# eval

```python
dbnl.eval.evaluate(df: DataFrame, metrics: Sequence[Metric], inplace: bool = False) → DataFrame
```

Evaluates a set of metrics on a dataframe, returning an augmented dataframe.

* **Parameters:**
  * **df** – input dataframe
  * **metrics** – metrics to compute
  * **inplace** – whether to modify the input dataframe in place
* **Returns:** input dataframe augmented with metrics

```python
dbnl.eval.get_column_schemas_from_dataframe_and_metrics(df: DataFrame, metrics: list[Metric]) → list[ColumnSchema]
```

Get the run config column schemas for a dataframe that was augmented with a list of metrics.

* **Parameters:**
  * **df** – Dataframe to get column schemas from
  * **metrics** – list of metrics added to the dataframe
* **Returns:** list of columns schemas for dataframe and metrics

```python
dbnl.eval.get_column_schemas_from_metrics(metrics: list[Metric]) -> list[ColumnSchema]
```

Get the run config column schemas from a list of metrics.

* **Parameters:** **metrics** – list of metrics to get column schemas from
* **Returns:** list of column schemas for metrics