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

# DatasetDataSource

> Data source for explainability analysis using a sample from a dataset.

Data source for explainability analysis using a sample from a dataset.

DatasetDataSource allows you to perform explainability analysis on a random
sample of data from a specified environment/dataset. This is useful for
understanding general model behavior, analyzing feature importance patterns
across multiple instances, or getting representative explanations.

This data source type is ideal for exploratory analysis, understanding overall
model behavior, or when you want to analyze explanations across a representative
sample rather than specific instances.

## Examples

Creating a dataset data source for production sampling:

```python theme={null}
dataset_source = DatasetDataSource(
    env_type="PRODUCTION",
    num_samples=100,
    env_id="prod_dataset_uuid"
)
```

Creating a dataset data source for validation analysis:

```python theme={null}
validation_source = DatasetDataSource(
    env_type="VALIDATION",
    num_samples=50
)
```

Creating a dataset data source with default sampling:

```python theme={null}
default_source = DatasetDataSource(
    env_type="PRODUCTION"
)
```

## source\_type

## env\_type

## num\_samples

## env\_id

## model\_config

Configuration for the model, should be a dictionary conforming to \[ConfigDict]\[pydantic.config.ConfigDict].