Query a data set using POST and a query json
post_dataset.RdThis function provides a method for generating and sending a json based data query to the EES API. As a minimum, it requires the dataset_id flag and either the indicators flag or a json file containing a query to be provided.
Usage
post_dataset(
dataset_id,
indicators = NULL,
time_periods = NULL,
geographies = NULL,
filter_items = NULL,
json_query = NULL,
dataset_version = NULL,
ees_environment = NULL,
api_version = NULL,
page = NULL,
page_size = 10000,
parse = TRUE,
debug = FALSE,
verbose = FALSE
)Arguments
- dataset_id
ID of data set to be connected to. This is required if the endpoint is one of "get-summary", "get-meta", "get-csv", "get-data" or "post-data"
- indicators
Indicators required as a string or vector of strings (required)
- time_periods
Time periods required as a string ("period|code") or vector of strings
- geographies
String, vector or data frame containing the geographic levels and locations to be queried.
- filter_items
Filter items required as a string or vector of strings
- json_query
Optional path to a json file containing the query parameters
- dataset_version
Version of data set to be connected to
- ees_environment
EES ees_environment to connect to: "dev", "test", "preprod" or "prod"
- api_version
EES API version
- page
Page number of query results to return
- page_size
Number of results to return in a single query
- parse
Logical flag to activate parsing of the results. Default: TRUE
- debug
Run POST query in debug mode. Logical, default = FALSE
- verbose
Run with additional contextual messaging. Logical, default = FALSE
Examples
post_dataset(
example_id(group = "attendance"),
json_query = example_json_query()
)
#> code period geographic_level nat_name nat_code reg_name reg_code
#> 1 W23 2024 REG England E92000001 North East E12000001
#> 2 W23 2024 REG England E92000001 North East E12000001
#> 3 W23 2024 REG England E92000001 North West E12000002
#> 4 W23 2024 REG England E92000001 North West E12000002
#> 5 W23 2024 REG England E92000001 North East E12000001
#> 6 W23 2024 REG England E92000001 North East E12000001
#> 7 W23 2024 REG England E92000001 North West E12000002
#> 8 W23 2024 REG England E92000001 North West E12000002
#> attendance_status attendance_type day_number education_phase
#> 1 Absence Authorised Total Secondary
#> 2 Absence Unauthorised Total Secondary
#> 3 Absence Authorised Total Secondary
#> 4 Absence Unauthorised Total Secondary
#> 5 Absence Authorised Total Total
#> 6 Absence Unauthorised Total Total
#> 7 Absence Authorised Total Total
#> 8 Absence Unauthorised Total Total
#> attendance_reason session_count
#> 1 Total 53326
#> 2 Total 64441
#> 3 Total 152262
#> 4 Total 167394
#> 5 Total 107165
#> 6 Total 117871
#> 7 Total 273327
#> 8 Total 273633
# Run post_dataset() to select rows containing either of two geographic locations and a single
# filter item.
post_dataset(
example_id(group = "attendance"),
indicators = example_id("indicator", group = "attendance"),
time_periods = example_id("time_period", group = "attendance"),
geographies = example_id("location_code", group = "attendance"),
filter_items = example_id("filter_item", group = "attendance"),
page = 1,
page_size = 32
)
#> code period geographic_level nat_name nat_code attendance_status
#> 1 W23 2024 NAT England E92000001 Absence
#> 2 W23 2024 NAT England E92000001 Absence
#> 3 W23 2024 NAT England E92000001 Absence
#> 4 W23 2024 NAT England E92000001 Absence
#> 5 W23 2024 NAT England E92000001 Absence
#> 6 W23 2024 NAT England E92000001 Absence
#> 7 W23 2024 NAT England E92000001 Absence
#> 8 W23 2024 NAT England E92000001 Absence
#> 9 W23 2024 NAT England E92000001 Absence
#> 10 W23 2024 NAT England E92000001 Absence
#> 11 W23 2024 NAT England E92000001 Absence
#> 12 W23 2024 NAT England E92000001 Absence
#> 13 W23 2024 NAT England E92000001 Absence
#> 14 W23 2024 NAT England E92000001 Absence
#> 15 W23 2024 NAT England E92000001 Absence
#> 16 W23 2024 NAT England E92000001 Absence
#> 17 W23 2024 NAT England E92000001 Absence
#> 18 W23 2024 NAT England E92000001 Absence
#> 19 W23 2024 NAT England E92000001 Absence
#> 20 W23 2024 NAT England E92000001 Absence
#> 21 W23 2024 NAT England E92000001 Absence
#> 22 W23 2024 NAT England E92000001 Absence
#> 23 W23 2024 NAT England E92000001 Absence
#> 24 W23 2024 NAT England E92000001 Absence
#> attendance_type day_number education_phase attendance_reason
#> 1 Unauthorised 1 Special G unauthorised holiday
#> 2 Unauthorised 1 Primary G unauthorised holiday
#> 3 Unauthorised 1 Secondary G unauthorised holiday
#> 4 Unauthorised 2 Special G unauthorised holiday
#> 5 Unauthorised 2 Primary G unauthorised holiday
#> 6 Unauthorised 2 Secondary G unauthorised holiday
#> 7 Unauthorised 3 Secondary G unauthorised holiday
#> 8 Unauthorised 3 Special G unauthorised holiday
#> 9 Unauthorised 3 Primary G unauthorised holiday
#> 10 Unauthorised 4 Secondary G unauthorised holiday
#> 11 Unauthorised 4 Primary G unauthorised holiday
#> 12 Unauthorised 4 Special G unauthorised holiday
#> 13 Unauthorised 5 Secondary G unauthorised holiday
#> 14 Unauthorised 5 Special G unauthorised holiday
#> 15 Unauthorised 5 Primary G unauthorised holiday
#> 16 Unauthorised Total Special G unauthorised holiday
#> 17 Unauthorised Total Primary G unauthorised holiday
#> 18 Unauthorised Total Secondary G unauthorised holiday
#> 19 Unauthorised 2 Total G unauthorised holiday
#> 20 Unauthorised 3 Total G unauthorised holiday
#> 21 Unauthorised 4 Total G unauthorised holiday
#> 22 Unauthorised 5 Total G unauthorised holiday
#> 23 Unauthorised Total Total G unauthorised holiday
#> 24 Unauthorised 1 Total G unauthorised holiday
#> session_count
#> 1 1574
#> 2 84811
#> 3 44458
#> 4 1443
#> 5 98308
#> 6 37788
#> 7 33274
#> 8 1372
#> 9 86219
#> 10 29610
#> 11 75852
#> 12 1345
#> 13 29339
#> 14 1410
#> 15 77983
#> 16 7144
#> 17 423173
#> 18 174469
#> 19 137539
#> 20 120865
#> 21 106807
#> 22 108732
#> 23 604786
#> 24 130843