From 8c5e315d9993bd251df56f13bce4dbb73c7e2735 Mon Sep 17 00:00:00 2001 From: Diego H Date: Thu, 28 Nov 2024 17:13:26 +0100 Subject: [PATCH] Update docs --- CITATION.cff | 3 - DESCRIPTION | 3 +- README.md | 1 + codemeta.json | 2 +- img/README-example-1.png | Bin 114303 -> 266881 bytes img/README-example-2.png | Bin 102290 -> 255686 bytes img/README-labels-1.png | Bin 81178 -> 194008 bytes img/README-thematic-1.png | Bin 246127 -> 702102 bytes vignettes/giscoR.Rmd | 515 +++++++++++++++++++------------------- 9 files changed, 262 insertions(+), 262 deletions(-) diff --git a/CITATION.cff b/CITATION.cff index 769aea60..6ea09acc 100644 --- a/CITATION.cff +++ b/CITATION.cff @@ -114,9 +114,6 @@ references: email: jeroenooms@gmail.com orcid: https://orcid.org/0000-0002-4035-0289 year: '2024' - identifiers: - - type: url - value: https://arxiv.org/abs/1403.2805 doi: 10.32614/CRAN.package.jsonlite - type: software title: rappdirs diff --git a/DESCRIPTION b/DESCRIPTION index d377d0b0..48cd314b 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -52,4 +52,5 @@ RoxygenNote: 7.3.2 X-schema.org-applicationCategory: cartography X-schema.org-isPartOf: http://ropengov.org/ X-schema.org-keywords: ropengov, r, spatial, api-wrapper, rstats, - r-package, eurostat, gisco, thematic-maps, eurostat-data + r-package, eurostat, gisco, thematic-maps, eurostat-data, cran, + ggplot2, gis diff --git a/README.md b/README.md index ecf00c8e..5c122282 100644 --- a/README.md +++ b/README.md @@ -183,6 +183,7 @@ We now download the data from Eurostat: library(eurostat) popdens <- get_eurostat("demo_r_d3dens") %>% filter(TIME_PERIOD == "2021-01-01") +#> indexed 0B in 0s, 0B/sindexed 2.15GB in 0s, 2.15GB/s ``` By last, we merge and manipulate the data for creating the final plot: diff --git a/codemeta.json b/codemeta.json index bc421327..6296e48e 100644 --- a/codemeta.json +++ b/codemeta.json @@ -240,7 +240,7 @@ "applicationCategory": "cartography", "isPartOf": "http://ropengov.org/", "keywords": ["ropengov", 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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$CNTR_CODE) - -# Eurostat data - Disposable income -pps <- get_eurostat("tgs00026") %>% - filter(TIME_PERIOD == "2021-01-01") - -nuts2_sf <- nuts2 %>% - left_join(pps, by = "geo") %>% - mutate( - values_th = values / 1000, - categ = cut(values_th, c(0, 15, 30, 60, 90, 120, Inf)) - ) - - -# Adjust the labels -labs <- levels(nuts2_sf$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() - ) - ) -``` - -
    -Disposable income of private households by NUTS 2 regions (2021) -

    Disposable income of private households by NUTS 2 regions (2021)

    -
    +--- +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$CNTR_CODE) + +# Eurostat data - Disposable income +pps <- get_eurostat("tgs00026") %>% + filter(TIME_PERIOD == "2021-01-01") +#> indexed 0B in 0s, 0B/s indexed 2.15GB in 0s, 2.15GB/s + +nuts2_sf <- nuts2 %>% + left_join(pps, by = "geo") %>% + mutate( + values_th = values / 1000, + categ = cut(values_th, c(0, 15, 30, 60, 90, 120, Inf)) + ) + + +# Adjust the labels +labs <- levels(nuts2_sf$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() + ) + ) +``` + +
    +Disposable income of private households by NUTS 2 regions (2021) +

    Disposable income of private households by NUTS 2 regions (2021)

    +

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