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Retrieve data from Eurostat API in JSON format.


  filters = NULL,
  type = "code",
  lang = "en",
  stringsAsFactors = FALSE,
  proxy = FALSE,



A unique identifier / code for the dataset of interest. If code is not known search_eurostat() function can be used to search Eurostat table of contents.


A named list of filters. Names of list objects are Eurostat variable codes and values are vectors of observation codes. If NULL (default) the whole dataset is returned. See details for more information on filters and limitations per query.


A type of variables, "code" (default), "label" or "both". The parameter "both" will return a data_frame with named vectors, labels as values and codes as names.


2-letter language code, default is "en" (English), other options are "fr" (French) and "de" (German). Used for labeling datasets.


if TRUE (the default) variables are converted to factors in the original Eurostat order. If FALSE they are returned as strings.


Use proxy, TRUE or FALSE (default).


Arguments passed on to httr2::req_proxy


A request.


Location of proxy.


Login details for proxy, if needed.


Type of HTTP authentication to use. Should be one of the following: basic, digest, digest_ie, gssnegotiate, ntlm, any.


A dataset as an object of data.frame class.


Data to retrieve from The Eurostat Web Services can be specified with filters. Normally, it is better to use JSON query through get_eurostat(), than to use get_eurostat_json() directly.

Queries are limited to 50 sub-indicators at a time. A time can be filtered with fixed "time" filter or with "sinceTimePeriod" and "lastTimePeriod" filters. A sinceTimePeriod = 2000 returns observations from 2000 to a last available. A lastTimePeriod = 10 returns a 10 last observations. See "Filtering datasets" section below for more detailed information about filters.

To use a proxy to connect, proxy arguments can be passed to httr2::req_perform() via httr2::req_proxy() - see latter function documentation for parameter names that can be passed with .... A non-functional example: get_eurostat_json(id, filters, proxy = TRUE, url = "", port = 80).

When retrieving data from Eurostat JSON API the user may encounter errors. For end user convenience, we have provided a ready-made internal dataset sdmx_http_errors that contains descriptive labels and descriptions about the possible interpretation or cause of each error. These messages are returned if the API returns a status indicating a HTTP error (400 or greater).

The Eurostat implementation seems to be based on SDMX 2.1, which is the reason we've used SDMX Standards guidelines as a supplementary source that we have included in the dataset. What this means in practice is that the dataset contains error codes and their mappings that are not mentioned in the Eurostat website. We hope you never encounter them.

Data source: Eurostat API Statistics (JSON API)

Data is downloaded from Eurostat API Statistics. See Eurostat documentation for more information about data queries in API Statistics

This replaces the old JSON Web Services that was used by Eurostat before February 2023 and by the eurostat R package versions before 3.7.13. See Eurostat documentation about the migration from JSON web service to API Statistics for more information about the differences between the old and the new service:

For easily viewing which filtering options are available - in addition to the default ones, time and language - Eurostat Web services Query builder tool may be useful:

Filtering datasets

When using Eurostat API Statistics (JSON API), datasets can be filtered before they are downloaded and saved in local memory. The general format for filter parameters is <DIMENSION_CODE>=<VALUE>.

Filter parameters are optional but the used dimension codes must be present in the data product that is being queried. Dimension codes can vary between different data products so it may be useful to examine new datasets in Eurostat data browser beforehand. However, most if not all Eurostat datasets concern European countries and contain information that was gathered at some point in time, so geo and time dimension codes can usually be used.

<DIMENSION_CODE> and <VALUE> are case-insensitive and they can be written in lowercase or uppercase in the query.

Parameters are passed onto the eurostat package functions get_eurostat() and get_eurostat_json() as a list item. If an individual item contains multiple items, as it often can be in the case of geo parameters and other optional items, they must be in the form of a vector: c("FI", "SE"). For examples on how to use these parameters, see function examples below.

Time parameters

time and time_period address the same TIME_PERIOD dimension in the dataset and can be used interchangeably. In the Eurostat documentation it is stated that "Using more than one Time parameter in the same query is not accepted", but practice has shown that actually Eurostat API allows multiple time parameters in the same query. This makes it possible to use R colon operator when writing queries, so time = c(2015:2018) translates to &time=2015&time=2016&time=2017&time=2018.

The only exception to this is when the queried dataset contains e.g. quarterly data and TIME_PERIOD is saved as 2015-Q1, 2015-Q2 etc. Then it is possible to use time=2015-Q1&time=2015-Q2 style in the query URL, but this makes it unfeasible to use the colon operator and requires a lot of manual typing.

Because of this, it is useful to know about other time parameters as well:

  • untilTimePeriod: return dataset items from the oldest record up until the set time, for example "all data until 2000": untilTimePeriod = 2000

  • sinceTimePeriod: return dataset items starting from set time, for example "all datastarting from 2008": sinceTimePeriod = 2008

  • lastTimePeriod: starting from the most recent time period, how many preceding time periods should be returned? For example 10 most recent observations: lastTimePeriod = 10

Using both untilTimePeriod and sinceTimePeriod parameters in the same query is allowed, making the usage of the R colon operator unnecessary. In the case of quarterly data, using untilTimePeriod and sinceTimePeriod parameters also works, as opposed to the colon operator, so it is generally safer to use them as well.

Other dimensions

In get_eurostat_json() examples nama_10_gdp dataset is filtered with two additional filter parameters:

  • na_item = "B1GQ"

  • unit = "CLV_I10"

Filters like these are most likely unique to the nama_10_gdp dataset (or other datasets within the same domain) and should not be used with others dataset without user discretion. By using label_eurostat() we know that "B1GQ" stands for "Gross domestic product at market prices" and "CLV_I10" means "Chain linked volumes, index 2010=100".

Different dimension codes can be translated to a natural language by using the get_eurostat_dic() function, which returns labels for individual dimension items such as na_item and unit, as opposed to label_eurostat() which does it for whole datasets. For example, the parameter na_item stands for "National accounts indicator (ESA 2010)" and unit stands for "Unit of measure".


All datasets have metadata available in English, French and German. If no parameter is given, the labels are returned in English.


  • lang = "fr"

More information

For more information about data filtering see Eurostat documentation on API Statistics:

The following copyright notice is provided for end user convenience. Please check up-to-date copyright information from the eurostat website:

"(c) European Union, 1995 - today

Eurostat has a policy of encouraging free re-use of its data, both for non-commercial and commercial purposes. All statistical data, metadata, content of web pages or other dissemination tools, official publications and other documents published on its website, with the exceptions listed below, can be reused without any payment or written licence provided that:

  • the source is indicated as Eurostat;

  • when re-use involves modifications to the data or text, this must be stated clearly to the end user of the information."

For exceptions to the abovementioned principles see Eurostat website

Citing Eurostat data

For citing datasets, use get_bibentry() to build a bibliography that is suitable for your reference manager of choice.

When using Eurostat data in other contexts than academic publications that in-text citations or footnotes/endnotes, the following guidelines may be helpful:

  • The origin of the data should always be mentioned as "Source: Eurostat".

  • The online dataset codes(s) should also be provided in order to ensure transparency and facilitate access to the Eurostat data and related methodological information. For example: "Source: Eurostat (online data code: namq_10_gdp)"

  • Online publications (e.g. web pages, PDF) should include a clickable link to the dataset using the bookmark functionality available in the Eurostat data browser.

It should be avoided to associate different entities (e.g. Eurostat, National Statistical Offices, other data providers) to the same dataset or indicator without specifying the role of each of them in the treatment of data.

See also section "Eurostat: Copyright notice and free re-use of data" in get_eurostat() documentation.

Disclaimer: Availability of filtering functionalities

Currently it only possible to download filtered data through API Statistics (JSON API) when using eurostat package, although technically filtering datasets downloaded through the SDMX Dissemination API is also supported by Eurostat. We may support this feature in the future. In the meantime, if you are interested in filtering Dissemination API data queries manually, please consult the following Eurostat documentation:


See 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

A BibTeX entry for LaTeX users is

    title = {Retrieval and Analysis of Eurostat Open Data with the eurostat Package},
    author = {Leo Lahti and Janne Huovari and Markus Kainu and Przemyslaw Biecek},
    journal = {The R Journal},
    volume = {9},
    number = {1},
    pages = {385--392},
    year = {2017},
    doi = {10.32614/RJ-2017-019},
    url = {},

  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.

A BibTeX entry for LaTeX users is

    title = {eurostat: Tools for Eurostat Open Data},
    author = {Leo Lahti and Janne Huovari and Markus Kainu and Przemyslaw Biecek and Diego Hernangomez and Daniel Antal and Pyry Kantanen},
    url = {},
    type = {Computer software},
    year = {2023},
    note = {R package version 4.0.0},

When citing data downloaded from Eurostat, see section "Citing Eurostat data" in get_eurostat() documentation.


Przemyslaw Biecek, Leo Lahti, Janne Huovari Markus Kainu and Pyry Kantanen


if (FALSE) {
# Generally speaking these queries would be done through get_eurostat
tmp <- get_eurostat_json("nama_10_gdp")
yy <- get_eurostat_json("nama_10_gdp", filters = list(
  geo = c("FI", "SE", "EU28"),
  time = c(2015:2023),
  lang = "FR",
  na_item = "B1GQ",
  unit = "CLV_I10"

# TIME_PERIOD filter works also with the new JSON API
yy2 <- get_eurostat_json("nama_10_gdp", filters = list(
   geo = c("FI", "SE", "EU28"),
   TIME_PERIOD = c(2015:2023),
   lang = "FR",
   na_item = "B1GQ",
   unit = "CLV_I10"

# An example from get_eurostat
dd <- get_eurostat("nama_10_gdp",
  filters = list(
  geo = "FI",
  na_item = "B1GQ",
  unit = "CLV_I10"