DATASET DROP COLUMNS¶
Removes one or more columns from a dataset by name or regex pattern. Use this worker to clean up unwanted or redundant columns before downstream processing or model training.
When to use¶
Classification: process.
Tagged: column_removal, dataset_cleaning, drop_columns, transformation.
Inputs¶
| Label | ID | Type | Default | Required | Description |
|---|---|---|---|---|---|
| Dataset | dataset_1 | dataset | — | Input dataset from which columns will be dropped; accepts any tabular dataset available in the workflow. | |
| CSV Column Names | column_names_regex | scalar | — | Comma-separated list of column names or regex patterns identifying the columns to remove; can also be selected interactively from the dataset’s column list. |
Outputs¶
| Label | ID | Type | Description |
|---|---|---|---|
| dataset_drop_columns_output_1 | dataset_drop_columns_output_1 | dataset | Resulting dataset with the specified columns removed; all other columns and rows are preserved unchanged. |
Disciplines¶
- data.dataset.transform
Runnable example¶
A runnable example is registered for this worker. Open the example workflow on the d3VIEW canvas: /api/workflow/example?id=dataset_drop_columns
Auto-generated from transformation schema. Worker id: dataset_drop_columns. Schema hash: 2bc9f50cc874. Hand-curated docs in workerexamples/ override this page when present.