Statistics Netherlands (www.cbs.nl) opendata API client for R
Retrieve data from the open data interface (dutch) of Statistics Netherlands (cbs.nl) with R.
Note for Windows 7/8 users
The security of the CBS web service has been updated, if you experience problems, you can try the following:
Sys.setenv(CURL_SSL_BACKEND = "openssl")
options("url.method" = "libcurl")
toc <- cbs_get_toc()
View(toc)Installation
From CRAN
install.packages("cbsodataR")The latest development version of cbsodata can installed using
devtools.
devtools::install_github("edwindj/cbsodataR")Usage (version 0.3+)
Retrieve a table of contents with all SN tables.
library(cbsodataR)
ds <- cbs_get_datasets("Language" = "en")
head(ds)## # A tibble: 6 x 25
## Updated Identifier Title ShortTitle ShortDescription Summary
## <dttm> <chr> <chr> <chr> <chr> <chr>
## 1 2021-03-19 00:00:00 80783eng Agricu… Agricultur… "\nThis table con… "Agricu…
## 2 2021-03-19 00:00:00 80784eng Agricu… Agricultur… "\nThis table con… "Agricu…
## 3 2021-03-31 00:00:00 7100eng Arable… Arable cro… "\nThis table pro… "Area a…
## 4 2019-04-12 00:00:00 70671ENG Fruit … Fruit cult… "\nThis table pro… "Cultiv…
## 5 2021-03-31 00:00:00 37738ENG Vegeta… Vegetables… "\nThis table pro… "Area a…
## 6 2021-02-15 00:00:00 83981ENG Livest… Livestock … "\nThis table com… "Manure…
## # … with 19 more variables: Modified <dttm>, MetaDataModified <dttm>,
## # ReasonDelivery <chr>, ExplanatoryText <chr>, OutputStatus <chr>,
## # Source <chr>, Language <chr>, Catalog <chr>, Frequency <chr>, Period <chr>,
## # SummaryAndLinks <chr>, ApiUrl <chr>, FeedUrl <chr>,
## # DefaultPresentation <chr>, DefaultSelection <chr>, GraphTypes <chr>,
## # RecordCount <int>, ColumnCount <int>, SearchPriority <chr>
or do a search:
res <- cbs_search("apple", language="en")
res[1:3, c(1:4)]## # A tibble: 3 x 4
## score Updated Identifier Title
## <dbl> <dttm> <chr> <chr>
## 1 16.0 2019-04-12 00:00:00 71509ENG Yield and cultivation area apples and pe…
## 2 10.3 2019-04-12 00:00:00 70671ENG Fruit culture; area fruit orchards, sort…
## 3 1.42 2015-05-22 00:00:00 81894ENG Health accounts; providers and financing…
Use the Identifier from tables to retrieve table information
cbs_get_meta('71509ENG')## 71509ENG: 'Yield apples and pears, 1997 - 2017', 2017
## FruitFarmingRegions: 'Fruit farming regions'
## Periods: 'Periods'
##
## Retrieve a default data selection with:
## cbs_get_data(id = "71509ENG", FruitFarmingRegions = c("1", "2",
## "4", "3", "5"), Periods = c("1997JJ00", "2012JJ00", "2013JJ00",
## "2016JJ00"), select = c("FruitFarmingRegions", "Periods", "TotalAppleVarieties_1",
## "CoxSOrangePippin_2", "DelbarestivaleDelcorf_3", "Elstar_4",
## "GoldenDelicious_5", "Jonagold_6", "Jonagored_7", "RodeBoskoopRennetApple_10",
## "OtherAppleVarieties_12", "TotalPearVarieties_13", "Conference_15",
## "DoyenneDuComice_16", "CookingPears_17", "TriompheDeVienne_18",
## "OtherPearVarieties_19", "TotalAppleVarieties_20", "CoxSOrangePippin_21",
## "DelbarestivaleDelcorf_22", "Elstar_23", "GoldenDelicious_24",
## "Jonagold_25", "Jonagored_26", "RodeBoskoopRennetApple_29", "OtherAppleVarieties_31",
## "TotalPearVarieties_32", "Conference_34", "DoyenneDuComice_35",
## "CookingPears_36", "TriompheDeVienne_37", "OtherPearVarieties_38"
## ))
Or download data.
library(dplyr) # just for example's sake
apples <- cbs_get_data("71509ENG")
apples %>%
select(1:4)## # A tibble: 105 x 4
## FruitFarmingRegions Periods TotalAppleVarieties_1 CoxSOrangePippin_2
## <chr> <chr> <int> <int>
## 1 1 1997JJ00 420 43
## 2 1 1998JJ00 518 40
## 3 1 1999JJ00 568 39
## 4 1 2000JJ00 461 27
## 5 1 2001JJ00 408 30
## 6 1 2002JJ00 354 17
## 7 1 2003JJ00 359 17
## 8 1 2004JJ00 436 14
## 9 1 2005JJ00 359 12
## 10 1 2006JJ00 365 11
## # … with 95 more rows
add label columns:
apples %>%
cbs_add_label_columns() %>%
select(1:4)## # A tibble: 105 x 4
## FruitFarmingRegions FruitFarmingRegions_label Periods Periods_label
## <chr> <fct> <chr> <fct>
## 1 1 Total Netherlands 1997JJ00 1997
## 2 1 Total Netherlands 1998JJ00 1998
## 3 1 Total Netherlands 1999JJ00 1999
## 4 1 Total Netherlands 2000JJ00 2000
## 5 1 Total Netherlands 2001JJ00 2001
## 6 1 Total Netherlands 2002JJ00 2002
## 7 1 Total Netherlands 2003JJ00 2003
## 8 1 Total Netherlands 2004JJ00 2004
## 9 1 Total Netherlands 2005JJ00 2005
## 10 1 Total Netherlands 2006JJ00 2006
## # … with 95 more rows
For more information, see vignette("cbsodataR")
Python user? Use cbsodata.