jbdatascience/cbsodatar

Statistics Netherlands (CBS) OpenData API Client for R

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.

Python user? Use cbsodata.

API change (0.3+)

In version 0.3 the api of the functions has changed. Old functions (should) still work, but generate warnings asking to switch to the new api.

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)
toc <- cbs_get_toc("Language" = "en")
head(toc)

## # A tibble: 6 x 25
##   Updated             Identifier Title ShortTitle ShortDescription Summary
##   <dttm>              <chr>      <chr> <chr>      <chr>            <chr>  
## 1 2018-03-21 00:00:00 80783eng   Agri… Agricultu… "\nThis table c… "Agric…
## 2 2018-02-28 00:00:00 80784eng   Agri… Agricultu… "\nThis table c… "Agric…
## 3 2018-02-08 00:00:00 7100eng    Arab… Arable cr… "\nThis table p… "Area …
## 4 2017-03-31 00:00:00 70671ENG   Frui… Fruit cul… "\nThis table p… "Culti…
## 5 2018-03-29 00:00:00 37738ENG   Vege… Vegetable… "\nThis table p… "Area …
## 6 2018-03-30 00:00:00 71509ENG   Yiel… Yield app… "\nThis table p… "yield…
## # ... 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>

Use the Identifier from tables to retrieve table information

cbs_get_meta('71509ENG')

## 71509ENG: 'Yield apples and pears', 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")