--- title: "Get started with giscoR" output: rmarkdown::html_vignette vignette: > %\VignetteIndexEntry{Get started with giscoR} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} --- # Introduction *Full site with more examples and vignettes on * [**giscoR**](https://ropengov.github.io/giscoR/) is a package designed to provide a clean interaction with the [GISCO API](https://gisco-services.ec.europa.eu/distribution/v2/). Within Eurostat, GISCO is responsible for meeting the European Commission's geographical information needs at 3 levels: the European Union, its member countries, and its regions. GISCO also provides a variety of shapefiles on different formats, focusing specially in the European Union area, but providing also some worldwide shapefiles, as country polygons, labels or borders and coastal lines. GISCO provides data on different resolutions suitable for representing small areas (01M, 03M) as well as lightweight datasets specially useful for representing wider areas (10M, 20M, 60M). Shapefiles are provided on 3 different projections: EPSG 4326, 3035 or 3857. **giscoR** returns [`sf`](https://r-spatial.github.io/sf/reference/sf.html) class objects, see . # Caching **giscoR** provides a dataset caching capability, that could be set as: ``` r gisco_set_cache_dir("./path/to/location") ``` If the file is not available locally, it would be downloaded to that directory so the next time you need the corresponding data it would be loaded from the local directory. If you experience any problems on downloading, you can also manually download the file from the [GISCO API website](https://gisco-services.ec.europa.eu/distribution/v2/) and store it on your local directory. # Downloading data Please be aware that downloading provisions apply when using GISCO data: > When data downloaded from this page 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: © EuroGeographics for the administrative boundaries > - FR: © EuroGeographics pour les limites administratives > - DE: © EuroGeographics bezüglich 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. There is a function, `gisco_attributions()` that would guide you on this topic. It also provides attributions on several languages. ``` r 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" ``` # Basic example Some examples on data downloads ``` r 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" ) ) ```
Political map of Asia

Political map of Asia

You can select specific countries by name (in any language), ISO 3 codes or Eurostat codes. The only restriction is that you can't mix country names, ISO3 and Eurostat codes on one single call. It is possible also to combine different shapefiles, just set `resolution` and `epsg` (and optionally `year`) to the same value: ``` r 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) ```
Political map of North Africa

Political map of North Africa

# Thematic maps with **giscoR** This is an example on how **giscoR** can play nicely with some Eurostat data. For plotting purposes we would use the [**ggplot2**](https://CRAN.R-project.org/package=ggplot2) package however any package that handles `sf` objects (e.g. [**tmap**](https://CRAN.R-project.org/package=tmap), [**mapsf**](https://CRAN.R-project.org/package=mapsf), [**leaflet**](https://CRAN.R-project.org/package=leaflet), etc. could be used). Also [**colorspace**](https://CRAN.R-project.org/package=colorspace) and [**rcartocolor**](https://CRAN.R-project.org/package=rcartocolor) packages are recommended, as they provide great color palettes. ``` r # 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$CNTR_CODE) # Eurostat data - Disposable income pps <- get_eurostat("tgs00026") %>% filter(TIME_PERIOD == "2021-01-01") nuts2_sf <- nuts2 %>% left_join(pps, by = "geo") %>% mutate( values_th = values / 1000, categ = cut(values_th, c(0, 15, 30, 60, 90, 120, Inf)) ) #> Error in UseMethod("left_join"): no applicable method for 'left_join' applied to an object of class "NULL" # Adjust the labels labs <- levels(nuts2_sf$categ) #> Error: object 'nuts2_sf' not found labs[1] <- "< 15" #> Error in labs[1] <- "< 15": object of type 'closure' is not subsettable labs[6] <- "> 120" #> Error in labs[6] <- "> 120": object of type 'closure' is not subsettable levels(nuts2_sf$categ) <- labs #> Error: object 'nuts2_sf' not found # 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() ) ) #> Error: object 'nuts2_sf' not found ```