Project Status: Active – The project has reached a stable, usable state and is being actively developed. CRAN_Status_Badge CRAN Total Downloads License: MIT

This is an R wrapper for the Wikidata Query Service (WDQS) which provides a way for tools to query Wikidata via SPARQL (see the beta at It is written in and for R, and was inspired by Oliver Keyes' WikipediR and WikidataR packages.

Author: Mikhail Popov (Wikimedia Foundation)
License: MIT
Status: Active



To install the development version:

# install.packages(c("devtools", "httr", "dplyr", "jsonlite"))


In this example, we find an "instance of" (P31) "film" (Q11424) that has the label "The Cabin in the Woods" (Q45394), get its genres (P136), and then use WDQS label service to return the genre labels.

sparql_query <- 'PREFIX wd: <>
PREFIX wdt: <>
PREFIX wikibase: <>
SELECT DISTINCT ?genre ?genreLabel WHERE {
  SERVICE wikibase:label { bd:serviceParam wikibase:language "en". }
  ?film wdt:P31 wd:Q11424.
  ?film rdfs:label "The Cabin in the Woods"@en.
  ?film wdt:P136 ?genre.
# 5 rows were returned by WDQS
genre genreLabel horror film science fiction film comedy horror comedy-drama monster film

For more example SPARQL queries, see this page on Wikidata.

query_wikidata() can accept multiple queries, returning a (potentially named) list of data frames. If the vector of SPARQL queries is named, the results will inherit those names.

Extracting and running example SPARQL queries

This package does not rely on the rvest and urltools R packages for core functionality, but if the user has them installed then there is a bonus function for scraping the examples page and extracting SPARQL queries.

# install.packages(c("rvest", "urltools"))
sparql_query <- scrape_example(c("Cats", "Horses", "Largest cities with female mayor"))
cat(sparql_query[["Largest cities with female mayor"]])
# Largest cities with female mayor
#added before 2016-10
#TEMPLATE={"template":"Largest ?c with ?sex head of government","variables":{"?sex":{"query":" SELECT ?id WHERE { ?id wdt:P31 wd:Q48264 .  } "},"?c":{"query":"SELECT DISTINCT ?id WHERE {  ?c wdt:P31 ?id.  ?c p:P6 ?mayor. }"} } }
SELECT DISTINCT ?city ?cityLabel ?mayor ?mayorLabel 
  BIND(wd:Q6581072 AS ?sex)
  BIND(wd:Q515 AS ?c)

    ?city wdt:P31/wdt:P279* ?c .  # find instances of subclasses of city
    ?city p:P6 ?statement .            # with a P6 (head of goverment) statement
    ?statement ps:P6 ?mayor .          # ... that has the value ?mayor
    ?mayor wdt:P21 ?sex .       # ... where the ?mayor has P21 (sex or gender) female
    FILTER NOT EXISTS { ?statement pq:P582 ?x }  # ... but the statement has no P582 (end date) qualifier
    # Now select the population value of the ?city
    # (wdt: properties use only statements of "preferred" rank if any, usually meaning "current population")
    ?city wdt:P1082 ?population .
    # Optionally, find English labels for city and mayor:
    SERVICE wikibase:label {
        bd:serviceParam wikibase:language "en" .
ORDER BY DESC(?population)

Now we can run all three scraped SPARQL queries and get back three data.frames:

results <- query_wikidata(sparql_query)
# 113 rows were returned by WDQS
# 6677 rows were returned by WDQS
# 10 rows were returned by WDQS
results$`Largest cities with female mayor`
city cityLabel mayor mayorLabel Tokyo Yuriko Koike Mumbai Snehal Ambekar Yokohama Fumiko Hayashi Madrid Manuela Carmena Surabaya Tri Rismaharini Rome Virginia Raggi Paris Anne Hidalgo Houston Annise Parker Havana Marta Hernández Romero Bucharest Gabriela Fireaa

Additional Information

Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.