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

# DynamicSelect gem for Data Analysis

> Dynamically filter columns of your dataset based on a set of conditions

export const gemName_0 = "DynamicSelect"

export const execution_engine_0 = "the SQL warehouse"

<Info>This gem runs in {execution_engine_0}.</Info>

## Overview

Use the DynamicSelect gem to dynamically filter columns of your dataset based on a set of conditions to avoid hard-coding your choice of columns.

<Tip>
  The {gemName_0} gem has a corresponding interactive gem example. See [Interactive gem
  examples](/data-analysis/gems/gems#interactive-gem-examples) to learn how to run sample pipelines
  for this and other gems.
</Tip>

## Prerequisites

* Add `prophecy_basics` package version 1.0.0 or higher to your project.

## Parameters

| Parameter     | Description                                                                                                                                                                                                                                                                                           |
| ------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Configuration | Whether to filter the columns visually or with code.<ul><li>Select field types: Use checkboxes to select column types to keep in the dataset, such as string, decimal, or date.</li><li>Select via expression: Create an expression that limits the type of columns to keep in the dataset.</li></ul> |

## Example

Let's say you have the following table with weather prediction data.

<div class="table-example">
  | DatePrediction - `Date` | TemperatureCelsius - `Integer` | HumidityPercent - `Integer` | WindSpeed - `Float` | Condition - `String` |
  | ----------------------- | ------------------------------ | --------------------------- | ------------------- | -------------------- |
  | 2025-03-01              | 15                             | 65                          | 10.0                | Sunny                |
  | 2025-03-02              | 17                             | 70                          | 12.2                | Cloudy               |
  | 2025-03-03              | 16                             | 68                          | 11.0                | Rainy                |
  | 2025-03-04              | 14                             | 72                          | 9.8                 | Sunny                |
</div>

### Remove columns using field type

Assume you would like to remove irrelevant float and string columns from your dataset. You can do so with the **Select field types** method by selecting all field types to maintain, except for float and string.

### Remove columns with an expression

Using the same example, you can accomplish the same task with the **Select via expression** method by inputting the the expression `column_type NOT IN ('Float', 'String')`.

<Note>
  Be aware that column types are case sensitive. Use the same format shown in the input table
  schemas in the gem configuration.
</Note>

### Result

<div class="table-example">
  | DatePrediction - `Date` | TemperatureCelsius - `Integer` | HumidityPercent - `Integer` |
  | ----------------------- | ------------------------------ | --------------------------- |
  | 2025-03-01              | 15                             | 65                          |
  | 2025-03-02              | 17                             | 70                          |
  | 2025-03-03              | 16                             | 68                          |
  | 2025-03-04              | 14                             | 72                          |
</div>