Drop Columns Transform

Drop Columns removes fields that the rest of the workflow does not need.

Basic Usage

To drop one or more columns:

1. Select Drop Columns from the transform menu.
2. In the "Columns to drop" field, select the columns to remove.
3. Select Apply.

Configuration Options

Basic Options

• Columns to Drop: Select one or more columns to remove from the dataset.

Examples

Example: Removing Personal Information

Input Dataset:

ID	Name	Age	City	Salary
1	Alice	30	New York	75000
2	Bob	35	Los Angeles	80000
3	Charlie	28	Chicago	70000

Configuration:

• Columns to drop: Age, Salary

Result:

ID	Name	City
1	Alice	New York
2	Bob	Los Angeles
3	Charlie	Chicago

caution

Dropped columns are no longer available to downstream nodes. Before applying the transform, check that no later step needs them.

Best Practices

1. Drop large, unused columns early to keep the rest of the workflow smaller.
2. Before removing identifying fields, check whether distinct rows will then look identical.
3. If the workflow is shared or audited, note why each column was removed.