De-Normalize Column

This transform will convert the normalized values back to their original scale or units.

tags: [“Data Preparation”]

Parameters

The table gives a brief description about each parameter in Cut Column transform.

Name:

By default, the transform name is populated. You can also add a custom name for the transform.

Input Dataset:

The input dataset to de-normalize. You can select this dataset from the drop-down list. (Required: True, Multiple: False)

Denormalized Dataset:

The file name of the de-normalized dataset. (Required: True, Multiple: False)

Column:

The column to be de-normalized. (Required: True, Multiple: False, Datatypes: [“STRING”], Options: [‘FIELDS’], Datasets: [‘df’])

The sample input for this transform looks as below:

The output after running the De-Normalize Column transform on the dataset appears as below:

How to use it in Notebook

The following is the code snippet you must use in the Jupyter Notebook editor to run the De-Normalize Column transform:

template=TemplateV2.get_template_by('De-Normalize Column')

recipe_De_Normalize_Column= project.addRecipe([car_data, employee_data, temperature_data, only_numeric], name='De-Normalize Column')

transform=Transform()
transform.templateId = template.id
transform.name='De-Normalize Column'
transform.variables = {
'input_dataset':'car',
'output_dataset':'car_den',
'col':"boreratio"}
recipe_De_Normalize_Column.add_transform(transform)
recipe_De_Normalize_Column.run()

Requirements

pandas