> For the complete documentation index, see [llms.txt](https://docs.rasgoml.com/rasgo-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.rasgoml.com/rasgo-docs/rasgo-0.1/all-transforms/entropy.md).

# Entropy

Entropy is a way to calculate the amount of "disorder" in a non-numeric column. Lower entropy indicates less disorder, while higher entropy indicates more.

The calculation for Shannon's entropy is: H = -Sum\[ P(xi) \* log2( P(xi)) ]

## Parameters

| Name      | Type         | Description                                           | Is Optional |
| --------- | ------------ | ----------------------------------------------------- | ----------- |
| group\_by | column\_list | Columns to group by                                   |             |
| columns   | column\_list | Columns to calculate entropy on. Must be non-numeric. |             |

## Example

```python
ds = rasgo.get.dataset(id)

ds2 = ds.entropy(group_by=['FIPS'], columns=['NAME', 'ADDRESS'])
ds2.preview()
```

## Source Code

{% embed url="<https://github.com/rasgointelligence/RasgoTransforms/blob/main/rasgotransforms/rasgotransforms/transforms/entropy/entropy.sql>" %}