Download all data from Statistics Netherlands / CBS

Description

cbsodataR allows to download all official statistics of Statistics Netherlands (CBS) into R. For a introduction please visit the vignette: vignette("cbsodataR", package="cbsodataR"). For an introduction on using cbs cartographic maps: vignette("maps", package="cbsodataR") The functions cbs_get_datasets() and cbs_get_data() should get you going. Interested in cartographic maps, see cbs_get_maps().

Catalog function

• cbs_get_datasets() returns a data.frame with table of contents (toc): the publication meta data for available tables, can also include the extra tables not directly available in StatLine (dataderden)

• cbs_get_catalogs(), returns data.frame with the available (extra) catalogs.

• cbs_get_toc(), returns a data.frame with table of contents (toc): the publication meta data for available tables within the standard CBS

• cbs_search(), returns a data.frame with tables that contain the given search word.

Data retrieval

• cbs_get_data(), returns the data of a specific opendata/StatLine table

• cbs_download_table(), saves the data (and metadata) as csv files into a directory

Meta data

• cbs_get_meta(), returns the meta data objects of a specific opendata / StatLine table .

• cbs_add_date_column(), converts date/period codes into DateTime objects in the data set that was downloaded.

• cbs_add_label_columns(), adds labels to the code columns in the data that was downloaded.

Cartographic maps

• cbs_get_maps(), returns a data.frame with available CBS maps

• cbs_join_sf_with_data(), returns an sf object joined with cbs table

• cbs_get_sf(), returns an sf object without data, e.g. "gemeente_2020".

Copyright use

The content of CBS opendata is subject to Creative Commons Attribution (CC BY 4.0). This means that the re-use of the content is permitted, provided Statistics Netherlands is cited as the source. For more information see: https://www.cbs.nl/en-gb/about-us/website/copyright

Author(s)

Maintainer: Edwin de Jonge edwindjonge@gmail.com

Other contributors:

• Sara Houweling [contributor]

See Also

Useful links:

• https://github.com/edwindj/cbsodataR

• Report bugs at https://github.com/edwindj/cbsodataR/issues

clears the cache

Description

clears the cache

Usage

cache_clear()

Convert the time variable into either a date or numeric.

Description

Time periods in data of CBS are coded: yyyyXXww (e.g. 2018JJ00, 2018MM10, 2018KW02), which contains year (yyyy), type (XX) and index (ww). cbs_add_date_column converts these codes into a Date() or numeric. In addition it adds a frequency column denoting the type of the column.

Usage

cbs_add_date_column(x, date_type = c("Date", "numeric"), ...)

Arguments

Value

original dataset with two added columns: ⁠<period>_date⁠ and ⁠<period>_freq⁠. This last column is a factor with levels: Y, Q and M

See Also

Other data retrieval: cbs_add_label_columns(), cbs_add_unit_column(), cbs_download_data(), cbs_extract_table_id(), cbs_get_data(), cbs_get_data_from_link()

Other meta data: cbs_add_label_columns(), cbs_add_unit_column(), cbs_download_meta(), cbs_get_meta()

Examples

## Not run: 
x <- cbs_get_data( id      = "7196ENG"      # table id
                 , Periods = "2000MM03"     # March 2000
                 , CPI     = "000000"       # Category code for total 
                 )

# add a Periods_Date column
x <- cbs_add_date_column(x)
x

# add a Periods_numeric column
x <- cbs_add_date_column(x, date_type = "numeric")
x

## End(Not run)

For each column with codes add label column to data set

Description

Adds cbs labels to the dataset that was retrieved using cbs_get_data().

Usage

cbs_add_label_columns(x, columns = colnames(x), ...)

Arguments

Details

Code columns will be translated into label columns for each of the column that was supplied.

By default all code columns will be accompagnied with a label column. The name of each label column will be ⁠<code_column>_label⁠.

Value

the original data.frame x with extra label columns. (see description)

See Also

Other data retrieval: cbs_add_date_column(), cbs_add_unit_column(), cbs_download_data(), cbs_extract_table_id(), cbs_get_data(), cbs_get_data_from_link()

Other meta data: cbs_add_date_column(), cbs_add_unit_column(), cbs_download_meta(), cbs_get_meta()

Examples

## Not run: 

# get data for main (000000) Consumer Price Index (7196ENG) for March 2000, 
 x <- cbs_get_data( id      = "7196ENG"
                  , Periods = "2000MM03"  # March 2000
                  , CPI     = "000000"    # main price index
                  )
 cbs_add_label_columns(x)

## End(Not run)

Prepares dataset for making a map

Description

Adds a statcode column to the dataset, so it can be more easily joined with a map retrieved with cbs_get_sf().

Usage

cbs_add_statcode_column(x, ...)

Arguments

Details

Regional data uses the x$RegioS dimension for data. The "codes" for each region are also used in the cartographic map boundaries of regions as used in cbs_get_sf(). Unfortunately the codes in x$RegioS can have trailing spaces, and the variable used in the mapping material is named statcode. This method simply adds a statcode column with trimmed codes from RegioS, making it more easy to connect a dataset to a cartographic map.

Value

original dataset with added statcode column.

See Also

Other cartographic map: cbs_get_maps(), cbs_get_sf(), cbs_join_sf_with_data()

Examples

if (interactive()){
  
  # retrieve maps
  cbs_maps <- cbs_get_maps()
  cbs_maps |> head(4)
  
  gemeente_map <- cbs_get_sf("gemeente", 2023, verbose=TRUE)
  
  # sf object
  gemeente_map
  
  # plot the statcodes (included in the map)
  plot(gemeente_map, max.plot = 1)
  
  # now connect with some data
  labor <- cbs_get_data("85268NED"
                       , Perioden = "2022JJ00" # only 2022
                       , RegioS = has_substring("PV") # only province
                       , verbose = TRUE
                       )
  
  # most conveniently
  provincie_2022_with_data <- cbs_join_sf_with_data("provincie", 2022, labor)
  
  # better plotting options are ggplot2 or tmap, 
  # but keeping dependencies low...
  provincie_2022_with_data |> 
    subset(select = Werkloosheidspercentage_13) |> 
    plot( border ="#FFFFFF99", main="unemployment rate")
  
  ## but of course this can also be done by hand:
  labor <- labor |> 
    cbs_add_statcode_column()  # add column to connect with map
  
  provincie_2022 <- cbs_get_sf("provincie", 2022)
  
  # this is a left_join(provincie_2022, labor, by = "statcode")
  provincie_2022_data <- 
    within(provincie_2022, {
      unemployment_rate <- labor$Werkloosheidspercentage_13[match(statcode, labor$statcode)]
    }) 
  
  # better plotting options are ggplot2 or tmap, 
  # but keeping dependencies low...
  plot( provincie_2022_data[,c("unemployment_rate")]
      , border ="#FFFFFF99"
      , nbreaks = 12
      )
}

For each topic column add a unit column

Description

Adds extra unit columns to the dataset that was retrieved using cbs_get_data().

Usage

cbs_add_unit_column(x, columns = colnames(x), ...)

Arguments

Details

The unit columns will be named ⁠<topic_column>_unit⁠, and are a character

By default all topic columns will be with a unit column. The name of each unit column will be ⁠<topic_column>_unit⁠.

Value

the original data.frame x with extra unit columns. (see description)

See Also

Other data retrieval: cbs_add_date_column(), cbs_add_label_columns(), cbs_download_data(), cbs_extract_table_id(), cbs_get_data(), cbs_get_data_from_link()

Other meta data: cbs_add_date_column(), cbs_add_label_columns(), cbs_download_meta(), cbs_get_meta()

Examples

if (interactive()) {
  x <- cbs_get_data( id      = "7196ENG"      # table id
                   , Periods = "2000MM03"     # March 2000
                   , CPI     = "000000"       # Category code for total 
                   , verbose = TRUE           # show the url that is used
                   )
  
  
  # adds two extra columns
  x_with_units <- 
    x |> 
    cbs_add_unit_column()
  
  x_with_units[,1:4]
}

extract the default selection from a cbsodata meta object

Description

extract the default selection from a cbsodata meta object

Usage

cbs_default_selection(x, ...)

Arguments

Gets all data from a cbs table.

Description

Gets all data via bulk download. cbs_download_data dumps the data in (international) csv format.

Usage

cbs_download_data(
  id,
  path = file.path(id, "data.csv"),
  catalog = "CBS",
  ...,
  select = NULL,
  typed = TRUE,
  verbose = FALSE,
  show_progress = interactive() && !verbose,
  base_url = getOption("cbsodataR.base_url", BASE_URL)
)

Arguments

See Also

Other download: cbs_download_meta(), cbs_download_table()

Other data retrieval: cbs_add_date_column(), cbs_add_label_columns(), cbs_add_unit_column(), cbs_extract_table_id(), cbs_get_data(), cbs_get_data_from_link()

Dumps the meta data into a directory

Description

Dumps the meta data into a directory

Usage

cbs_download_meta(
  id,
  dir = id,
  catalog = "CBS",
  ...,
  verbose = FALSE,
  cache = FALSE,
  base_url = getOption("cbsodataR.base_url", BASE_URL)
)

Arguments

Value

meta data object

See Also

Other meta data: cbs_add_date_column(), cbs_add_label_columns(), cbs_add_unit_column(), cbs_get_meta()

Other download: cbs_download_data(), cbs_download_table()

Download a table from statistics Netherlands

Description

cbs_download_table downloads the data and metadata of a table from statistics Netherlands and stores it in csv format.

Usage

cbs_download_table(
  id,
  catalog = "CBS",
  ...,
  dir = id,
  cache = FALSE,
  verbose = TRUE,
  typed = FALSE,
  base_url = getOption("cbsodataR.base_url", BASE_URL)
)

Arguments

Details

cbs_download_table retrieves all raw meta data and data and stores these as csv files in the directory specified by dir. It is possible to add a filter. A filter is specified with ⁠<column_name> = <values>⁠ in which ⁠<values>⁠ is a character vector. Rows with values that are not part of the character vector are not returned.

Value

meta data object of id cbs_get_meta().

See Also

Other download: cbs_download_data(), cbs_download_meta()

Examples

## Not run: 

# download meta data and data from inflation/Consumer Price Indices
 download_table(id="7196ENG")

## End(Not run)

extract the id of a cbs table from the statline url

Description

extract the id of a cbs table from the statline url

Usage

cbs_extract_table_id(url, ...)

Arguments

Value

character with id, will be NA if not found.

See Also

Other data retrieval: cbs_add_date_column(), cbs_add_label_columns(), cbs_add_unit_column(), cbs_download_data(), cbs_get_data(), cbs_get_data_from_link()

Retrieves the possible catalog values that can be used for retrieving data

Description

Retrieves the possible catalog values that can be used for retrieving data

Usage

cbs_get_catalogs(..., base_url = BASE_URL)

Arguments

Examples

if (interactive()){
  catalogs <- cbs_get_catalogs()

  # Identifier of catalog can be used to query
  print(catalogs$Identifier)
  
  ds_rivm <- cbs_get_datasets(catalog = "RIVM")
  ds_rivm[1:5, c("Identifier","ShortTitle")]
}

Get data from Statistics Netherlands (CBS)

Description

Retrieves data from a table of Statistics Netherlands. A list of available tables can be retrieved with cbs_get_datasets(). Use the Identifier column of cbs_get_datssets as id in cbs_get_data and cbs_get_meta.

Usage

cbs_get_data(
  id,
  ...,
  catalog = "CBS",
  select = NULL,
  typed = TRUE,
  add_column_labels = TRUE,
  dir = tempdir(),
  verbose = FALSE,
  base_url = getOption("cbsodataR.base_url", BASE_URL),
  include_ID = FALSE
)

Arguments

Details

To reduce the download time, optionaly the data can be filtered on category values: for large tables (> 100k records) this is a wise thing to do.

The filter is specified with (see examples below):

• ⁠<column_name> = <values>⁠ in which ⁠<values>⁠ is a character vector. Rows with values that are not part of the character vector are not returned. Note that the values have to be values from the ⁠$Key⁠ column of the corresponding meta data. These may contain trailing spaces...

• ⁠<column_name> = has_substring(x)⁠ in which x is a character vector. Rows with values that do not have a substring that is in x are not returned. Useful substrings are "JJ", "KW", "MM" for Periods (years, quarters, months) and "PV", "CR" and "GM" for Regions (provinces, corops, municipalities).

• ⁠<column_name> = eq(<values>) | has_substring(x)⁠, which combines the two statements above.

By default the columns will be converted to their type (typed=TRUE). CBS uses multiple types of missing (unknown, surpressed, not measured, missing): users wanting all these nuances can use typed=FALSE which results in character columns.

Value

data.frame with the requested data. Note that a csv copy of the data is stored in dir.

Copyright use

The content of CBS opendata is subject to Creative Commons Attribution (CC BY 4.0). This means that the re-use of the content is permitted, provided Statistics Netherlands is cited as the source. For more information see: https://www.cbs.nl/en-gb/about-us/website/copyright

Note

All data are downloaded using cbs_download_table()

See Also

cbs_get_meta(), cbs_download_data()

Other data retrieval: cbs_add_date_column(), cbs_add_label_columns(), cbs_add_unit_column(), cbs_download_data(), cbs_extract_table_id(), cbs_get_data_from_link()

Other query: eq(), has_substring()

Examples

## Not run: 
cbs_get_data( id      = "7196ENG"      # table id
            , Periods = "2000MM03"     # March 2000
            , CPI     = "000000"       # Category code for total 
            )

# useful substrings:
## Periods: "JJ": years, "KW": quarters, "MM", months
## Regions: "NL", "PV": provinces, "GM": municipalities
  
cbs_get_data( id      = "7196ENG"      # table id
            , Periods = has_substring("JJ")     # all years
            , CPI     = "000000"       # Category code for total 
            )

cbs_get_data( id      = "7196ENG"      # table id
            , Periods = c("2000MM03","2001MM12")     # March 2000 and Dec 2001
            , CPI     = "000000"       # Category code for total 
            )

# combine either this
cbs_get_data( id      = "7196ENG"      # table id
            , Periods = has_substring("JJ") | "2000MM01" # all years and Jan 2001
            , CPI     = "000000"       # Category code for total 
            )

# or this: note the "eq" function
cbs_get_data( id      = "7196ENG"      # table id
            , Periods = eq("2000MM01") | has_substring("JJ") # Jan 2000 and all years
            , CPI     = "000000"       # Category code for total 
            )

## End(Not run)

Retrieve data from a link created from the StatLine app.

Description

Retrieve data from a link created from the StatLine app.

Usage

cbs_get_data_from_link(
  link,
  message = TRUE,
  ...,
  base_url = getOption("cbsodataR.base_url", BASE_URL)
)

Arguments

Value

Same as cbs_get_data

See Also

Other data retrieval: cbs_add_date_column(), cbs_add_label_columns(), cbs_add_unit_column(), cbs_download_data(), cbs_extract_table_id(), cbs_get_data()

Retrieve a data.frame with requested cbs tables

Description

cbs_get_datasets by default a list of all tables and all columns will be retrieved. You can restrict the query by supplying multiple filter statements or by specifying the columns that should be returned.

Usage

cbs_get_datasets(
  catalog = "CBS",
  convert_dates = TRUE,
  select = NULL,
  verbose = FALSE,
  cache = TRUE,
  base_url = getOption("cbsodataR.base_url", BASE_URL),
  ...
)

Arguments

Details

Note that setting catalog to NULL results in a datasets list with all tables including the extra catalogs.

Examples

if (interactive()){
  # retrieve the datasets in the "CBS" catalog
  ds <- cbs_get_datasets()
  ds[1:5, c("Identifier", "ShortTitle")]
  
  # retrieve de datasets in the "AZW" catalog
  ds_azw <- cbs_get_datasets(catalog = "AZW")
  
  # to retrieve all datasets of all catalogs, supply "NULL"
  ds_all <- cbs_get_datasets(catalog = NULL)
}

Get list of cbs maps

Description

Returns a list of (simplified) maps, that can be used with CBS data.

Usage

cbs_get_maps(verbose = FALSE, cache = TRUE)

Arguments

Value

data.frame with region, year and links to geojson

See Also

Other cartographic map: cbs_add_statcode_column(), cbs_get_sf(), cbs_join_sf_with_data()

Examples

if (interactive()){
  
  # retrieve maps
  cbs_maps <- cbs_get_maps()
  cbs_maps |> head(4)
  
  gemeente_map <- cbs_get_sf("gemeente", 2023, verbose=TRUE)
  
  # sf object
  gemeente_map
  
  # plot the statcodes (included in the map)
  plot(gemeente_map, max.plot = 1)
  
  # now connect with some data
  labor <- cbs_get_data("85268NED"
                       , Perioden = "2022JJ00" # only 2022
                       , RegioS = has_substring("PV") # only province
                       , verbose = TRUE
                       )
  
  # most conveniently
  provincie_2022_with_data <- cbs_join_sf_with_data("provincie", 2022, labor)
  
  # better plotting options are ggplot2 or tmap, 
  # but keeping dependencies low...
  provincie_2022_with_data |> 
    subset(select = Werkloosheidspercentage_13) |> 
    plot( border ="#FFFFFF99", main="unemployment rate")
  
  ## but of course this can also be done by hand:
  labor <- labor |> 
    cbs_add_statcode_column()  # add column to connect with map
  
  provincie_2022 <- cbs_get_sf("provincie", 2022)
  
  # this is a left_join(provincie_2022, labor, by = "statcode")
  provincie_2022_data <- 
    within(provincie_2022, {
      unemployment_rate <- labor$Werkloosheidspercentage_13[match(statcode, labor$statcode)]
    }) 
  
  # better plotting options are ggplot2 or tmap, 
  # but keeping dependencies low...
  plot( provincie_2022_data[,c("unemployment_rate")]
      , border ="#FFFFFF99"
      , nbreaks = 12
      )
}

Get metadata of a cbs table

Description

Retrieve the meta data of a CBS open data table. Caching (cache=TRUE) improves the performance considerably.

Usage

cbs_get_meta(
  id,
  catalog = "CBS",
  verbose = FALSE,
  cache = TRUE,
  base_url = getOption("cbsodataR.base_url", BASE_URL)
)

Arguments

Details

The meta data of a CBS table is determined by the web api of Statistics Netherlands. cbsodataR stays close to this API. Each cbsodataR object has the following metadata items, which are all data.frames :

• ⁠$TableInfos⁠: data.frame with the descriptive publication metadata of the table, such as Title, Description, Summary etc.

• ⁠$DataProperties⁠: data.frame with the Title, Description, Unit etc. of each column in the dataset that is downloaded with cbs_get_data().

• ⁠$CategoryGroups⁠: hierarchical groupings of the code columns.

• ⁠$<code column>⁠: for each code column a data.frame with the Title, Key, Description etc. of each code / category in that column. e.g. Perioden for time codes c("2019JJ00","2018JJ00").

Value

cbs_table object containing several data.frames with meta data (see details)

See Also

Other meta data: cbs_add_date_column(), cbs_add_label_columns(), cbs_add_unit_column(), cbs_download_meta()

Load meta data from a downloaded table

Description

Load meta data from a downloaded table

Usage

cbs_get_meta_from_dir(dir)

Arguments

Value

cbs_table object with meta data

Retrieve an sf map for plotting

Description

Retrieve a polygon sf object that can be used for plotting. This function only provides the region boundaries.

Usage

cbs_get_sf(
  region,
  year,
  keep_columns = c("statcode", "statnaam"),
  verbose = FALSE
)

Arguments

Details

To use the map for plotting:

• add data columns to the sf data.frame returned by cbs_get_sf, e.g. by using dplyr::left_join or otherwise

• use ggplot2, tmap, leaflet or any other plotting library useful for plotting spatial data.

Value

sf::st_sf() object with the polygons of the regions specified.

See Also

Other cartographic map: cbs_add_statcode_column(), cbs_get_maps(), cbs_join_sf_with_data()

Examples

if (interactive()){
  
  # retrieve maps
  cbs_maps <- cbs_get_maps()
  cbs_maps |> head(4)
  
  gemeente_map <- cbs_get_sf("gemeente", 2023, verbose=TRUE)
  
  # sf object
  gemeente_map
  
  # plot the statcodes (included in the map)
  plot(gemeente_map, max.plot = 1)
  
  # now connect with some data
  labor <- cbs_get_data("85268NED"
                       , Perioden = "2022JJ00" # only 2022
                       , RegioS = has_substring("PV") # only province
                       , verbose = TRUE
                       )
  
  # most conveniently
  provincie_2022_with_data <- cbs_join_sf_with_data("provincie", 2022, labor)
  
  # better plotting options are ggplot2 or tmap, 
  # but keeping dependencies low...
  provincie_2022_with_data |> 
    subset(select = Werkloosheidspercentage_13) |> 
    plot( border ="#FFFFFF99", main="unemployment rate")
  
  ## but of course this can also be done by hand:
  labor <- labor |> 
    cbs_add_statcode_column()  # add column to connect with map
  
  provincie_2022 <- cbs_get_sf("provincie", 2022)
  
  # this is a left_join(provincie_2022, labor, by = "statcode")
  provincie_2022_data <- 
    within(provincie_2022, {
      unemployment_rate <- labor$Werkloosheidspercentage_13[match(statcode, labor$statcode)]
    }) 
  
  # better plotting options are ggplot2 or tmap, 
  # but keeping dependencies low...
  plot( provincie_2022_data[,c("unemployment_rate")]
      , border ="#FFFFFF99"
      , nbreaks = 12
      )
}

Get a the list of tables connected to themes

Description

Get a the list of tables connected to themes

Usage

cbs_get_tables_themes(
  ...,
  select = NULL,
  verbose = FALSE,
  cache = TRUE,
  base_url = getOption("cbsodataR.base_url", BASE_URL)
)

Arguments

Value

A data.frame with various properties of SN/CBS themes.

Get list of all cbs thematic entries.

Description

Returns a list of all cbs themes.

Usage

cbs_get_themes(
  ...,
  select = NULL,
  verbose = TRUE,
  cache = FALSE,
  base_url = getOption("cbsodataR.base_url", BASE_URL)
)

Arguments

Value

A data.frame with various properties of SN/CBS themes.

The filter is specified with ⁠<column_name> = <values>⁠ in which ⁠<values>⁠ is a character vector. Rows with values that are not part of the character vector are not returned.

Examples

## Not run: 
# get list of all themes
cbs+get_themes()

# get list of all dutch themes from the Catalog "CBS"
cbs_get_themes(Language="nl", Catalog="CBS")

## End(Not run)

Retrieve a data.frame with requested cbs tables

Description

cbs_get_toc by default a list of all tables and all columns will be retrieved. You can restrict the query by supplying multiple filter statements or by specifying the columns that should be returned.

Usage

cbs_get_toc(
  ...,
  convert_dates = TRUE,
  select = NULL,
  verbose = FALSE,
  cache = TRUE,
  base_url = getOption("cbsodataR.base_url", BASE_URL),
  include_ID = FALSE
)

Arguments

Value

data.frame with identifiers, titles and descriptions of tables

Note

cbs_get_toc will cache results, so subsequent calls will be much faster.

Examples

## Not run: 

# get list of english tables
tables_en <- cbs_get_toc(Language="en")

# get list of dutch tables
tables_nl <- cbs_get_toc(Language="nl")
View(tables_nl)

## End(Not run)

Create a map with data from cbsodataR

Description

Utility function to create an sf map object with data from cbsodataR.

Usage

cbs_join_sf_with_data(region, year, x, verbose = FALSE)

Arguments

Details

The function is a simple wrapper around cbs_add_statcode_column() and cbs_get_sf(). Please note that the resulting sf::st_sf() dataset has the same number of rows as the requested map object, as requested by cbs_get_sf(), i.e. not the same rows as x. It's the users responsibility to match the correct map to the selection of the data.

See Also

Other cartographic map: cbs_add_statcode_column(), cbs_get_maps(), cbs_get_sf()

Examples

if (interactive()){
  
  # retrieve maps
  cbs_maps <- cbs_get_maps()
  cbs_maps |> head(4)
  
  gemeente_map <- cbs_get_sf("gemeente", 2023, verbose=TRUE)
  
  # sf object
  gemeente_map
  
  # plot the statcodes (included in the map)
  plot(gemeente_map, max.plot = 1)
  
  # now connect with some data
  labor <- cbs_get_data("85268NED"
                       , Perioden = "2022JJ00" # only 2022
                       , RegioS = has_substring("PV") # only province
                       , verbose = TRUE
                       )
  
  # most conveniently
  provincie_2022_with_data <- cbs_join_sf_with_data("provincie", 2022, labor)
  
  # better plotting options are ggplot2 or tmap, 
  # but keeping dependencies low...
  provincie_2022_with_data |> 
    subset(select = Werkloosheidspercentage_13) |> 
    plot( border ="#FFFFFF99", main="unemployment rate")
  
  ## but of course this can also be done by hand:
  labor <- labor |> 
    cbs_add_statcode_column()  # add column to connect with map
  
  provincie_2022 <- cbs_get_sf("provincie", 2022)
  
  # this is a left_join(provincie_2022, labor, by = "statcode")
  provincie_2022_data <- 
    within(provincie_2022, {
      unemployment_rate <- labor$Werkloosheidspercentage_13[match(statcode, labor$statcode)]
    }) 
  
  # better plotting options are ggplot2 or tmap, 
  # but keeping dependencies low...
  plot( provincie_2022_data[,c("unemployment_rate")]
      , border ="#FFFFFF99"
      , nbreaks = 12
      )
}

Find tables containing search words

Description

Find tables containing search words.

Usage

cbs_search(
  query,
  catalog = "CBS",
  language = "nl",
  format = c("datasets", "docs", "raw"),
  verbose = FALSE,
  ...
)

Arguments

Details

The format can be either:

• datasets: the same format as cbs_get_datasets(), with an extra score column.

• docs: the table results from the solr query,

• raw: the complete results from the solr query.

Examples

if (interactive()){
  # search for tables containing the word birth
  
  ds_en <- cbs_search("Birth", language="en")
  ds_en[1:3, c("Identifier", "ShortTitle")]
  
  # or in Dutch
  
  ds_nl <- cbs_search(c("geboorte"), language="nl")
  ds_nl[1:3, c("Identifier", "ShortTitle")]
  
  # Search in an other catalog
  ds_rivm <- cbs_search(c("geboorte"), catalog = "RIVM", language="nl")
  ds_rivm[1:3, c("Identifier", "ShortTitle")]
  
  # search in all catalogs
  ds_all <- cbs_search(c("geboorte"), catalog = NULL, language="nl")

  # docs
  docs <- cbs_search(c("geboorte,sterfte"), language="nl", format="docs")
  names(docs)
  docs[1:2,]
  
  #raw 
  raw_res <- cbs_search(c("geboorte,sterfte"), language="nl", format="raw")
  raw_res
}

Gets all data from a cbs table.

Description

This method is deprecated in favor of cbs_download_data().

Usage

download_data(
  id,
  path = file.path(id, "data.csv"),
  ...,
  select = NULL,
  typed = FALSE,
  verbose = TRUE,
  base_url = getOption("cbsodataR.base_url", BASE_URL)
)

Arguments

See Also

Other download: cbs_download_meta(), cbs_download_table()

Other data retrieval: cbs_add_date_column(), cbs_add_label_columns(), cbs_add_unit_column(), cbs_extract_table_id(), cbs_get_data(), cbs_get_data_from_link()

Dumps the meta data into a directory

Description

This method is deprecated in favor of cbs_download_meta().

Usage

download_meta(
  id,
  dir = id,
  ...,
  verbose = FALSE,
  cache = FALSE,
  base_url = getOption("cbsodataR.base_url", BASE_URL)
)

Arguments

Value

meta data object

See Also

Other meta data: cbs_add_date_column(), cbs_add_label_columns(), cbs_add_unit_column(), cbs_get_meta()

Other download: cbs_download_data(), cbs_download_table()

Download a table from statistics Netherlands

Description

This method is deprecated in favor of cbs_download_table().

Usage

download_table(
  id,
  ...,
  dir = id,
  cache = FALSE,
  verbose = TRUE,
  typed = FALSE,
  base_url = getOption("cbsodataR.base_url", BASE_URL)
)

Arguments

Details

cbs_download_table retrieves all raw meta data and data and stores these as csv files in the directory specified by dir. It is possible to add a filter. A filter is specified with ⁠<column_name> = <values>⁠ in which ⁠<values>⁠ is a character vector. Rows with values that are not part of the character vector are not returned.

Value

meta data object of id cbs_get_meta().

See Also

Other download: cbs_download_data(), cbs_download_meta()

Examples

## Not run: 

# download meta data and data from inflation/Consumer Price Indices
 download_table(id="7196ENG")

## End(Not run)

Detect codes in a column

Description

Detects for codes in a column. eq filters the data set at CBS: rows that have a code that is not in x are filtered out.

Usage

eq(x, column = NULL, allowed = NULL)

Arguments

Value

query object

See Also

Other query: cbs_get_data(), has_substring()

Examples

## Not run: 
cbs_get_data( id      = "7196ENG"      # table id
            , Periods = "2000MM03"     # March 2000
            , CPI     = "000000"       # Category code for total 
            )

# useful substrings:
## Periods: "JJ": years, "KW": quarters, "MM", months
## Regions: "NL", "PV": provinces, "GM": municipalities
  
cbs_get_data( id      = "7196ENG"      # table id
            , Periods = has_substring("JJ")     # all years
            , CPI     = "000000"       # Category code for total 
            )

cbs_get_data( id      = "7196ENG"      # table id
            , Periods = c("2000MM03","2001MM12")     # March 2000 and Dec 2001
            , CPI     = "000000"       # Category code for total 
            )

# combine either this
cbs_get_data( id      = "7196ENG"      # table id
            , Periods = has_substring("JJ") | "2000MM01" # all years and Jan 2001
            , CPI     = "000000"       # Category code for total 
            )

# or this: note the "eq" function
cbs_get_data( id      = "7196ENG"      # table id
            , Periods = eq("2000MM01") | has_substring("JJ") # Jan 2000 and all years
            , CPI     = "000000"       # Category code for total 
            )

## End(Not run)

Get data from Statistics Netherlands (CBS)

Description

This method is deprecated in favor of cbs_get_data()

Usage

get_data(
  id,
  ...,
  recode = TRUE,
  use_column_title = recode,
  dir = tempdir(),
  base_url = getOption("cbsodataR.base_url", BASE_URL)
)

Arguments

Details

To reduce the download time, optionaly the data can be filtered on category values: for large tables (> 100k records) this is a wise thing to do.

The filter is specified with (see examples below):

• ⁠<column_name> = <values>⁠ in which ⁠<values>⁠ is a character vector. Rows with values that are not part of the character vector are not returned. Note that the values have to be values from the ⁠$Key⁠ column of the corresponding meta data. These may contain trailing spaces...

• ⁠<column_name> = has_substring(x)⁠ in which x is a character vector. Rows with values that do not have a substring that is in x are not returned. Useful substrings are "JJ", "KW", "MM" for Periods (years, quarters, months) and "PV", "CR" and "GM" for Regions (provinces, corops, municipalities).

• ⁠<column_name> = eq(<values>) | has_substring(x)⁠, which combines the two statements above.

By default the columns will be converted to their type (typed=TRUE). CBS uses multiple types of missing (unknown, surpressed, not measured, missing): users wanting all these nuances can use typed=FALSE which results in character columns.

Value

data.frame with the requested data. Note that a csv copy of the data is stored in dir.

Copyright use

The content of CBS opendata is subject to Creative Commons Attribution (CC BY 4.0). This means that the re-use of the content is permitted, provided Statistics Netherlands is cited as the source. For more information see: https://www.cbs.nl/en-gb/about-us/website/copyright

Note

All data are downloaded using cbs_download_table()

See Also

cbs_get_meta(), cbs_download_data()

Other data retrieval: cbs_add_date_column(), cbs_add_label_columns(), cbs_add_unit_column(), cbs_download_data(), cbs_extract_table_id(), cbs_get_data_from_link()

Other query: eq(), has_substring()

Examples

## Not run: 
cbs_get_data( id      = "7196ENG"      # table id
            , Periods = "2000MM03"     # March 2000
            , CPI     = "000000"       # Category code for total 
            )

# useful substrings:
## Periods: "JJ": years, "KW": quarters, "MM", months
## Regions: "NL", "PV": provinces, "GM": municipalities
  
cbs_get_data( id      = "7196ENG"      # table id
            , Periods = has_substring("JJ")     # all years
            , CPI     = "000000"       # Category code for total 
            )

cbs_get_data( id      = "7196ENG"      # table id
            , Periods = c("2000MM03","2001MM12")     # March 2000 and Dec 2001
            , CPI     = "000000"       # Category code for total 
            )

# combine either this
cbs_get_data( id      = "7196ENG"      # table id
            , Periods = has_substring("JJ") | "2000MM01" # all years and Jan 2001
            , CPI     = "000000"       # Category code for total 
            )

# or this: note the "eq" function
cbs_get_data( id      = "7196ENG"      # table id
            , Periods = eq("2000MM01") | has_substring("JJ") # Jan 2000 and all years
            , CPI     = "000000"       # Category code for total 
            )

## End(Not run)

Get meta data from table

Description

This method is deprecated in favor of cbs_get_meta()

Usage

get_meta(
  id,
  verbose = TRUE,
  cache = FALSE,
  base_url = getOption("cbsodataR.base_url", BASE_URL)
)

Arguments

Details

The meta data of a CBS table is determined by the web api of Statistics Netherlands. cbsodataR stays close to this API. Each cbsodataR object has the following metadata items, which are all data.frames :

• ⁠$TableInfos⁠: data.frame with the descriptive publication metadata of the table, such as Title, Description, Summary etc.

• ⁠$DataProperties⁠: data.frame with the Title, Description, Unit etc. of each column in the dataset that is downloaded with cbs_get_data().

• ⁠$CategoryGroups⁠: hierarchical groupings of the code columns.

• ⁠$<code column>⁠: for each code column a data.frame with the Title, Key, Description etc. of each code / category in that column. e.g. Perioden for time codes c("2019JJ00","2018JJ00").

Value

cbs_table object containing several data.frames with meta data (see details)

See Also

Other meta data: cbs_add_date_column(), cbs_add_label_columns(), cbs_add_unit_column(), cbs_download_meta()

Load meta data from a downloaded table

Description

Load meta data from a downloaded table

Usage

get_meta_from_dir(dir)

Arguments

Value

cbs_table object with meta data

Retrieve a data.frame with requested cbs tables

Description

This method is deprecated in favor of cbs_get_toc().

Usage

get_table_list(
  ...,
  select = NULL,
  base_url = getOption("cbsodataR.base_url", BASE_URL)
)

Arguments

Value

data.frame with identifiers, titles and descriptions of tables

Examples

## Not run: 

# get list of english tables
tables_en <- get_table_list(Language="en")

# get list of dutch tables
tables_nl <- get_table_list(Language="nl")
View(tables_nl)

## End(Not run)

Get a the list of tables connected to themes

Description

Get a the list of tables connected to themes

Usage

get_tables_themes(
  ...,
  select = NULL,
  base_url = getOption("cbsodataR.base_url", BASE_URL)
)

Arguments

Value

A data.frame with various properties of SN/CBS themes.

Get list of all cbs thematic entries.

Description

Returns a list of all cbs themes.

Usage

get_themes(
  ...,
  select = NULL,
  verbose = TRUE,
  cache = FALSE,
  base_url = getOption("cbsodataR.base_url", BASE_URL)
)

Arguments

Value

A data.frame with various properties of SN/CBS themes.

The filter is specified with ⁠<column_name> = <values>⁠ in which ⁠<values>⁠ is a character vector. Rows with values that are not part of the character vector are not returned.

Examples

## Not run: 
# get list of all themes
get_themes()

# get list of all dutch themes from the Catalog "CBS"
get_themes(Language="nl", Catalog="CBS")

## End(Not run)

Detect substring in column column

Description

Detects a substring in a column. has_substring filters the dataset at CBS: rows that have a code that does not contain (one of) x are filtered out.

Usage

has_substring(x, column = NULL, allowed = NULL)

Arguments

See Also

Other query: cbs_get_data(), eq()

Examples

## Not run: 
cbs_get_data( id      = "7196ENG"      # table id
            , Periods = "2000MM03"     # March 2000
            , CPI     = "000000"       # Category code for total 
            )

# useful substrings:
## Periods: "JJ": years, "KW": quarters, "MM", months
## Regions: "NL", "PV": provinces, "GM": municipalities
  
cbs_get_data( id      = "7196ENG"      # table id
            , Periods = has_substring("JJ")     # all years
            , CPI     = "000000"       # Category code for total 
            )

cbs_get_data( id      = "7196ENG"      # table id
            , Periods = c("2000MM03","2001MM12")     # March 2000 and Dec 2001
            , CPI     = "000000"       # Category code for total 
            )

# combine either this
cbs_get_data( id      = "7196ENG"      # table id
            , Periods = has_substring("JJ") | "2000MM01" # all years and Jan 2001
            , CPI     = "000000"       # Category code for total 
            )

# or this: note the "eq" function
cbs_get_data( id      = "7196ENG"      # table id
            , Periods = eq("2000MM01") | has_substring("JJ") # Jan 2000 and all years
            , CPI     = "000000"       # Category code for total 
            )

## End(Not run)

resolve a deeplink created in the opendata portal

Description

resolve a deeplink created in the opendata portal

Usage

resolve_deeplink(
  deeplink,
  ...,
  base_url = getOption("cbsodataR.base_url", BASE_URL)
)

Arguments

Value

information object with table id, select, filter and query statement.