View source: R/get_eurostat_json.R
get_eurostat_json | R Documentation |
Retrieve data from Eurostat API in JSON format.
get_eurostat_json(
id,
filters = NULL,
type = "code",
lang = "en",
stringsAsFactors = FALSE,
proxy = FALSE,
...
)
id |
A unique identifier / code for the dataset of interest. If code is not
known |
filters |
A named list of filters. Names of list objects are Eurostat
variable codes and values are vectors of observation codes. If |
type |
A type of variables, " |
lang |
2-letter language code, default is " |
stringsAsFactors |
if |
proxy |
Use proxy, TRUE or FALSE (default). |
... |
Arguments passed on to
|
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 = "127.0.0.1", 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.
A dataset as an object of data.frame
class.
Data is downloaded from Eurostat API Statistics. See Eurostat documentation for more information about data queries in API Statistics https://wikis.ec.europa.eu/display/EUROSTATHELP/API+Statistics+-+data+query
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: https://wikis.ec.europa.eu/display/EUROSTATHELP/API+Statistics+-+migrating+from+JSON+web+service+to+API+Statistics
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: https://ec.europa.eu/eurostat/web/query-builder
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
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.
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.
Example:
lang = "fr"
For more information about data filtering see Eurostat documentation on API Statistics: https://wikis.ec.europa.eu/display/EUROSTATHELP/API+Statistics+-+data+query#APIStatisticsdataquery-TheparametersdefinedintheRESTrequest
The following copyright notice is provided for end user convenience. Please check up-to-date copyright information from the eurostat website: https://ec.europa.eu/eurostat/about-us/policies/copyright
"(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
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.
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:
https://wikis.ec.europa.eu/display/EUROSTATHELP/API+SDMX+2.1+-+data+filtering
Przemyslaw Biecek, Leo Lahti, Janne Huovari Markus Kainu and Pyry Kantanen
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 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)'.
When citing data downloaded from Eurostat, see section "Citing Eurostat data"
in get_eurostat()
documentation.
httr2::req_proxy()
## Not run:
# 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"
))
## End(Not run)
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