Get data set versions

Usage

get_dataset_versions(
  dataset_id,
  detail = "light",
  ees_environment = NULL,
  api_version = NULL,
  page_size = 40,
  page = NULL,
  verbose = FALSE
)

Arguments

dataset_id

ID of data set to be connected to. This is required if the endpoint is one of "get-dataset-versions", "get-summary", "get-meta", "get-csv", "get-data" or "post-data"

detail

Level of detail to return. Given as a character string, it should be one of: "light" (default) or "full". Using "light" gives the following:

version - version number
type - version type (major or minor)
total_rows - total number of rows in the listed version
release_date - release date of the data set version
release_name - name of the release in which the data set version was published
time_period_start - first available time period in the data
time_period_start - latest available time period in the data

Using "full" adds the following in addition to the above:

version_id - unique ID code for the data set version
status - publication status of the data set version
geographic_levels - geographic levels provided
filters - names of filters in the data set version
indicators - names of indicators in the data set version
notes - any additional information

ees_environment

EES ees_environment to connect to: "dev", "test", "preprod" or "prod"

api_version

EES API version

page_size

Number of results to return in a single query

page

Page number of query results to return

verbose

Run with additional contextual messaging. Logical, default = FALSE

Value

A data frame with X columns:

Data frame listing all available versions of the given data set

Examples

get_dataset_versions(dataset_id = example_id(group = "attendance"))
#>    version  type total_rows release_date release_name time_period_start
#> 1     1.11 Minor    5162258   2025-08-07 Week 29 2025      2024 Week 37
#> 2     1.10 Minor    5020394   2025-07-24 Week 28 2025      2024 Week 37
#> 3      1.9 Minor    4747752   2025-07-10 Week 26 2025      2024 Week 37
#> 4      1.8 Minor    4475018   2025-06-26 Week 24 2025      2024 Week 37
#> 5      1.7 Minor    4202376   2025-06-16 Week 21 2025      2024 Week 37
#> 6      1.6 Minor    4066032   2025-05-29 Week 20 2025      2024 Week 37
#> 7      1.5 Minor    3815654   2025-05-15 Week 18 2025      2024 Week 37
#> 8      1.4 Minor    3583998   2025-05-01 Week 15 2025      2024 Week 37
#> 9      1.3 Minor    3556490   2025-04-17 Week 14 2025      2024 Week 37
#> 10     1.2 Minor    3285734   2025-04-03 Week 12 2025      2024 Week 37
#> 11    1.11 Minor    5162258   2025-08-07 Week 29 2025      2024 Week 37
#> 12    1.10 Minor    5020394   2025-07-24 Week 28 2025      2024 Week 37
#> 13     1.9 Minor    4747752   2025-07-10 Week 26 2025      2024 Week 37
#> 14     1.8 Minor    4475018   2025-06-26 Week 24 2025      2024 Week 37
#> 15     1.7 Minor    4202376   2025-06-16 Week 21 2025      2024 Week 37
#> 16     1.6 Minor    4066032   2025-05-29 Week 20 2025      2024 Week 37
#> 17     1.5 Minor    3815654   2025-05-15 Week 18 2025      2024 Week 37
#> 18     1.4 Minor    3583998   2025-05-01 Week 15 2025      2024 Week 37
#> 19     1.3 Minor    3556490   2025-04-17 Week 14 2025      2024 Week 37
#> 20     1.2 Minor    3285734   2025-04-03 Week 12 2025      2024 Week 37
#>    time_period_end
#> 1     2025 Week 30
#> 2     2025 Week 28
#> 3     2025 Week 26
#> 4     2025 Week 24
#> 5     2025 Week 21
#> 6     2025 Week 20
#> 7     2025 Week 18
#> 8     2025 Week 15
#> 9     2025 Week 14
#> 10    2025 Week 12
#> 11    2025 Week 30
#> 12    2025 Week 28
#> 13    2025 Week 26
#> 14    2025 Week 24
#> 15    2025 Week 21
#> 16    2025 Week 20
#> 17    2025 Week 18
#> 18    2025 Week 15
#> 19    2025 Week 14
#> 20    2025 Week 12