2\", \"FRJ\", \"FRL\", \"ITC\")) ggplot(select_nuts) + geom_sf(aes(fill = CNTR_CODE)) + scale_fill_viridis_d() # }"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_postalcodes.html","id":null,"dir":"Reference","previous_headings":"","what":"Get postal code points from GISCO — gisco_get_postalcodes","title":"Get postal code points from GISCO — gisco_get_postalcodes","text":"Get postal codes points EU, EFTA candidate countries.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_postalcodes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get postal code points from GISCO — gisco_get_postalcodes","text":"","code":"gisco_get_postalcodes( year = \"2020\", country = NULL, cache_dir = NULL, update_cache = FALSE, verbose = FALSE )"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_postalcodes.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Get postal code points from GISCO — gisco_get_postalcodes","text":"https://ec.europa.eu/eurostat/web/gisco/geodata//administrative-units/postal-codes.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_postalcodes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get postal code points from GISCO — gisco_get_postalcodes","text":"year Year reference. Currently \"2020\" available. country Optional. character vector country codes. either vector country names, vector ISO3 country codes vector Eurostat country codes. Mixed types (c(\"Italy\",\"ES\",\"FRA\")) work. See also countrycode::countrycode(). cache_dir path cache directory. See caching. update_cache logical whether update cache. Default FALSE. set TRUE force fresh download source .geojson file. verbose Logical, displays information. Useful debugging, default FALSE.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_postalcodes.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get postal code points from GISCO — gisco_get_postalcodes","text":"POINT sf object EPSG:4326.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_postalcodes.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get postal code points from GISCO — gisco_get_postalcodes","text":"postal code point dataset shows location postal codes, NUTS codes Degree Urbanisation classification across EU, EFTA candidate countries variety sources. primary purpose create correspondence tables NUTS classification (EC) 1059/2003 part Tercet Regulation (EU) 2017/2391","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_postalcodes.html","id":"copyright","dir":"Reference","previous_headings":"","what":"Copyright","title":"Get postal code points from GISCO — gisco_get_postalcodes","text":"dataset released CC--SA-4.0 licence requires following attribution whenever used: (c) European Union - GISCO, 2021, postal code point dataset, Licence CC--SA 4.0 available https://ec.europa.eu/eurostat/web/gisco/geodata//administrative-units/postal-codes. Shapefiles provided ETRS89 (EPSG:4258).","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_postalcodes.html","id":"about-caching","dir":"Reference","previous_headings":"","what":"About caching","title":"Get postal code points from GISCO — gisco_get_postalcodes","text":"can set cache_dir gisco_set_cache_dir(). Sometimes cached files may corrupt. case, try re-downloading data setting update_cache = TRUE. experience problem download, try download corresponding .geojson file method save cache_dir. Use option verbose = TRUE debugging API query. complete list files available check gisco_db.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_postalcodes.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get postal code points from GISCO — gisco_get_postalcodes","text":"","code":"# Heavy-weight download! # \\dontrun{ pc_bel <- gisco_get_postalcodes(country = \"BE\") if (!is.null(pc_bel)) { library(ggplot2) ggplot(pc_bel) + geom_sf(color = \"gold\") + theme_bw() + labs( title = \"Postcodes of Belgium\", subtitle = \"2020\", caption = paste(\"(c) European Union - GISCO, 2021,\", \"postal code point dataset\", \"Licence CC-BY-SA 4.0\", sep = \"\\n\" ) ) } # }"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_units.html","id":null,"dir":"Reference","previous_headings":"","what":"Get geospatial units data from GISCO API — gisco_get_units","title":"Get geospatial units data from GISCO API — gisco_get_units","text":"Download individual shapefiles units. Unlike gisco_get_countries(), gisco_get_nuts() gisco_get_urban_audit(), downloads full dataset applies filters, gisco_get_units() downloads single shapefile unit.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_units.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get geospatial units data from GISCO API — gisco_get_units","text":"","code":"gisco_get_units( id_giscoR = c(\"nuts\", \"countries\", \"urban_audit\"), unit = \"ES4\", mode = c(\"sf\", \"df\"), year = \"2016\", epsg = \"4326\", cache = TRUE, update_cache = FALSE, cache_dir = NULL, verbose = FALSE, resolution = \"20\", spatialtype = \"RG\" )"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_units.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Get geospatial units data from GISCO API — gisco_get_units","text":"https://gisco-services.ec.europa.eu/distribution/v2/","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_units.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get geospatial units data from GISCO API — gisco_get_units","text":"id_giscoR Select unit type downloaded. Accepted values \"nuts\", \"countries\" \"urban_audit\". unit Unit ID downloaded. See Details. mode Controls output function. Possible values \"sf\" \"df\". See Value Details. year Release year file. One \"2001\", \"2006\", \"2010\", \"2013\", \"2016\", \"2020\" \"2024\". epsg projection map: 4-digit EPSG code. One : \"4258\": ETRS89 \"4326\": WGS84 \"3035\": ETRS89 / ETRS-LAEA \"3857\": Pseudo-Mercator cache logical whether caching. Default TRUE. See caching. update_cache logical whether update cache. Default FALSE. set TRUE force fresh download source .geojson file. cache_dir path cache directory. See caching. verbose Logical, displays information. Useful debugging, default FALSE. resolution Resolution geospatial data. One \"60\": 1:60million \"20\": 1:20million \"10\": 1:10million \"03\": 1:3million \"01\": 1:1million spatialtype Type geometry returned: \"RG\", POLYGON \"LB\" POINT.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_units.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get geospatial units data from GISCO API — gisco_get_units","text":"sf object mode = \"sf\" data frame mode = \"df\".","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_units.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Get geospatial units data from GISCO API — gisco_get_units","text":"function can return data frame mode = \"df\" sf object mode = \"sf\". order see available unit ids required combination spatialtype, year, first run function \"df\" mode. get data frame can select required ids unit parameter. mode = \"df\" relevant parameters spatialtype, year.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_units.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Get geospatial units data from GISCO API — gisco_get_units","text":"Country-level files renamed cache_dir avoid naming conflicts NUTS-0 datasets. Please check download usage provisions gisco_attributions().","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_units.html","id":"about-caching","dir":"Reference","previous_headings":"","what":"About caching","title":"Get geospatial units data from GISCO API — gisco_get_units","text":"can set cache_dir gisco_set_cache_dir(). Sometimes cached files may corrupt. case, try re-downloading data setting update_cache = TRUE. experience problem download, try download corresponding .geojson file method save cache_dir. Use option verbose = TRUE debugging API query. complete list files available check gisco_db.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_units.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Get geospatial units data from GISCO API — gisco_get_units","text":"dieghernan, https://github.com/dieghernan/","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_units.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get geospatial units data from GISCO API — gisco_get_units","text":"","code":"# \\donttest{ cities <- gisco_get_units( id_giscoR = \"urban_audit\", mode = \"df\", year = \"2020\" ) VAL <- cities[grep(\"Valencia\", cities$URAU_NAME), ] # Order from big to small VAL <- VAL[order(as.double(VAL$AREA_SQM), decreasing = TRUE), ] VAL.sf <- gisco_get_units( id_giscoR = \"urban_audit\", year = \"2020\", unit = VAL$URAU_CODE ) # Provincia Provincia <- gisco_get_units( id_giscoR = \"nuts\", unit = c(\"ES523\"), resolution = \"01\" ) # Reorder VAL.sf$URAU_CATG <- factor(VAL.sf$URAU_CATG, levels = c(\"F\", \"K\", \"C\")) # Plot library(ggplot2) ggplot(Provincia) + geom_sf(fill = \"gray1\") + geom_sf(data = VAL.sf, aes(fill = URAU_CATG)) + scale_fill_viridis_d() + labs( title = \"Valencia\", subtitle = \"Urban Audit\", fill = \"Urban Audit\\ncategory\" ) # }"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_urban_audit.html","id":null,"dir":"Reference","previous_headings":"","what":"Get GISCO greater cities and metropolitan areas sf objects — gisco_get_urban_audit","title":"Get GISCO greater cities and metropolitan areas sf objects — gisco_get_urban_audit","text":"Returns polygons points corresponding cities, greater cities metropolitan areas included Urban Audit report Eurostat.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_urban_audit.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get GISCO greater cities and metropolitan areas sf objects — gisco_get_urban_audit","text":"","code":"gisco_get_urban_audit( year = \"2021\", epsg = \"4326\", cache = TRUE, update_cache = FALSE, cache_dir = NULL, verbose = FALSE, spatialtype = \"RG\", country = NULL, level = NULL )"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_urban_audit.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Get GISCO greater cities and metropolitan areas sf objects — gisco_get_urban_audit","text":"https://gisco-services.ec.europa.eu/distribution/v2/","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_urban_audit.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get GISCO greater cities and metropolitan areas sf objects — gisco_get_urban_audit","text":"year Release year file. One \"2001\", \"2004\", \"2014\", \"2018\", \"2020\" \"2021\". epsg projection map: 4-digit EPSG code. One : \"4258\": ETRS89 \"4326\": WGS84 \"3035\": ETRS89 / ETRS-LAEA \"3857\": Pseudo-Mercator cache logical whether caching. Default TRUE. See caching. update_cache logical whether update cache. Default FALSE. set TRUE force fresh download source .geojson file. cache_dir path cache directory. See caching. verbose Logical, displays information. Useful debugging, default FALSE. spatialtype Type geometry returned: \"LB\": Labels - POINT object. \"RG\": Regions - MULTIPOLYGON/POLYGON object. country Optional. character vector country codes. either vector country names, vector ISO3 country codes vector Eurostat country codes. Mixed types (c(\"Italy\",\"ES\",\"FRA\")) work. See also countrycode::countrycode(). level Level Urban Audit. Possible values \"CITIES\", \"FUA\", \"GREATER_CITIES\" NULL, download full dataset.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_urban_audit.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get GISCO greater cities and metropolitan areas sf objects — gisco_get_urban_audit","text":"sf object specified spatialtype.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_urban_audit.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Get GISCO greater cities and metropolitan areas sf objects — gisco_get_urban_audit","text":"Please check download usage provisions gisco_attributions().","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_urban_audit.html","id":"about-caching","dir":"Reference","previous_headings":"","what":"About caching","title":"Get GISCO greater cities and metropolitan areas sf objects — gisco_get_urban_audit","text":"can set cache_dir gisco_set_cache_dir(). Sometimes cached files may corrupt. case, try re-downloading data setting update_cache = TRUE. experience problem download, try download corresponding .geojson file method save cache_dir. Use option verbose = TRUE debugging API query. complete list files available check gisco_db.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_get_urban_audit.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get GISCO greater cities and metropolitan areas sf objects — gisco_get_urban_audit","text":"","code":"# \\donttest{ cities <- gisco_get_urban_audit(year = \"2020\", level = \"CITIES\") if (!is.null(cities)) { bcn <- cities[cities$URAU_NAME == \"Barcelona\", ] library(ggplot2) ggplot(bcn) + geom_sf() } # }"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_nuts.html","id":null,"dir":"Reference","previous_headings":"","what":"All NUTS POLYGON object — gisco_nuts","title":"All NUTS POLYGON object — gisco_nuts","text":"sf object including NUTS levels provided GISCO (2016 version).","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_nuts.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"All NUTS POLYGON object — gisco_nuts","text":"POLYGON data frame (resolution: 1:20million, EPSG:4326) object 2,016 rows 11 variables: NUTS_ID NUTS identifier. LEVL_CODE NUTS level code (0,1,2,3). URBN_TYPE Urban Type, see Details. CNTR_CODE Eurostat Country code. NAME_LATN NUTS name Latin characters. NUTS_NAME NUTS name local alphabet. MOUNT_TYPE Mount Type, see Details. COAST_TYPE Coast Type, see Details. FID FID. geo NUTS_ID, provided compatibility eurostat. geometry geometry field.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_nuts.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"All NUTS POLYGON object — gisco_nuts","text":"NUTS_RG_20M_2016_4326.geojson file.","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_nuts.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"All NUTS POLYGON object — gisco_nuts","text":"MOUNT_TYPE: Mountain typology: 1: 50 % surface covered topographic mountain areas. 2: 50 % regional population lives topographic mountain areas. 3: 50 % surface covered topographic mountain areas 50 % regional population lives mountain areas. 4: Non-mountain region / regions. 0: classification provided. URBN_TYPE: Urban-rural typology: 1: Predominantly urban region. 2: Intermediate region. 3: Predominantly rural region. 0: classification provided. COAST_TYPE: Coastal typology: 1: Coastal (coast). 2: Coastal (less 50% population living within 50 km. coastline). 3: Non-coastal region. 0: classification provided.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_nuts.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"All NUTS POLYGON object — gisco_nuts","text":"","code":"data(\"gisco_nuts\") head(gisco_nuts) #> Simple feature collection with 6 features and 10 fields #> Geometry type: MULTIPOLYGON #> Dimension: XY #> Bounding box: xmin: -63.08825 ymin: -21.39077 xmax: 55.83808 ymax: 70.08134 #> Geodetic CRS: WGS 84 #> NUTS_ID LEVL_CODE URBN_TYPE CNTR_CODE NAME_LATN #> 1 ES 0 0 ES ESPAÑA #> 2 FI 0 0 FI SUOMI / FINLAND #> 3 IS 0 0 IS ÍSLAND #> 4 PT2 1 0 PT REGIÃO AUTÓNOMA DOS AÇORES #> 5 FR 0 0 FR FRANCE #> 6 HR 0 0 HR HRVATSKA #> NUTS_NAME MOUNT_TYPE COAST_TYPE FID geo #> 1 ESPAÑA 0 0 ES ES #> 2 SUOMI / FINLAND 0 0 FI FI #> 3 ÍSLAND 0 0 IS IS #> 4 REGIÃO AUTÓNOMA DOS AÇORES 0 0 PT2 PT2 #> 5 FRANCE 0 0 FR FR #> 6 HRVATSKA 0 0 HR HR #> geometry #> 1 MULTIPOLYGON (((4.17069 40.... #> 2 MULTIPOLYGON (((28.8195 69.... #> 3 MULTIPOLYGON (((-21.25398 6... #> 4 MULTIPOLYGON (((-25.18988 3... #> 5 MULTIPOLYGON (((55.32105 -2... #> 6 MULTIPOLYGON (((16.37339 46..."},{"path":"https://ropengov.github.io/giscoR/reference/gisco_set_cache_dir.html","id":null,"dir":"Reference","previous_headings":"","what":"Set your giscoR cache dir — gisco_set_cache_dir","title":"Set your giscoR cache dir — gisco_set_cache_dir","text":"function store cache_dir path local machine load future sessions. Type Sys.getenv(\"GISCO_CACHE_DIR\") find cached path use gisco_detect_cache_dir(). Alternatively, can store cache_dir manually following options: Run Sys.setenv(GISCO_CACHE_DIR = \"cache_dir\"). need run command session (Similar install = FALSE). Write line .Renviron file: GISCO_CACHE_DIR = \"value_for_cache_dir\" (behavior install = TRUE). store cache_dir permanently. See also usethis::edit_r_environ().","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_set_cache_dir.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Set your giscoR cache dir — gisco_set_cache_dir","text":"","code":"gisco_set_cache_dir( cache_dir, overwrite = FALSE, install = FALSE, verbose = TRUE ) gisco_detect_cache_dir(...)"},{"path":"https://ropengov.github.io/giscoR/reference/gisco_set_cache_dir.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Set your giscoR cache dir — gisco_set_cache_dir","text":"cache_dir path cache directory. missing value function store cached files temporary dir (See base::tempdir()). overwrite set TRUE, overwrite existing GISCO_CACHE_DIR already local machine. install TRUE, install key local machine use future sessions. Defaults FALSE. cache_dir FALSE parameter set FALSE automatically. verbose Logical, displays information. Useful debugging, default FALSE. ... Ignored","code":""},{"path":"https://ropengov.github.io/giscoR/reference/gisco_set_cache_dir.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Set your giscoR cache dir — gisco_set_cache_dir","text":"gisco_set_cache_dir() returns (invisible) character path cache_dir, mainly called side effect. gisco_detect_cache_dir() returns path cache_dir used session.","code":""},{"path":[]},{"path":"https://ropengov.github.io/giscoR/reference/gisco_set_cache_dir.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Set your giscoR cache dir — gisco_set_cache_dir","text":"","code":"# Don't run this! It would modify your current state # \\dontrun{ gisco_set_cache_dir(verbose = TRUE) #> Using a temporary cache dir. Set 'cache_dir' to a value for store permanently #> giscoR cache dir is: C:\\Users\\RUNNER~1\\AppData\\Local\\Temp\\RtmpS07t9H/giscoR # } Sys.getenv(\"GISCO_CACHE_DIR\") #> [1] \"C:\\\\Users\\\\RUNNER~1\\\\AppData\\\\Local\\\\Temp\\\\RtmpS07t9H/giscoR\" gisco_detect_cache_dir() #> [1] \"C:\\\\Users\\\\RUNNER~1\\\\AppData\\\\Local\\\\Temp\\\\RtmpS07t9H/giscoR\""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"giscor-060","dir":"Changelog","previous_headings":"","what":"giscoR 0.6.0","title":"giscoR 0.6.0","text":"CRAN release: 2024-08-28","code":""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"update-with-latest-data-available-0-6-0","dir":"Changelog","previous_headings":"","what":"Update with latest data available","title":"giscoR 0.6.0","text":"gisco_get_education() gisco_get_healthcare() gains new year argument: years available now 2020 2023 versions dataset. gisco_get_nuts() gisco_get_countries() now can download 2024 version datasets (#93 @hannesaddec).","code":""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"giscor-051","dir":"Changelog","previous_headings":"","what":"giscoR 0.5.1","title":"giscoR 0.5.1","text":"CRAN release: 2024-07-06 Use CRAN DOI: https://doi.org/10.32614/CRAN.package.giscoR. gisco_get_education(): Fix API entry points. Review failing examples.","code":""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"giscor-050","dir":"Changelog","previous_headings":"","what":"giscoR 0.5.0","title":"giscoR 0.5.0","text":"CRAN release: 2024-05-29 gisco_get_education(). Add access GISCO Address API new functions. See ?gisco_addressapi know (#84). New dependency: jsonlite added ‘Imports’. Update gisco_db --date released data. gisco_get_lau() gisco_get_urban_audit() default year now \"2021\". Update urls documentation.","code":""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"giscor-042","dir":"Changelog","previous_headings":"","what":"giscoR 0.4.2","title":"giscoR 0.4.2","text":"CRAN release: 2024-03-27 Update docs avoid warnings CRAN (#81). Rebuild datasets.","code":""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"giscor-041","dir":"Changelog","previous_headings":"","what":"giscoR 0.4.1","title":"giscoR 0.4.1","text":"CRAN release: 2024-03-15 Improve documentation, stating parameters country region applies (#50, #75). Migrate httr2 instead httr. Removed tgs00026 dataset, use eurostat::get_eurostat(\"tgs00026\") instead.","code":""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"giscor-040","dir":"Changelog","previous_headings":"","what":"giscoR 0.4.0","title":"giscoR 0.4.0","text":"CRAN release: 2023-10-30 gisco_get_nuts(): Add additional geo column (identical NUTS_ID) enhanced compatibility eurostat package (#62). Adjust examples CRAN. Add dependency httr.","code":""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"giscor-035","dir":"Changelog","previous_headings":"","what":"giscoR 0.3.5","title":"giscoR 0.3.5","text":"CRAN release: 2023-06-30 Review examples avoid CRAN errors notes. New helper function: gisco_detect_cache_dir(). Now functions fail gracefully informative message, instead error, return NULL.","code":""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"giscor-034","dir":"Changelog","previous_headings":"","what":"giscoR 0.3.4","title":"giscoR 0.3.4","text":"CRAN release: 2023-05-26 Update tests documentation.","code":""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"giscor-033","dir":"Changelog","previous_headings":"","what":"giscoR 0.3.3","title":"giscoR 0.3.3","text":"CRAN release: 2023-02-16 Fix broken urls gisco_get_healthcare() (#51).","code":""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"giscor-032","dir":"Changelog","previous_headings":"","what":"giscoR 0.3.2","title":"giscoR 0.3.2","text":"CRAN release: 2022-08-13 Fix HTML5 issue requested CRAN.","code":""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"giscor-031","dir":"Changelog","previous_headings":"","what":"giscoR 0.3.1","title":"giscoR 0.3.1","text":"CRAN release: 2021-10-06 Add Copyright DESCRIPTION. Add lwgeom ‘Suggests’. year available 2013. Now information downloaded instead using internal data. New function: gisco_get_postalcodes(). Update gisco_db.","code":""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"giscor-030","dir":"Changelog","previous_headings":"","what":"giscoR 0.3.0","title":"giscoR 0.3.0","text":"CRAN release: 2021-09-27 Now giscoR part rOpenGov. Repo transferred. Caching improvements: new function gisco_set_cache_dir() based rappdirs::user_cache_dir(). Now cache_dir path stored necessary set new session. Also added gisco_clear_cache(). Fix error cache = FALSE. Now files loaded instead throwing error. New tests testthat. Update docs. New examples Refactor documents codes previous gisco_get doc. Add eurostat package ’ Suggests’. lwgeom dependency removed. Update internal grid object. tmap package replaced ggplot2 vignettes examples.","code":""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"giscor-024","dir":"Changelog","previous_headings":"","what":"giscoR 0.2.4","title":"giscoR 0.2.4","text":"CRAN release: 2021-04-13 New eu field giscoR::gisco_countrycode. Fix typos documentation. Include vignette package. Move docs roxygen2. lwgeom moved ‘Imports’ field. cartography package replaced tmap vignettes.","code":""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"giscor-023","dir":"Changelog","previous_headings":"","what":"giscoR 0.2.3","title":"giscoR 0.2.3","text":"Update docs Release DOI","code":""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"giscor-022","dir":"Changelog","previous_headings":"","what":"giscoR 0.2.2","title":"giscoR 0.2.2","text":"CRAN release: 2020-11-23 Remove vignette","code":""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"giscor-021","dir":"Changelog","previous_headings":"","what":"giscoR 0.2.1","title":"giscoR 0.2.1","text":"Remove CRAN notes. Improve docs. Fix CRAN checks.","code":""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"giscor-020","dir":"Changelog","previous_headings":"","what":"giscoR 0.2.0","title":"giscoR 0.2.0","text":"CRAN release: 2020-11-12 Remove colorspace dependency. Bump R minimal version 3.6.0. Change order parameters gisco_get() functions. Rewriting internal functions utils. Add verbose parameter functions. Rewriting giscoR::gisco_db. gisco_bulk_download() gisco_check_access() gisco_get_airports() gisco_get_grid() gisco_get_ports() gisco_get_units() Now gisco_get_countries() gisco_get_nuts() uses gisco_get_units() individual files, making call much faster.","code":""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"giscor-011","dir":"Changelog","previous_headings":"","what":"giscoR 0.1.1","title":"giscoR 0.1.1","text":"CRAN release: 2020-10-28 Added giscoR::tgs00026 dataset. Remove eurostat dependency.","code":""},{"path":"https://ropengov.github.io/giscoR/news/index.html","id":"giscor-010","dir":"Changelog","previous_headings":"","what":"giscoR 0.1.0","title":"giscoR 0.1.0","text":"CRAN release: 2020-10-13 First stable release.","code":""}]

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