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

# Custom SQL Code

> Write and run your own SQL code to transform a tabular dataset in the Monolith platform.

## Description

Custom code enables a user to write and run their own SQL code in order to transform a tabular dataset.

<Note>
  **Advanced functionality, not recommended for inexperienced users**

  This complex feature requires advanced knowledge of SQL code. For assistance, contact our Customer Success team or visit our Support Portal. Also consider using other manipulator steps in combination to achieve your intended result.
</Note>

***

## Application

Even though the platform offers numerous functions to transform tables, users may want to transform their data in a way so specific that no general solution is available. This function will allow such users to manipulate the data with total freedom and flexibility. The function can be used for example to manually modify the values of the table, restructure the table, to create new columns in a complex way.

***

## How to use

<Info>
  Knowledge of SQL code is required for this step.
</Info>

* Select the dataset on which you want to apply the code.
* Write the code in the code section.

Here are a few important points:

* Each snippet of code must contain **FROM \{dataset\_1}** in a single line, to reference the selected dataset
* The code block cannot end with a semi-colon

After your code is written, you have the following options before running the step:

* **Add a description** to your code that will be visible from the notebook (for example, "data filtered in my specific way"). If no description is added, the step will just print the custom code. Especially if the code becomes longer it is highly recommended to add a description instead.
* Enable **Save output under a different name** if the step should not overwrite the initial dataset. If this option is not enabled the dataset will be overwritten.

***

## Examples

The examples below assume using data available for selection in the Tabular loader under *workshop > Other data sets > Automotive Dynamics Track Testing > TrackTesting.csv.*

The initial list of columns in this dataset are

```text theme={"system"}
name, time, steeringtorque, steeringangle, wheelfront_forcex, wheelfront_forcey, wheelfront_forcez, wheelfront_momentx, wheelfront_momenty, wheelfront_momentz, wheelrear_forcex, wheelrear_forcey, wheelrear_forcez, wheelrear_momentx, wheelrear_momenty, wheelrear_momentz, car_accelerationx, car_accelerationy, car_accelerationz, car_velocity, car_angle
```

Renaming a column

```text theme={"system"}
SELECT name AS test_id, time
FROM {dataset_1}
```

Select/Reorder columns

```text theme={"system"}
SELECT test_id, time, steeringtorque, steeringangle, car_accelerationx, car_accelerationy, car_accelerationz, car_velocity, car_angle
FROM {dataset_1}
```

Remove missing values

```text theme={"system"}
SELECT * FROM {dataset_1} 
WHERE NOT (car_angle IS NULL AND car_velocity IS NULL)
```

Remove duplicates

```text theme={"system"}
SELECT DISTINCT test_id, time, steeringtorque, steeringangle, car_accelerationx, car_accelerationy, car_accelerationz, car_velocity, car_angle
FROM {dataset_1}
```

Random subset

```text theme={"system"}
SELECT * FROM {dataset_1}
WHERE RAND() <= 0.6
```

Group by

```text theme={"system"}
SELECT test_id, MAX(car_angle) AS max_car_angle
FROM {dataset_1}
GROUP BY test_id
```

Sort by

```text theme={"system"}
SELECT test_id, time, steeringtorque, steeringangle, car_accelerationx, car_accelerationy, car_accelerationz, car_velocity, car_angle
FROM {dataset_1}
ORDER BY test_id, time
```

Filter numeric values

```text theme={"system"}
SELECT test_id, time, steeringtorque, steeringangle, car_accelerationx, car_accelerationy, car_accelerationz, car_velocity, car_angle
FROM {dataset_1}
WHERE steeringangle BETWEEN -50 AND 50
```

Clip values

```text theme={"system"}
SELECT
    test_id,
    time,
    steeringtorque,
    CASE
        WHEN steeringangle < -50 THEN -50
        WHEN steeringangle > 50 THEN 50
        ELSE steeringangle
    END AS steeringangle,
    car_accelerationx,
    car_accelerationy,
    car_accelerationz,
    car_velocity,
    car_angle
FROM {dataset_1}
```