> For the complete documentation index, see [llms.txt](https://hwasumok.gitbook.io/r-flow/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://hwasumok.gitbook.io/r-flow/r/data-preprocess/normalize.md).

# Normalize

bestNormalize, Arcsinh Transformation, Box-Cox Normalization, Lambert W x F Normalization,log Transformation, sqrt Normalization, Yeo-Johnson Normalization, Transform Normalize

## Common

### Input Data

|                    | Inputs                                                                                                                                    |
| ------------------ | ----------------------------------------------------------------------------------------------------------------------------------------- |
| **Target Data**    | Input data                                                                                                                                |
| **Output Name**    | Name of the output after normalization                                                                                                    |
| **Normalize info** | Short description of the work. It should not contain spaces.                                                                              |
| **sample**         | Number of samples. 400 by default                                                                                                         |
| **x**              | <p>Variables to normalize. Only numeric or integer types will show up.</p><p>Drag the variables from the table and drop them under X.</p> |

### Statistic & p\_value

The two variables are the result of **Shapiro-Wilk test**. The null hypothesis of the Shapiro-Wilk test is that the data is normally distributed. If the p-value is greater than the alpha level, the null hypothesis cannot be rejected therefore indicating that the data is normally distributed. The program will run the test again with the given sample number whenever you click the green arrow button.

![\[Task information of Normalize\]](https://3929524962-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-MGaxNdSdRN_L_WNiX4I%2F-MJIBLJODX3-hdp5Xjjg%2F-MJIiUy1FgDSF5CT3UTK%2Fimage.png?alt=media\&token=e4f5477c-1180-46ea-9fa3-dc2ca5c592ce)

## Transformation Normalize

This task is used to mitigate the influence of the heavy-tailed distributions while preserving the 1-1 nature of the transformation.&#x20;

### Input Data

|                    | Inputs                                                                                                                                                                                                                                        |
| ------------------ | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| **Target Data**    | Input (vector-like) data                                                                                                                                                                                                                      |
| **Output Name**    | Name of the output after Transformation Normalize                                                                                                                                                                                             |
| **Normalize info** | <p>Normalize Info of 'Normalize' task generated before doing 'Transform Normalize' task . </p><ul><li>The 'Normalize info.' of the 'Transform Normalize' task should be the same as the 'Normalize info.' of the 'Normalize' task. </li></ul> |

### How to Use

1. Use vector-like data as input for the normalization
2. Use other 'Normalize' tasks such as 'bestNormalize' to normalize the input value
3. Then, Transform\_Normalize can be used.&#x20;

![\[Task Information of Transformation Normalize\]](https://3929524962-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-MGaxNdSdRN_L_WNiX4I%2F-MLjae_CtoP2aoPb_Czf%2F-MLji3B9LwQZC9TIfkDG%2Fimage.png?alt=media\&token=96371850-d782-48f9-b971-a0324a74ed89)

## Workflow Example

[**R-Flow Task Example Video**](https://youtu.be/51vPGieh6zc) **- Transform Normalize**

![](https://3929524962-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-MGaxNdSdRN_L_WNiX4I%2F-MLjae_CtoP2aoPb_Czf%2F-MLjhx5psqvS2WIAOrYX%2Fimage.png?alt=media\&token=17698e36-ec25-4744-8498-001f1ae05da4)

## R Package

**Best Normalize:** <https://cran.r-project.org/web/packages/bestNormalize/index.html>

**Arcsinh Transformation, Box-Cox Normalization, Lambert W x F Normalization,log Transformation, sqrt Normalization, Yeo-Johnson Normalization**: <https://cran.r-project.org/web/packages/bestNormalize/vignettes/bestNormalize.html>