I am using Great Expectations in my ETL data pipeline for a POC. I have a validation which is failing (as expected), and I have the following data in my validation JSON:
"unexpected_count": 205,
"unexpected_percent": 10.25,
"unexpected_percent_nonmissing": 10.25,
"unexpected_percent_total": 10.25
Is there a way to identify/segregate these bad records (depicted as unexpected_count)?