sc_tabulate: Turn sc_data objects into tidy data frames

In STATcubeR: R Interface for the 'STATcube' REST API and Open Government Data

Turn sc_data objects into tidy data frames

Description

sc_tabulate() extracts the data in the table and turns it into a tidy data.frame. It applies labeling of the data and transforms time variables into a Date format if they satisfy certain 'STATcube' standards.

sc_tabulate(table, ...) is just an alias for table$tabulate(...) and was added so this rather complicated method can have a separate documentation page. It is recommended to use the table$tabulate() syntax

the ... argument decides which measures and/or fields should be included in the output. If no measures are given, all measures are included. The same is true for fields.

Usage

sc_tabulate(
  table,
  ...,
  .list = NULL,
  raw = FALSE,
  parse_time = TRUE,
  recode_zeros = inherits(table, "sc_table"),
  language = NULL,
  sort = FALSE
)

Arguments

table	An object of class sc_data
...	Names of measures and/or fields
.list	allows to define the arguments for ... as a character vector.
raw	If FALSE (the default), apply labeling to the dataset. Otherwise, return codes.
parse_time	Should time variables be converted into a Date format? Ignored if raw is set to TRUE.
recode_zeros	turn zero values into NAs
language	The language to be used for labeling. By default, the dataset language (table$language) is used.
sort	If TRUE, the resulting data will be sorted by all provided field values

Details

Aggregation is done as follows

• First, all columns that provide a total code via table$total_codes() will be used to filter for column == total_code or column != total_code

• Then, the remaining data is aggregated using rowsum()

The ellipsis (...) supports partial matching of codes and labels. See Examples

For objects of class sc_table two additional operations are performed.

• zeros are recoded to NAs

• rounding is done according to the precision of each measure. Rounding happens after the recoding to NA values

Value

a data.frame

See Also

sc_table_class

Examples

############################ OGD Data #######################################

table <- od_table("OGD_veste309_Veste309_1")

# no arguments -> same output as `table$data`
table$tabulate()

# provide some fields -> aggregate to keep only these fields
table$tabulate("Sex", "Citizenship")

# provide some measures -> drop all other measures from the output
table$tabulate("Arithmetic mean")

# mixture of measures and fields  -> keep exactly those columns
table$tabulate("Sex", "Arithmetic mean")

## define total codes
table$total_codes(
  `C-A11-0` = "A11-1",
  `C-STAATS-0` = "STAATS-9",
  `C-VEBDL-0` = "VEBDL-10",
  `C-BESCHV-0` = "BESCHV-1"
)

## alternatively, use partial matching to define totals
table$total_codes(
  Sex = "Sum total",
  Citizenship = "Total",
  Region = "Total",
  `Form of employment` = "Total"
)

# filter for totals in `Region (NUTS2)` and `Form of employment`. Drop totals
# in `Sex` and `Citizenship`.
table$tabulate("Sex", "Citizenship")

## switch language
table$language <- "de"

## `...` matches for codes and labels
table$tabulate("C-A11-0", "Staats", "2. Quartil (Median)")

## Keep totals in the output by removing total codes
table$tabulate("C-A11-0")      # -> 2 rows: "male" "female"
table$total_codes(`C-A11-0` = NA)
table$tabulate("C-A11-0")      # -> 3 rows: "total", "male", "female"

## table$tabulate(...) is an alias for sc_tabulate(table, ...)
sc_tabulate(table, "C-A11-0")

######################## 'STATcube' REST API ################################


table_tourism <- sc_table(sc_example("accomodation.json"), "de")

table_tourism$tabulate()
table_tourism$tabulate("Saison/Tourismusmonat")
table_tourism$tabulate("Saison/Tourismusmonat", "Ankünfte")
table_tourism$tabulate("Ankünfte")

STATcubeR documentation built on April 3, 2025, 7:31 p.m.