To separate good and bad records, you can utilize the "Split Into Good Bad Records'' node. After adding this node to your workflow following any Great Expectation node, ensure that the input DataFrame is the original DataFrame. Depending on your needs, you can use the "Print N Rows'' or "Save CSV'' node. The split node will segregate all the records into two categories: Good Records and Bad Records.
This node requires an identifier column name from you, which allows you to track good and bad records based on their index.
Hey Nagisa,
To separate good and bad records, you can utilize the "Split Into Good Bad Records'' node. After adding this node to your workflow following any Great Expectation node, ensure that the input DataFrame is the original DataFrame. Depending on your needs, you can use the "Print N Rows'' or "Save CSV'' node. The split node will segregate all the records into two categories: Good Records and Bad Records.
This node requires an identifier column name from you, which allows you to track good and bad records based on their index.