{
    "action": "final",
    "content": "**No column in `raw.iris` has any missing values.** The null-count query over all 150 rows returned 0 missing and 0.0% for every column:\n\n- `sepal_length`, `sepal_width`, `petal_length`, `petal_width`: 0 missing (0.0%)\n- `species`: 0 missing (0.0%)\n- The metadata columns `_ingestion_timestamp`, `_batch_id`, `_source_file` and `_source_system`: 0 missing\n\nThe dataset is fully populated, so you don't need imputation or row-dropping before using the four measurements or the species label. The check looks only for NULLs. It does not test for placeholder values such as empty strings or zeros, which would need a separate check."
}