Statistics Netherlands (www.cbs.nl) opendata API client for R

Installation

install.packages("cbsodataR")

devtools::install_github("edwindj/cbsodataR")

Usage

library(cbsodataR)ds<- cbs_get_datasets("Language"="en")head(ds)

## # A tibble: 6 × 25##   Updated             Identifier Title       ShortTitle ShortDescription Summary##   <dttm>              <chr>      <chr>       <chr>      <chr>            <chr>  ## 1 2023-11-30 00:00:00 80783eng   Agricultur… Agricultu… "\nThis table c… "Agric…## 2 2023-11-30 00:00:00 80784eng   Agricultur… Agricultu… "\nThis table c… "Agric…## 3 2023-12-12 00:00:00 85636ENG   Arable cro… Arable cr… "\nThis table p… "area …## 4 2023-04-03 00:00:00 37738ENG   Vegetables… Vegetable… "\nThis table p… "Area …## 5 2023-06-30 00:00:00 83981ENG   Livestock … Livestock… "\nThis table c… "Manur…## 6 2023-10-12 00:00:00 84952ENG   Livestock … Livestock  "\nThis table c… "Lives…## # ℹ 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>

res<- cbs_search("apple",language="en")res[1:3, c(1:4)]

## # A tibble: 3 × 4##    score Updated             Identifier Title                                   ##    <dbl> <dttm>              <chr>      <chr>                                   ## 1 0.0503 2023-12-07 00:00:00 85680ENG   Trade in goods; border crossing, SITC (…## 2 0.0356 2023-12-07 00:00:00 85683ENG   Trade in goods; border crossing, SITC (…## 3 0.0337 2023-12-07 00:00:00 85682ENG   Trade in goods; border crossing, SITC (…

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"## ))

library(dplyr)# just for example's sakeapples<- cbs_get_data("71509ENG")apples|>   select(1:4)

## # A tibble: 105 × 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## # ℹ 95 more rows

apples|>   cbs_add_label_columns()|>   select(1:4)

## # A tibble: 105 × 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         ## # ℹ 95 more rows