Get Open Data resources from a dataset

Source: R/get_dataset.R

Downloads multiple resources from a dataset on the NHS Open Data platform by dataset name, with optional row limits and context columns.

get_dataset(
  dataset_name,
  max_resources = NULL,
  rows = NULL,
  row_filters = NULL,
  col_select = NULL,
  include_context = FALSE
)

Arguments

dataset_name

Name of the dataset as found on NHS Open Data platform (character).

max_resources

(optional) The maximum number of resources to return (integer). If not set, all resources are returned.

rows

(optional) Maximum number of rows to return (integer).

row_filters

(optional) A named list or vector specifying values of columns/fields to keep (e.g., list(Date = 20220216, Sex = "Female")).

col_select

(optional) A character vector containing the names of desired columns/fields (e.g., c("Date", "Sex")).

include_context

(optional) If TRUE, additional information about the resource will be added as columns to the data, including the resource ID, the resource name, the creation date, and the last modified/updated date.

Value

A tibble with the data.

See also

get_resource() for downloading a single resource from a dataset.

Examples

get_dataset("gp-practice-populations", max_resources = 2, rows = 10)
#> # A tibble: 20 × 59
#>        Date PracticeCode HB       HSCP  Sex   SexQF AllAges AllAgesQF Ages00to04
#>       <int>        <int> <chr>    <chr> <chr> <chr>   <int> <chr>          <int>
#>  1 20251001        10002 S080000… S370… Fema… ""       4328 ""               175
#>  2 20251001        10002 S080000… S370… Male  ""       4163 ""               174
#>  3 20251001        10002 S080000… S370… All   "d"      8491 ""               349
#>  4 20251001        10017 S080000… S370… Fema… ""       3850 ""               119
#>  5 20251001        10017 S080000… S370… Male  ""       3856 ""               130
#>  6 20251001        10017 S080000… S370… All   "d"      7706 ""               249
#>  7 20251001        10036 S080000… S370… Fema… ""       2393 ""                57
#>  8 20251001        10036 S080000… S370… Male  ""       2468 ""                86
#>  9 20251001        10036 S080000… S370… All   "d"      4861 ""               143
#> 10 20251001        10106 S080000… S370… Fema… ""       3318 ""                86
#> 11 20250701        10002 S080000… S370… Male  ""       4134 ""                NA
#> 12 20250701        10002 S080000… S370… Fema… ""       4292 ""                NA
#> 13 20250701        10002 S080000… S370… All   "d"      8426 ""                NA
#> 14 20250701        10017 S080000… S370… Male  ""       3822 ""                NA
#> 15 20250701        10017 S080000… S370… Fema… ""       3854 ""                NA
#> 16 20250701        10017 S080000… S370… All   "d"      7676 ""                NA
#> 17 20250701        10036 S080000… S370… Male  ""       2456 ""                NA
#> 18 20250701        10036 S080000… S370… Fema… ""       2402 ""                NA
#> 19 20250701        10036 S080000… S370… All   "d"      4858 ""                NA
#> 20 20250701        10106 S080000… S370… Male  ""       3115 ""                NA
#> # ℹ 50 more variables: Ages00to04QF <chr>, Ages05to09 <int>,
#> #   Ages05to09QF <chr>, Ages10to14 <int>, Ages10to14QF <chr>, Ages15to19 <int>,
#> #   Ages15to19QF <chr>, Ages20to24 <int>, Ages20to24QF <chr>, Ages25to29 <int>,
#> #   Ages25to29QF <chr>, Ages30to34 <int>, Ages30to34QF <chr>, Ages35to39 <int>,
#> #   Ages35to39QF <chr>, Ages40to44 <int>, Ages40to44QF <chr>, Ages45to49 <int>,
#> #   Ages45to49QF <chr>, Ages50to54 <int>, Ages50to54QF <chr>, Ages55to59 <int>,
#> #   Ages55to59QF <chr>, Ages60to64 <int>, Ages60to64QF <chr>, …