The column values match test can help verifying that key attributes or features in your dataset remain consistent over time or across different datasets.
If you are writing a tests.json, here are a few valid configurations for the character length test:
Copy
Ask AI
[ { "name": "Values in `output` and `target` match", "description": "Make sure that rows in your two datasets have the same values for target_column_name where reference_column_name is also the same", "type": "consistency", "subtype": "columnValuesMatch", "thresholds": [ { "insightName": "columnValuesMatch", "insightParameters": [ { "name": "reference_column_name", "value": "output" }, // Selects the column `output` as the reference column { "name": "target_column_name", "value": "target" } // Selects the column `target` as the target column ], "measurement": "failingRowPercentage", // Must be one of `failingRowPercentage` or `failingRowCount` "operator": "<=", "value": 0.0 } ], "subpopulationFilters": null, "mode": "development", "usesValidationDataset": true, "usesTrainingDataset": true, "usesMlModel": false, "syncId": "b4dee7dc-4f15-48ca-a282-63e2c04e0689" // Some unique id }]