This method is deprecated in favor of cbs_get_data()

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

Arguments

id

Identifier of table, can be found in cbs_get_datasets()

...

optional filter statements, see details.

recode

recodes all codes in the code columns with their Title as found in the metadata

use_column_title

not used.

dir

Directory where the table should be downloaded. Defaults to temporary directory

base_url

optionally specify a different server. Useful for third party data services implementing the same protocol.

Value

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

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.

Note

All data are downloaded using cbs_download_table()

Examples

if (FALSE) {
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 
            )
}