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# data\_designer.engine.processing.processors.drop\_columns

## Module Contents

### Classes

| Name                                                                                               | Description                                                |
| -------------------------------------------------------------------------------------------------- | ---------------------------------------------------------- |
| [`DropColumnsProcessor`](#data_designerengineprocessingprocessorsdrop_columnsdropcolumnsprocessor) | Drops specified columns from the dataset after each batch. |

### Data

[`logger`](#data_designerengineprocessingprocessorsdrop_columnslogger)

### API

```python
logger = getLogger(...)
```

```python
class data_designer.engine.processing.processors.drop_columns.DropColumnsProcessor(
    config: data_designer.engine.configurable_task.TaskConfigT,
    resource_provider: data_designer.engine.resources.resource_provider.ResourceProvider
)
```

**Bases**: `data_designer.engine.processing.processors.base.Processor[data_designer.config.processors.DropColumnsProcessorConfig]`

Drops specified columns from the dataset after each batch.

```python
_resolve_columns(available: pandas.Index) -> list[str]
```

Expand column\_names entries (including glob patterns) against available columns.

```python
process_after_batch(
    data: pandas.DataFrame,
    *,
    current_batch_number: int | None
) -> pandas.DataFrame
```

```python
_save_dropped_columns(
    data: pandas.DataFrame,
    resolved: list[str],
    current_batch_number: int
) -> None
```