R Tools for Eurostat Open Data

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.


Release version (CRAN):


Development version (Github):


Overall, the eurostat package includes the following functions:

add_nuts_level          Add the statistical aggregation level to data
check_access_to_data    Check access to ec.europe.eu
clean_eurostat_cache    Clean Eurostat Cache
cut_to_classes          Cuts the Values Column into Classes and
                        Polishes the Labels
dic_order               Order of Variable Levels from Eurostat
eu_countries            Countries and Country Codes
                        Geospatial data of Europe from Gisco in 1:60
                        million scale from year 2016
eurostat-package        R Tools for Eurostat open data
eurotime2date           Date Conversion from Eurostat Time Format
eurotime2num            Conversion of Eurostat Time Format to Numeric
get_bibentry            Create A Data Bibliography
get_eurostat            Read Eurostat Data
get_eurostat_dic        Download Eurostat Dictionary
                        Download Geospatial Data from GISCO
get_eurostat_json       Get Data from Eurostat API in JSON
get_eurostat_raw        Download Data from Eurostat Database
get_eurostat_toc        Download Table of Contents of Eurostat Data
                        Harmonize Country Code
harmonize_geo_code      Harmonize NUTS region codes that changed with
                        the 'NUTS2016' definition
label_eurostat          Get Eurostat Codes
nuts_correspondence     Correspondence Table NUTS2013-NUTS2016
recode_to_nuts_2013     Recode geo labels and rename regions from
                        NUTS2016 to NUTS2013
recode_to_nuts_2016     Recode geo labels and rename regions from
                        NUTS2013 to NUTS2016
regional_changes_2016   Changes in regional boundaries
search_eurostat         Grep Datasets Titles from Eurostat
tgs00026                Auxiliary Data
evaluate <- curl::has_internet()

Finding data

Function get_eurostat_toc() downloads a table of contents of eurostat datasets. The values in column ‘code’ should be used to download a selected dataset.

# Load the package

# Get Eurostat data listing
toc <- get_eurostat_toc()

# Check the first items
title code type last update of data last table structure change data start data end values
Database by themes data folder NA NA NA NA NA
General and regional statistics general folder NA NA NA NA NA
European and national indicators for short-term analysis euroind folder NA NA NA NA NA
Business and consumer surveys (source: DG ECFIN) ei_bcs folder NA NA NA NA NA
Consumer surveys (source: DG ECFIN) ei_bcs_cs folder NA NA NA NA NA
Consumers - monthly data ei_bsco_m dataset 28.01.2021 28.01.2021 1980M01 2021M01 NA

Some of the data sets (e.g. in the ‘comext’ type) are not accessible through the standard interface. See the get_eurostat function documentation for more details.

With search_eurostat() you can search the table of contents for particular patterns, e.g. all datasets related to passenger transport. The kable function to produces nice markdown output. Note that with the type argument of this function you could restrict the search to for instance datasets or tables.

# info about passengers
kable(head(search_eurostat("passenger transport")))
title code type last update of data last table structure change data start data end values
Volume of passenger transport relative to GDP tran_hv_pstra dataset 01.09.2020 31.08.2020 1990 2018 NA
Modal split of passenger transport tran_hv_psmod dataset 01.09.2020 31.08.2020 1990 2018 NA
Air passenger transport by reporting country avia_paoc dataset 26.01.2021 26.01.2021 1993 2020Q4 NA
Air passenger transport by main airports in each reporting country avia_paoa dataset 26.01.2021 26.01.2021 1993 2020Q4 NA
Air passenger transport between reporting countries avia_paocc dataset 26.01.2021 26.01.2021 1993 2020Q4 NA
Air passenger transport between main airports in each reporting country and partner reporting countries avia_paoac dataset 26.01.2021 26.01.2021 1993 2020Q4 NA

Codes for the dataset can be searched also from the Eurostat database. The Eurostat database gives codes in the Data Navigation Tree after every dataset in parenthesis.

Downloading data

The package supports two of the Eurostats download methods: the bulk download facility and the Web Services’ JSON API. The bulk download facility is the fastest method to download whole datasets. It is also often the only way as the JSON API has limitation of maximum 50 sub-indicators at a time and whole datasets usually exceeds that. To download only a small section of the dataset the JSON API is faster, as it allows to make a data selection before downloading.

A user does not usually have to bother with methods, as both are used via main function get_eurostat(). If only the table id is given, the whole table is downloaded from the bulk download facility. If also filters are defined the JSON API is used.

Here an example of indicator ‘Modal split of passenger transport’. This is the percentage share of each mode of transport in total inland transport, expressed in passenger-kilometres (pkm) based on transport by passenger cars, buses and coaches, and trains. All data should be based on movements on national territory, regardless of the nationality of the vehicle. However, the data collection is not harmonized at the EU level.

Pick and print the id of the data set to download:

# For the original data, see
# http://ec.europa.eu/eurostat/tgm/table.do?tab=table&init=1&plugin=1&language=en&pcode=tsdtr210
id <- search_eurostat("Modal split of passenger transport", 
                         type = "table")$code[1]

[1] “t2020_rk310”

Get the whole corresponding table. As the table is annual data, it is more convient to use a numeric time variable than use the default date format:

dat <- get_eurostat(id, time_format = "num")

Investigate the structure of the downloaded data set:

## tibble [2,798 × 5] (S3: tbl_df/tbl/data.frame)
##  $ unit   : chr [1:2798] "PC" "PC" "PC" "PC" ...
##  $ vehicle: chr [1:2798] "BUS_TOT" "BUS_TOT" "BUS_TOT" "BUS_TOT" ...
##  $ geo    : chr [1:2798] "AT" "BE" "CH" "DE" ...
##  $ time   : num [1:2798] 1990 1990 1990 1990 1990 1990 1990 1990 1990 1990 ...
##  $ values : num [1:2798] 8.2 10.6 3.7 9.1 11.3 32.4 14.9 13.5 6 24.8 ...
unit vehicle geo time values
PC BUS_TOT AT 1990 8.2
PC BUS_TOT BE 1990 10.6
PC BUS_TOT CH 1990 3.7
PC BUS_TOT DE 1990 9.1
PC BUS_TOT DK 1990 11.3
PC BUS_TOT EL 1990 32.4

Or you can get only a part of the dataset by defining filters argument. It should be named list, where names corresponds to variable names (lower case) and values are vectors of codes corresponding desidered series (upper case). For time variable, in addition to a time, also a sinceTimePeriod and a lastTimePeriod can be used.

dat2 <- get_eurostat(id, filters = list(geo = c("EU28", "FI"), lastTimePeriod=1), time_format = "num")
unit vehicle geo time values
PC BUS_TOT EU28 2018 8.7
PC BUS_TOT FI 2018 10.1
PC CAR EU28 2018 83.3
PC CAR FI 2018 84.2
PC TRN EU28 2018 8.0
PC TRN FI 2018 5.7

Replacing codes with labels

By default variables are returned as Eurostat codes, but to get human-readable labels instead, use a type = "label" argument.

datl2 <- get_eurostat(id, filters = list(geo = c("EU28", "FI"), 
                                         lastTimePeriod = 1), 
                      type = "label", time_format = "num")
unit vehicle geo time values
Percentage Motor coaches, buses and trolley buses European Union - 28 countries (2013-2020) 2018 8.7
Percentage Motor coaches, buses and trolley buses Finland 2018 10.1
Percentage Passenger cars European Union - 28 countries (2013-2020) 2018 83.3
Percentage Passenger cars Finland 2018 84.2
Percentage Trains European Union - 28 countries (2013-2020) 2018 8.0
Percentage Trains Finland 2018 5.7

Eurostat codes in the downloaded data set can be replaced with human-readable labels from the Eurostat dictionaries with the label_eurostat() function.

datl <- label_eurostat(dat)
unit vehicle geo time values
Percentage Motor coaches, buses and trolley buses Austria 1990 8.2
Percentage Motor coaches, buses and trolley buses Belgium 1990 10.6
Percentage Motor coaches, buses and trolley buses Switzerland 1990 3.7
Percentage Motor coaches, buses and trolley buses Germany (until 1990 former territory of the FRG) 1990 9.1
Percentage Motor coaches, buses and trolley buses Denmark 1990 11.3
Percentage Motor coaches, buses and trolley buses Greece 1990 32.4

The label_eurostat() allows conversion of individual variable vectors or variable names as well.

## [1] "Unit of measure"                 "Vehicles"                       
## [3] "Geopolitical entity (reporting)" "Period of time"

Vehicle information has 3 levels. You can check them now with:


Selecting and modifying data

EFTA, Eurozone, EU and EU candidate countries

To facilitate smooth visualization of standard European geographic areas, the package provides ready-made lists of the country codes used in the eurostat database for EFTA (efta_countries), Euro area (ea_countries), EU (eu_countries) and EU candidate countries (eu_candidate_countries). These can be used to select specific groups of countries for closer investigation. For conversions with other standard country coding systems, see the countrycode R package. To retrieve the country code list for EFTA, for instance, use:

code name label
IS Iceland Iceland
LI Liechtenstein Liechtenstein
NO Norway Norway
CH Switzerland Switzerland

EU data from 2012 in all vehicles:

dat_eu12 <- subset(datl, geo == "European Union - 28 countries" & time == 2012)
kable(dat_eu12, row.names = FALSE)
unit vehicle geo time values

EU data from 2000 - 2012 with vehicle types as variables:

Reshaping the data is best done with spread() in tidyr.

dat_eu_0012 <- subset(dat, geo == "EU28" & time %in% 2000:2012)
dat_eu_0012_wide <- spread(dat_eu_0012, vehicle, values)
kable(subset(dat_eu_0012_wide, select = -geo), row.names = FALSE)
unit time BUS_TOT CAR TRN
PC 2000 10.4 82.5 7.1
PC 2001 10.2 82.8 7.0
PC 2002 9.8 83.4 6.8
PC 2003 9.8 83.6 6.6
PC 2004 9.7 83.5 6.7
PC 2005 9.8 83.4 6.9
PC 2006 9.6 83.4 7.0
PC 2007 9.8 83.1 7.1
PC 2008 9.8 82.9 7.4
PC 2009 9.2 83.7 7.1
PC 2010 9.3 83.5 7.2
PC 2011 9.4 83.2 7.4
PC 2012 9.4 82.9 7.7

Train passengers for selected EU countries in 2000 - 2012

dat_trains <- subset(datl, geo %in% c("Austria", "Belgium", "Finland", "Sweden")
                   & time %in% 2000:2012 
                   & vehicle == "Trains") 
dat_trains_wide <- spread(dat_trains, geo, values) 
kable(subset(dat_trains_wide, select = -vehicle), row.names = FALSE)
unit time Austria Belgium Finland Sweden
Percentage 2000 9.8 6.3 5.1 6.9
Percentage 2001 9.8 6.4 4.8 7.3
Percentage 2002 9.7 6.5 4.8 7.2
Percentage 2003 9.6 6.5 4.7 7.1
Percentage 2004 9.5 7.1 4.7 6.9
Percentage 2005 9.8 6.6 4.8 7.1
Percentage 2006 10.0 6.9 4.8 7.7
Percentage 2007 10.1 7.1 5.0 8.0
Percentage 2008 11.1 7.5 5.4 8.7
Percentage 2009 11.2 7.5 5.1 8.8
Percentage 2010 11.1 7.7 5.2 8.7
Percentage 2011 11.5 7.7 5.0 8.7
Percentage 2012 11.9 7.8 5.3 9.1


Eurostat data is available also in the Statistical Data and Metadata eXchange (SDMX) Web Services. Our eurostat R package does not provide custom tools for this but the following generic R packages provide access to eurostat SDMX version:

Further examples

For further examples, see the package homepage.

Version info

This tutorial was created with

## R version 4.0.3 (2020-10-10)
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##  [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
##  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## other attached packages:
## [1] tidyr_1.1.2    rvest_0.3.6    xml2_1.3.2     eurostat_3.7.1 knitr_1.31    
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