Invoke the /schema endpoint of the STATcube REST API. This endpoint can be used to get all available databases and tables as well as metadata about specific databases.
The main function sc_schema() can be used with any resouce id.
sc_schema_catalogue() and sc_schema_db() are very simple
wrapper functions around sc_schema() and are comparabable to the
catalogue explorer or the
table view of the STATcube GUI.
The responses of the API are tree-like data structures which
are wrapped into a class called sc_schema to simplify the usage in R.
Usage
sc_schema(id = NULL, depth = NULL, language = NULL, key = NULL, server = "ext")
# S3 method for sc_schema
print(x, tree = NULL, ..., limit = 30)
sc_schema_flatten(x, type)
sc_schema_catalogue(
depth = "folder",
language = c("en", "de"),
key = NULL,
server = "ext"
)
sc_schema_db(id, depth = "valueset", language = c("en", "de"), key = NULL)Arguments
- id
A resource identifier in uid format. In case of
sc_schema_db(), this should be a database id. Forsc_schema()any resource-id (folder, measure, table, ...) is accepted.- depth
If provided, the request will recurse into the given level. For datasets, available options are
NULL(no recursion),"folder","field"and"valueset". For the catalogue, onlyNULLand"folder"are applicable.- language
The language to be used for labeling.
"en"or"de"- key
(
string) An API key. To display your key, callsc_browse_preferences().- server
A STATcube API server. Defaults to the external Server via
"ext". Other options are"red"for the editing server and"prod"for the production server. External users should always use the default option"ext".- x
an object of class
sc_schema()i.e. the return value ofsc_schema(),sc_schema_db()orsc_schema_catalogue().- tree
wether to use the
data.treepackage for printing.- limit, ...
passed to
data.tree::print.Node()iftreeis set toTRUE. Ignored otherwise.- type
a schema type such as "DATABASE", "VALUE" or "TABLE". See the API reference for a list of all schema types.
Functions
sc_schema_flatten(): turns asc_schemaobject into adata.framesc_schema_catalogue(): is similar to the catalogue explorer of the STATcube GUI and reurns a tree-type object containing all databases and tables.sc_schema_db(): is similar to the table view of ths STATcube GUI and gives information about all measures and classification fields for a specific database
Printing with data.tree
limit and ... will simply be ignored if tree is set to FALSE, which is
the default. The printing via data.tree can take longer than the default
implementation because x will need to be converted into a data.tree node.
To use data.tree printing permanently, use
options(STATcubeR.print_tree = TRUE)Examples
my_catalogue <- sc_schema_catalogue()
## print
my_catalogue
#> FOLDER: Extern V9
#> # A data frame: 6 × 3
#> child type n_childs
#> <chr> <chr> <int>
#> 1 Examples FOLDER 9
#> 2 Publications and services FOLDER 2
#> 3 Default Tables FOLDER 0
#> 4 Statistics FOLDER 20
#> 5 meineErsteTabelle TABLE 0
#> 6 meineZweiteTabelle TABLE 0
## access the parsed catalogue
my_catalogue$Statistics$`Labour Market`
#> FOLDER: Labour Market
#> # A data frame: 15 × 3
#> child type n_childs
#> <chr> <chr> <int>
#> 1 Job Seeker FOLD… 0
#> 2 Labour Market Policy FOLD… 0
#> 3 Working Time FOLD… 0
#> 4 Selected Labour Market Indicators FOLD… 0
#> 5 Activity Status FOLD… 0
#> 6 Employment FOLD… 0
#> 7 Job Vacancies FOLD… 4
#> 8 Working hours (Labour Force Survey) DATA… 0
#> 9 Austrian Micro census - Labour Force Survey Yearly … DATA… 0
#> 10 Austrian Micro census - Labour Force Survey Quarter… DATA… 0
#> 11 Mikrozensus-Zeitreihe ab 1974 DATA… 0
#> 12 Standardtabelle / Default table (defaulttable_deake… TABLE 0
#> 13 Standardtabelle / Default table (defaulttable_deake… TABLE 0
#> 14 Standardtabelle / Default table (defaulttable_deake… TABLE 0
#> 15 Standardtabelle / Default table (defaulttable_deake… TABLE 0
my_catalogue$Statistics$`Labour Market`$`Working hours (Labour Force Survey)`
#> DATABASE: Working hours (Labour Force Survey)
#> # Get more info with `STATcubeR::sc_schema_db('str:database:deake005')`
db_schema <- sc_schema_db("deake005")
# printing
db_schema
#> DATABASE: Working hours (Labour Force Survey)
#> # A data frame: 8 × 3
#> child type n_childs
#> <chr> <chr> <int>
#> 1 Factors GROUP 9
#> 2 Datensätze/Records GROUP 1
#> 3 Time (mandatory field) GROUP 1
#> 4 Demographic Characteristics GROUP 8
#> 5 Employment Characteristics GROUP 6
#> 6 Working Time GROUP 5
#> 7 Characteristics of second employment GROUP 6
#> 8 Geographic Characteristics GROUP 1
# access child nodes
db_schema$`Demographic Characteristics`
#> GROUP: Demographic Characteristics
#> # A data frame: 8 × 3
#> child type n_childs
#> <chr> <chr> <int>
#> 1 Gender FIELD 1
#> 2 Age in years-groups FIELD 3
#> 3 Highest level of training completed (national classi… FIELD 2
#> 4 Highest level of training completed (ISCED 97) FIELD 2
#> 5 Highest level of training completed (ISCED 2011) FIELD 2
#> 6 Nationality FIELD 2
#> 7 Country of birth FIELD 2
#> 8 Migration background FIELD 2
db_schema$`Demographic Characteristics`$Gender$Gender
#> VALUESET: Gender
#> # A data frame: 3 × 3
#> child type n_childs
#> <chr> <chr> <int>
#> 1 male VALUE 0
#> 2 female VALUE 0
#> 3 Not classifiable <0> VALUE 0
db_schema$`Demographic Characteristics`$Gender$Gender$male
#> VALUE: male
# access the raw response from httr::GET()
my_response <- attr(db_schema, "response")
my_response$headers$date
#> [1] "Thu, 18 Apr 2024 10:03:04 GMT"
my_content <- httr::content(my_response)
my_content$label
#> [1] "Working hours (Labour Force Survey)"
# print with data.tree
"str:group:deake005:X_B1" %>%
sc_schema(depth = "valueset") %>%
print(tree = TRUE)
#> levelName type
#> 1 Demographic Characteristics GROUP
#> 2 ¦--Gender FIELD
#> 3 ¦ °--Gender VALUESET
#> 4 ¦ ¦--male VALUE
#> 5 ¦ ¦--female VALUE
#> 6 ¦ °--Not classifiable <0> VALUE
#> 7 ¦--Age in years-groups FIELD
#> 8 ¦ ¦--Age in years-groups VALUESET
#> 9 ¦ ¦ ¦--Under 15 years VALUE
#> 10 ¦ ¦ ¦--15 to 19 years VALUE
#> 11 ¦ ¦ ¦--20 to 24 years VALUE
#> 12 ¦ ¦ ¦--25 to 29 years VALUE
#> 13 ¦ ¦ ¦--30 to 34 years VALUE
#> 14 ¦ ¦ ¦--35 to 39 years VALUE
#> 15 ¦ ¦ ¦--40 to 44 years VALUE
#> 16 ¦ ¦ ¦--45 to 49 years VALUE
#> 17 ¦ ¦ ¦--50 to 54 years VALUE
#> 18 ¦ ¦ ¦--55 to 59 years VALUE
#> 19 ¦ ¦ ¦--60 to 64 years VALUE
#> 20 ¦ ¦ ¦--65 to 69 years VALUE
#> 21 ¦ ¦ ¦--70 to 74 years VALUE
#> 22 ¦ ¦ ¦--75 years and older VALUE
#> 23 ¦ ¦ °--Not classifiable <0> VALUE
#> 24 ¦ ¦--Alter in Jahresgruppen VALUESET
#> 25 ¦ ¦ ¦--Under 15 years VALUE
#> 26 ¦ ¦ ¦--15 to 24 years VALUE
#> 27 ¦ ¦ ¦--25 to 34 years VALUE
#> 28 ¦ ¦ ¦--35 to 44 years VALUE
#> 29 ¦ ¦ ¦--45 to 54 years VALUE
#> 30 ¦ ¦ °--... 3 nodes w/ 0 sub
#> 31 ¦ °--... 1 nodes w/ 6 sub
#> 32 °--... 6 nodes w/ 80 sub