> ## Documentation Index
> Fetch the complete documentation index at: https://docs.wandb.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Map columns in datasets

> Map columns in datasets to different names. This helps you align the column names in your dataset with the column names expected by the scorer.

<Tabs>
  <Tab title="Python">
    In the Weave Python SDK, use the `column_map` attribute on a scorer to map its expected parameter names to your dataset's column names. The mapping format is `{scorer_parameter: dataset_column}`.

    The following example maps the `output` and `target` parameters to a dataset's `model_output` and `answer` columns:

    ```python theme={null}
    from weave.scorers import EmbeddingSimilarityScorer

    similarity_scorer = EmbeddingSimilarityScorer()

    similarity_scorer.column_map = {
        "output": "model_output",  # The model's generated text
        "target": "answer"         # The expected or reference response
    }
    ```

    For more details on scorer column mapping, see [Mapping Column Names with `column_map`](../evaluation/scorers#mapping-column-names-with-column_map).
  </Tab>

  <Tab title="TypeScript">
    In the Weave TypeScript SDK, column mapping is configured on the `Evaluation` object using the `columnMapping` option, not on individual scorers. The mapping format is `{scorer_key: dataset_column}`.

    The following example maps `expectedOutputTimesTwo` (used by the scorer) to the `expected` column in the dataset:

    ```typescript theme={null}
    import * as weave from 'weave';

    const myScorer = weave.op(
      ({modelOutput, datasetRow}) => {
        return modelOutput * 2 === datasetRow.expectedOutputTimesTwo;
      },
      {name: 'myScorer'}
    );

    const myEval = new weave.Evaluation({
      id: 'my-evaluation',
      dataset: [{expected: 2}],
      scorers: [myScorer],
      columnMapping: {expectedOutputTimesTwo: 'expected'},
    });
    ```

    For more details on TypeScript scorer arguments, see [Scorer Keyword Arguments](../evaluation/scorers#scorer-keyword-arguments).
  </Tab>
</Tabs>