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https://github.com/ropengov/giscor
Download geospatial data from GISCO API - Eurostat
https://github.com/ropengov/giscor
api-wrapper cran eurostat eurostat-data ggplot2 gis gisco r r-package ropengov rstats spatial thematic-maps
Last synced: 3 days ago
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Download geospatial data from GISCO API - Eurostat
- Host: GitHub
- URL: https://github.com/ropengov/giscor
- Owner: rOpenGov
- License: gpl-3.0
- Created: 2020-09-23T19:40:44.000Z (over 4 years ago)
- Default Branch: main
- Last Pushed: 2024-10-15T06:36:07.000Z (3 months ago)
- Last Synced: 2024-10-29T22:31:51.751Z (3 months ago)
- Topics: api-wrapper, cran, eurostat, eurostat-data, ggplot2, gis, gisco, r, r-package, ropengov, rstats, spatial, thematic-maps
- Language: R
- Homepage: https://ropengov.github.io/giscoR/
- Size: 121 MB
- Stars: 72
- Watchers: 4
- Forks: 1
- Open Issues: 3
-
Metadata Files:
- Readme: README.Rmd
- Changelog: NEWS.md
- Contributing: CONTRIBUTING.md
- Funding: .github/FUNDING.yml
- License: LICENSE
- Citation: CITATION.cff
- Codemeta: codemeta.json
Awesome Lists containing this project
README
---
output: github_document
bibliography: inst/REFERENCES.bib
link-citations: yes
---
```{r, include = FALSE}
knitr::opts_knit$set(
progress = TRUE,
base.url = "https://raw.githubusercontent.com/ropengov/giscoR/main/"
)
knitr::opts_chunk$set(
collapse = TRUE,
tidy = "styler",
comment = "#>",
fig.path = "img/README-",
warning = FALSE,
message = FALSE,
dev = "ragg_png",
dpi = 300,
out.width = "100%"
)
```
# giscoR 
[](https://ropengov.org/)
[](https://CRAN.R-project.org/package=giscoR)
[](https://cran.r-project.org/web/checks/check_results_giscoR.html)
[](https://CRAN.R-project.org/package=giscoR)
[](https://ropengov.r-universe.dev/giscoR)
[](https://github.com/rOpenGov/giscoR/actions/workflows/check-full.yaml)
[](https://github.com/rOpenGov/giscoR/actions/workflows/rhub.yaml)
[](https://app.codecov.io/gh/ropengov/giscoR)
[](https://www.codefactor.io/repository/github/ropengov/giscor)
[](https://doi.org/10.32614/CRAN.package.giscoR)
[](https://www.repostatus.org/#active)
[**giscoR**](https://ropengov.github.io/giscoR//) is an API package that helps
to retrieve data from [Eurostat - GISCO (the Geographic Information System of
the COmmission)](https://ec.europa.eu/eurostat/web/gisco). It also provides some
lightweight data sets ready to use without downloading.
[GISCO](https://ec.europa.eu/eurostat/web/gisco) is a geospatial open data
repository including several data sets as countries, coastal lines, labels or
[NUTS levels](https://ec.europa.eu/eurostat/web/regions-and-cities/overview).
The data sets are usually provided at several resolution levels
(60M/20M/10M/03M/01M) and in 3 different projections (4326/3035/3857).
Note that the package does not provide metadata on the downloaded files, the
information is available on the [API
webpage](https://gisco-services.ec.europa.eu/distribution/v2/).
Full site with examples and vignettes on
## Installation
Install **giscoR** from [**CRAN**](https://CRAN.R-project.org/package=giscoR):
```{r, eval=FALSE}
install.packages("giscoR")
```
You can install the developing version of **giscoR** with:
```{r, eval=FALSE}
remotes::install_github("rOpenGov/giscoR")
```
Alternatively, you can install **giscoR** using the
[r-universe](https://ropengov.r-universe.dev/giscoR):
```{r, eval=FALSE}
install.packages("giscoR",
repos = c("https://ropengov.r-universe.dev", "https://cloud.r-project.org")
)
```
## Usage
```{r echo=FALSE, results='asis'}
v <- packageVersion("giscoR")
l <- unlist(strsplit(as.character(v), ".", fixed = TRUE))
if (length(l) == 4) {
cat(
"You can have a look to the documentation of",
"the dev version in "
)
}
```
This script highlights some features of **giscoR** :
```{r example}
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")]
)
```
### Labels
An example of a labeled map using **ggplot2**:
```{r labels, fig.height=7, fig.width=6}
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())
```
### Thematic maps
An example of a thematic map plotted with the **ggplot2** package. The
information is extracted via the **eurostat** package [@RJ-2017-019]. We would
follow the fantastic approach presented by [Milos
Popovic](https://milospopovic.net/) on [this
post](https://milospopovic.net/how-to-make-choropleth-map-in-r/):
We start by extracting the corresponding geographic data:
```{r euroex, fig.asp=1.1}
# 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")
```
We now download the data from Eurostat:
```{r}
# Use eurostat
library(eurostat)
popdens <- get_eurostat("demo_r_d3dens") %>%
filter(TIME_PERIOD == "2021-01-01")
```
By last, we merge and manipulate the data for creating the final plot:
```{r thematic, fig.asp=1.1}
# 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/"
)
)
```
## A note on caching
Some data sets (as Local Administrative Units - LAU, or high-resolution files)
may have a size larger than 50MB. You can use **giscoR** to create your own
local repository at a given local directory passing the following function:
```{r, eval=FALSE}
gisco_set_cache_dir("./path/to/location")
```
You can also download manually the files (`.geojson` format) and store them on
your local directory.
## Recommended packages
### API data packages
- **eurostat** [@RJ-2017-019]: This is an API package that provides access to
open data from Eurostat.
### Plotting **sf** objects
Some packages recommended for visualization are:
- [**tmap**](https://r-tmap.github.io/tmap/)
- [**ggplot2**](https://github.com/tidyverse/ggplot2) +
[**ggspatial**](https://github.com/paleolimbot/ggspatial) +
[**tidyterra**](https://dieghernan.github.io/tidyterra/)
- [**mapsf**](https://riatelab.github.io/mapsf/)
- [**leaflet**](https://rstudio.github.io/leaflet/)
## Contribute
Check the GitHub page for [source code](https://github.com/rOpenGov/giscoR/).
Contributions are very welcome:
- [Use issue tracker](https://github.com/rOpenGov/giscoR/issues) for feedback
and bug reports.
- [Send pull requests](https://github.com/rOpenGov/giscoR/)
- [Star us on the GitHub page](https://github.com/rOpenGov/giscoR)
## Citation
```{r echo=FALSE, results='asis'}
print(citation("giscoR"), bibtex = FALSE)
```
A BibTeX entry for LaTeX users is
```{r echo=FALSE, comment=""}
toBibtex(citation("giscoR"))
```
## Copyright notice
> 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](https://eurogeographics.org/maps-for-europe/licensing/) for
> information regarding their licence agreements.
>
> *From [GISCO
> Web](https://ec.europa.eu/eurostat/web/gisco/geodata/statistical-units)*
## Disclaimer
This package is in no way officially related to or endorsed by Eurostat.
## References