R Tools for Eurostat Open Data: maps
This rOpenGov R package provides tools to access Eurostat database, which you can also browse on-line for the data sets and documentation. For contact information and source code, see the package website.
See the vignette of eurostat
(vignette(package = "eurostat")) for installation and basic
use.
Maps
NOTE: we recommend to check also the
giscoRpackage (https://dieghernan.github.io/giscoR/). This is another API package that provides R tools for Eurostat geographic data to support geospatial analysis and visualization.
Disposable income of private households by NUTS 2 regions at 1:60mln resolution using tmap
The mapping examples below use tmap
package.
library(dplyr)
#>
#> 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
library(eurostat)
library(sf)
#> Linking to GEOS 3.10.2, GDAL 3.4.1, PROJ 8.2.1; sf_use_s2() is TRUE
library(tmap)
#> Breaking News: tmap 3.x is retiring. Please test v4, e.g. with
#> remotes::install_github('r-tmap/tmap')
# Download attribute data from Eurostat
sp_data <- eurostat::get_eurostat("tgs00026", time_format = "raw") %>%
# subset to have only a single row per geo
filter(TIME_PERIOD == 2016, nchar(geo) == 4) %>%
# categorise
mutate(income = cut_to_classes(values, n = 5))
#> Table tgs00026 cached at /tmp/RtmpvrJG9l/eurostat/dd151caf327bc5e9efad11fc2015a64c.rds
# Download geospatial data from GISCO
geodata <- get_eurostat_geospatial(nuts_level = 2, year = 2016)
#> Extracting data from eurostat::eurostat_geodata_60_2016
# merge with attribute data with geodata
map_data <- inner_join(geodata, sp_data, by = "geo")Construct the map
# Create and plot the map
map1 <- tm_shape(geodata,
projection = "EPSG:3035",
xlim = c(2400000, 7800000),
ylim = c(1320000, 5650000)
) +
tm_fill("lightgrey") +
tm_shape(map_data) +
tm_polygons("income",
title = "Disposable household\nincomes in 2016",
palette = "Oranges"
)
print(map1)
Interactive maps can be generated as well
# Interactive
tmap_mode("view")
#> tmap mode set to interactive viewing
map1
Disposable income of private households by NUTS 2 regions in Poland with labels at 1:1mln resolution using tmap
library(eurostat)
library(dplyr)
library(sf)
# Downloading and manipulating the tabular data
print("Let us focus on year 2016 and NUTS-3 level")
#> [1] "Let us focus on year 2016 and NUTS-3 level"
euro_sf2 <- get_eurostat("tgs00026",
time_format = "raw",
filter = list(time = "2016")
) %>%
# Subset to NUTS-3 level
dplyr::filter(grepl("PL", geo)) %>%
# label the single geo column
mutate(
label = paste0(label_eurostat(.)[["geo"]], "\n", values, "€"),
income = cut_to_classes(values)
)
#> Table tgs00026 cached at /tmp/RtmpvrJG9l/eurostat/00652b88d07b75dcb8117aafbabcd39b.rds
print("Download geospatial data from GISCO")
#> [1] "Download geospatial data from GISCO"
geodata <- get_eurostat_geospatial(
resolution = "01", nuts_level = 2,
year = 2016, country = "PL"
)
#> Loading required namespace: giscoR
#> Extracting data using giscoR package, please report issues on https://github.com/rOpenGov/giscoR/issues
# Merge with attribute data with geodata
map_data <- inner_join(geodata, euro_sf2, by = "geo")
# plot map
library(tmap)
map2 <- tm_shape(geodata) +
tm_fill("lightgrey") +
tm_shape(map_data, is.master = TRUE) +
tm_polygons("income",
title = "Disposable household incomes in 2014",
palette = "Oranges", border.col = "white"
) +
tm_text("NUTS_NAME", just = "center") +
tm_scale_bar() +
tm_layout(legend.outside = TRUE)
map2
Disposable income of private households by NUTS 2 regions at 1:10mln resolution using ggplot2
# Disposable income of private households by NUTS 2 regions at 1:1mln res
library(eurostat)
library(dplyr)
library(ggplot2)
data_eurostat <- get_eurostat("tgs00026", time_format = "raw") %>%
filter(TIME_PERIOD == 2018, nchar(geo) == 4) %>%
# classifying the values the variable
dplyr::mutate(cat = cut_to_classes(values))
#> Dataset query already saved in cache_list.json...
#> Reading cache file /tmp/RtmpvrJG9l/eurostat/dd151caf327bc5e9efad11fc2015a64c.rds
#> Table tgs00026 read from cache file: /tmp/RtmpvrJG9l/eurostat/dd151caf327bc5e9efad11fc2015a64c.rds
# Download geospatial data from GISCO
data_geo <- get_eurostat_geospatial(
resolution = "01", nuts_level = "2",
year = 2016
)
#> Extracting data using giscoR package, please report issues on https://github.com/rOpenGov/giscoR/issues
# merge with attribute data with geodata
data <- left_join(data_geo, data_eurostat, by = "geo")
ggplot(data) +
# Base layer
geom_sf(fill = "lightgrey", color = "lightgrey") +
# Choropleth layer
geom_sf(aes(fill = cat), color = "lightgrey", linewidth = 0.1, na.rm = TRUE) +
scale_fill_brewer(palette = "Oranges", na.translate = FALSE) +
guides(fill = guide_legend(reverse = TRUE, title = "euro")) +
labs(
title = "Disposable household income in 2018",
caption = "© EuroGeographics for the administrative boundaries
Map produced in R with data from Eurostat-package http://ropengov.github.io/eurostat"
) +
theme_light() +
coord_sf(
xlim = c(2377294, 7453440),
ylim = c(1313597, 5628510),
crs = 3035
)
Citations and related work
Citing the data sources
Eurostat data: cite Eurostat.
Administrative boundaries: cite EuroGeographics
Citing the eurostat R package
For main developers and contributors, see the package homepage.
This work can be freely used, modified and distributed under the BSD-2-clause (modified FreeBSD) license:
citation("eurostat")
#> Kindly cite the eurostat R package as follows:
#>
#> Lahti L., Huovari J., Kainu M., and Biecek P. (2017). Retrieval and
#> analysis of Eurostat open data with the eurostat package. The R
#> Journal 9(1), pp. 385-392. doi: 10.32614/RJ-2017-019
#>
#> Lahti, L., Huovari J., Kainu M., Biecek P., Hernangomez D., Antal D.,
#> and Kantanen P. (2023). eurostat: Tools for Eurostat Open Data
#> [Computer software]. R package version 4.0.0.
#> https://github.com/rOpenGov/eurostat
#>
#> To see these entries in BibTeX format, use 'print(<citation>,
#> bibtex=TRUE)', 'toBibtex(.)', or set
#> 'options(citation.bibtex.max=999)'.Contact
For contact information, see the package homepage.
Version info
This tutorial was created with
sessioninfo::session_info()
#> ─ Session info ───────────────────────────────────────────────────────────────
#> setting value
#> version R version 4.3.3 (2024-02-29)
#> os Ubuntu 22.04.4 LTS
#> system x86_64, linux-gnu
#> ui X11
#> language en
#> collate C.UTF-8
#> ctype C.UTF-8
#> tz UTC
#> date 2024-04-11
#> pandoc 3.1.11 @ /opt/hostedtoolcache/pandoc/3.1.11/x64/ (via rmarkdown)
#>
#> ─ Packages ───────────────────────────────────────────────────────────────────
#> package * version date (UTC) lib source
#> abind 1.4-5 2016-07-21 [1] RSPM
#> assertthat 0.2.1 2019-03-21 [1] RSPM
#> backports 1.4.1 2021-12-13 [1] RSPM
#> base64enc 0.1-3 2015-07-28 [1] RSPM
#> bibtex 0.5.1 2023-01-26 [1] RSPM
#> bit 4.0.5 2022-11-15 [1] RSPM
#> bit64 4.0.5 2020-08-30 [1] RSPM
#> bslib 0.7.0 2024-03-29 [1] RSPM
#> cachem 1.0.8 2023-05-01 [1] RSPM
#> cellranger 1.1.0 2016-07-27 [1] RSPM
#> class 7.3-22 2023-05-03 [3] CRAN (R 4.3.3)
#> classInt 0.4-10 2023-09-05 [1] RSPM
#> cli 3.6.2 2023-12-11 [1] RSPM
#> codetools 0.2-19 2023-02-01 [3] CRAN (R 4.3.3)
#> colorspace 2.1-0 2023-01-23 [1] RSPM
#> countrycode 1.6.0 2024-03-22 [1] RSPM
#> crayon 1.5.2 2022-09-29 [1] RSPM
#> crosstalk 1.2.1 2023-11-23 [1] RSPM
#> curl 5.2.1 2024-03-01 [1] RSPM
#> data.table 1.15.4 2024-03-30 [1] RSPM
#> DBI 1.2.2 2024-02-16 [1] RSPM
#> desc 1.4.3 2023-12-10 [1] RSPM
#> dichromat 2.0-0.1 2022-05-02 [1] RSPM
#> digest 0.6.35 2024-03-11 [1] RSPM
#> dplyr * 1.1.4 2023-11-17 [1] RSPM
#> e1071 1.7-14 2023-12-06 [1] RSPM
#> eurostat * 4.0.0 2024-04-11 [1] local
#> evaluate 0.23 2023-11-01 [1] RSPM
#> fansi 1.0.6 2023-12-08 [1] RSPM
#> farver 2.1.1 2022-07-06 [1] RSPM
#> fastmap 1.1.1 2023-02-24 [1] RSPM
#> fs 1.6.3 2023-07-20 [1] RSPM
#> generics 0.1.3 2022-07-05 [1] RSPM
#> geojsonsf 2.0.3 2022-05-30 [1] RSPM
#> ggplot2 * 3.5.0 2024-02-23 [1] RSPM
#> giscoR 0.4.2 2024-03-27 [1] RSPM
#> glue 1.7.0 2024-01-09 [1] RSPM
#> gtable 0.3.4 2023-08-21 [1] RSPM
#> here 1.0.1 2020-12-13 [1] RSPM
#> highr 0.10 2022-12-22 [1] RSPM
#> hms 1.1.3 2023-03-21 [1] RSPM
#> htmltools 0.5.8.1 2024-04-04 [1] RSPM
#> htmlwidgets 1.6.4 2023-12-06 [1] RSPM
#> httr 1.4.7 2023-08-15 [1] RSPM
#> httr2 1.0.1 2024-04-01 [1] RSPM
#> ISOweek 0.6-2 2011-09-07 [1] RSPM
#> jquerylib 0.1.4 2021-04-26 [1] RSPM
#> jsonlite 1.8.8 2023-12-04 [1] RSPM
#> KernSmooth 2.23-22 2023-07-10 [3] CRAN (R 4.3.3)
#> knitr 1.46 2024-04-06 [1] RSPM
#> lattice 0.22-5 2023-10-24 [3] CRAN (R 4.3.3)
#> leafem 0.2.3 2023-09-17 [1] RSPM
#> leaflet 2.2.2 2024-03-26 [1] RSPM
#> leaflet.providers 2.0.0 2023-10-17 [1] RSPM
#> leafsync 0.1.0 2019-03-05 [1] RSPM
#> lifecycle 1.0.4 2023-11-07 [1] RSPM
#> lubridate 1.9.3 2023-09-27 [1] RSPM
#> lwgeom 0.2-14 2024-02-21 [1] RSPM
#> magrittr 2.0.3 2022-03-30 [1] RSPM
#> memoise 2.0.1 2021-11-26 [1] RSPM
#> munsell 0.5.1 2024-04-01 [1] RSPM
#> pillar 1.9.0 2023-03-22 [1] RSPM
#> pkgconfig 2.0.3 2019-09-22 [1] RSPM
#> pkgdown 2.0.7 2022-12-14 [1] any (@2.0.7)
#> plyr 1.8.9 2023-10-02 [1] RSPM
#> png 0.1-8 2022-11-29 [1] RSPM
#> proxy 0.4-27 2022-06-09 [1] RSPM
#> purrr 1.0.2 2023-08-10 [1] RSPM
#> R.cache 0.16.0 2022-07-21 [1] RSPM
#> R.methodsS3 1.8.2 2022-06-13 [1] RSPM
#> R.oo 1.26.0 2024-01-24 [1] RSPM
#> R.utils 2.12.3 2023-11-18 [1] RSPM
#> R6 2.5.1 2021-08-19 [1] RSPM
#> ragg 1.3.0 2024-03-13 [1] RSPM
#> rappdirs 0.3.3 2021-01-31 [1] RSPM
#> raster 3.6-26 2023-10-14 [1] RSPM
#> RColorBrewer 1.1-3 2022-04-03 [1] RSPM
#> Rcpp 1.0.12 2024-01-09 [1] RSPM
#> readr 2.1.5 2024-01-10 [1] RSPM
#> readxl 1.4.3 2023-07-06 [1] RSPM
#> RefManageR 1.4.0 2022-09-30 [1] RSPM
#> regions 0.1.8 2021-06-21 [1] RSPM
#> rlang 1.1.3 2024-01-10 [1] RSPM
#> rmarkdown 2.26 2024-03-05 [1] RSPM
#> rprojroot 2.0.4 2023-11-05 [1] RSPM
#> s2 1.1.6 2023-12-19 [1] RSPM
#> sass 0.4.9 2024-03-15 [1] RSPM
#> scales 1.3.0 2023-11-28 [1] RSPM
#> sessioninfo 1.2.2 2021-12-06 [1] any (@1.2.2)
#> sf * 1.0-16 2024-03-24 [1] RSPM
#> sp 2.1-3 2024-01-30 [1] RSPM
#> stars 0.6-5 2024-04-04 [1] RSPM
#> stringi 1.8.3 2023-12-11 [1] RSPM
#> stringr 1.5.1 2023-11-14 [1] RSPM
#> styler 1.10.3 2024-04-07 [1] RSPM
#> systemfonts 1.0.6 2024-03-07 [1] RSPM
#> terra 1.7-71 2024-01-31 [1] RSPM
#> textshaping 0.3.7 2023-10-09 [1] RSPM
#> tibble 3.2.1 2023-03-20 [1] RSPM
#> tidyr 1.3.1 2024-01-24 [1] RSPM
#> tidyselect 1.2.1 2024-03-11 [1] RSPM
#> timechange 0.3.0 2024-01-18 [1] RSPM
#> tmap * 3.3-4 2023-09-12 [1] RSPM
#> tmaptools 3.1-1 2021-01-19 [1] RSPM
#> tzdb 0.4.0 2023-05-12 [1] RSPM
#> units 0.8-5 2023-11-28 [1] RSPM
#> utf8 1.2.4 2023-10-22 [1] RSPM
#> vctrs 0.6.5 2023-12-01 [1] RSPM
#> viridisLite 0.4.2 2023-05-02 [1] RSPM
#> vroom 1.6.5 2023-12-05 [1] RSPM
#> withr 3.0.0 2024-01-16 [1] RSPM
#> wk 0.9.1 2023-11-29 [1] RSPM
#> xfun 0.43 2024-03-25 [1] RSPM
#> XML 3.99-0.16.1 2024-01-22 [1] RSPM
#> xml2 1.3.6 2023-12-04 [1] RSPM
#> yaml 2.3.8 2023-12-11 [1] RSPM
#>
#> [1] /home/runner/work/_temp/Library
#> [2] /opt/R/4.3.3/lib/R/site-library
#> [3] /opt/R/4.3.3/lib/R/library
#>
#> ──────────────────────────────────────────────────────────────────────────────