Validation Correction Checks — validation

Validation correction tests to be run on data before and after validation to test expectations.

Usage

validation_checks(validation_log, before_data, after_data, idcol)

Arguments

validation_log: tibble Validation log
before_data: tibble Data before corrections
after_data: tibble Data after corrections
idcol: character the primary key for the 'after_data'

Value

NULL if passed or stops with error

Details

As part of the OH cleaning pipelines, raw data is converted to 'semi-clean' data through a process of upserting records from an external Validation Log. To ensure these corrections were made as expected, some checks are performed in this function.

If no existing log exists > no changes are make to data
- Same variables
- same Rows
- No unequal values
If log exists but no changes are recommended > no changes to data.
- Same variables
- same Rows
- No unequal values
Log exists and changes recommended > number of changes are same as log
- Same variables
- same Rows
- Number of changing records in data match records in log
Correct fields and records are being updated
- Checks before and after variables and rows are the same
- Checks the variable names and row indexes are the same in the logs and the changed data.

Examples

if (FALSE) { # \dontrun{
    validation_checks(
    validation_log = kzn_animal_ship_existing_log,
    before_data = kzn_animal_ship,
    after_data = kzn_animal_ship_semiclean,
    idcol = "animal_id"
    )
} # }