Returns an overview of available metadata for a given dataset.
nomis_overview(id, select = NULL)
The ID of the particular dataset. Returns no data if not specified.
A string or character vector of one or more overview parts to
select, excluding all others. select
is not case sensitive. The
options for select
are described below, and are taken from the
Nomis API help page.
A tibble with two columns, one a character vector with the name of the metadata category, and the other a list column of values for each category.
General dataset information such as name, description, sub-description, mnemonic, restricted access and status
Shows the geographic coverage of the main geography dimension in this dataset (e.g. United Kingdom, England and Wales etc.)
The keywords allocated to the dataset
The units of measure supported by the dataset
The classifications allocated to this dataset
Information about the first release, last update and next update
Details for the point of contact for this dataset
Show the available analysis breakdowns of this dataset
Individual dimension information (e.g. sex, geography, date, etc.)
Allows a specific dimension to be selected (e.g. dimension-geography would allow information about geography dimension). This is not used if "Dimensions" is specified too.
Full list of selectable codes, excluding Geography, which as a list of Types instead. (Requires "Dimensions" to be selected too)
Full list of selectable codes for a specific dimension, excluding Geography, which as a list of Types instead. This is not used if "Codes" is specified too (Requires "Dimensions" or equivalent to be selected too)
Any available metadata attached at the dimensional level (Requires "Dimensions" or equivalent to be selected too)
Information about whether user defined codes can be created with the MAKE parameter when querying data (Requires "Dimensions" or equivalent to be selected too)
Metadata attached at the dataset level
# \donttest{
library(dplyr)
#>
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#>
#> filter, lag
#> The following objects are masked from ‘package:base’:
#>
#> intersect, setdiff, setequal, union
q <- nomis_overview("NM_1650_1")
q %>%
tidyr::unnest(name) %>%
glimpse()
#> Rows: 21
#> Columns: 2
#> $ name <chr> "analyses", "analysisname", "analysisnumber", "contact", "conten…
#> $ value <list> [[<data.frame[3 x 3]>]], "output data for a single date or rang…
s <- nomis_overview("NM_1650_1", select = c("Units", "Keywords"))
s %>%
tidyr::unnest(name) %>%
glimpse()
#> Rows: 3
#> Columns: 2
#> $ name <chr> "id", "keywords", "units"
#> $ value <list> "NM_1650_1", "Year last worked", [["Persons"]]
# }