> ## 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.

# RowDataSource

> Data source for explainability analysis using a single row of data.

Data source for explainability analysis using a single row of data.

RowDataSource allows you to perform explainability analysis on a specific
data row by providing the row data directly. This is useful when you want
to explain a particular prediction or analyze feature importance for a
specific instance without referencing stored data.

This data source type is ideal for real-time explanations, ad-hoc analysis,
or when you have specific data points that you want to analyze independently
of your stored datasets.

## Examples

Creating a row data source for a loan application:

```python theme={null}
row_source = RowDataSource(
    row={
        "age": 35,
        "income": 75000,
        "credit_score": 720,
        "employment_years": 8,
        "loan_amount": 250000
    }
)
```

Creating a row data source for image classification:

```python theme={null}
image_row_source = RowDataSource(
    row={
        "image_features": [0.1, 0.5, 0.3, ...],
        "metadata": "product_image_001.jpg",
        "category": "electronics"
    }
)
```

## source\_type

## row

## model\_config

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