# Train Test Split

Label rows as part of the train or test set based off of percentage split you want to apply to the data.

If you want a row-wise random sample applied, do not pass an order\_by column. If you want an ordered split, then pass the order\_by column.

## Parameters

| Name           | Type         | Description                                                                                                                                              | Is Optional |
| -------------- | ------------ | -------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------- |
| order\_by      | column\_list | Optional argument that affects the train/test split method applied. if needed, pass the names of column(s) you want to order by when applying the split. | True        |
| train\_percent | int          | Percent of the data you want in the train set, expressed as a decimal (i.e. .8). The rest of the rows will be included in the test set.                  |             |

## Example

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

ds2 = ds.train_test_split(order_by = ['DATE'],
    train_percent = 0.8)
ds2.preview()

ds2b = ds.train_test_split(train_percent = 0.8)
ds2b.preview()
```

## Source Code

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


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.rasgoml.com/rasgo-docs/rasgo-0.1/all-transforms/train_test_split.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
