Description
The Drop Columns activity removes one or more specified columns from the dataset.
It is typically used to clean up unwanted fields, reduce data size, or eliminate sensitive or irrelevant information before further processing or export.
Use case: When exporting customer data for reporting, drop internal system fields such as JSON metadata or nested structures that are not needed by the end user.
| Input Type | Description |
|---|
| Data | A tabular dataset with all fields |
Output
| Output Type | Description |
|---|
| Data | Returns the same dataset minus the specified columns. |
Configuration Fields
| Field Name | Required | Description |
|---|
| Columns | Yes | A list of column names to drop. Multiple selections allowed. |
| employee_id | name | age | department | designation | salary | contact | skills | contact_email | contact_phone | contact_address | name_first_name | name_last_name | emp_name |
|---|
| E001 | {“first_name”:“John”,“last_name”:“Doe”} | 32 | Sales | Sales Manager | 75000 USD | {“email”:“[email protected]”,…} | [“Communication”,“CRM”] | [email protected] | +1-555-1234 | {“street”:“123 Elm St”,…} | John | Doe | John Doe |
| E002 | {“first_name”:“Jane”,“last_name”:“Smith”} | 28 | Engineering | Software Developer | 85000$ | {“email”:“[email protected]”,…} | [“Python”,“React”] | [email protected] | +1-555-5678 | {“street”:“456 Maple Ave”,…} | Jane | Smith | Jane Smith |
Sample Configuration
| Field | Value |
|---|
| Columns | name, contact, name_first_name, name_last_name |
Sample Output
| employee_id | age | department | designation | salary | skills | contact_email | contact_phone | contact_address | emp_name |
|---|
| E001 | 32 | Sales | Sales Manager | 75000 USD | [“Communication”,“CRM”] | [email protected] | +1-555-1234 | {“street”:“123 Elm St”,…} | John Doe |
| E002 | 28 | Engineering | Software Developer | 85000$ | [“Python”,“React”] | [email protected] | +1-555-5678 | {“street”:“456 Maple Ave”,…} | Jane Smith |
