Normalization column

This transforms the values in a specific column to a specified range, usually between 0 and 1 using a simple formula and is applicable only to numeric datasets.

tags: [“Data Preparation”]

Parameters

The table gives a brief description about each parameter in Normalize dataset 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 be normalized. You can select this dataset from the drop-down list. (Required: True, Multiple: False)

Column:

The column that should be normalized.

Output Dataset:

The file name with which the normalized Dataset is created. (Required: True, Multiple: False)

The sample input for this transform looks as shown in the screenshot:

../../../_images/normalize_input.png

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

../../../_images/normalize_output.png

How to use it in Notebook

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

template=TemplateV2.get_template_by('Normalize dataset')

recipe_Normalize_dataset= project.addRecipe([car_data, employee_data, temperature_data, only_numeric], name='Normalize dataset')

transform=Transform()
transform.templateId = template.id
transform.name='Normalize dataset'
transform.variables = {
'input_dataset':'only_numeric',
'output_dataset':'only_numeric_norm'}
recipe_Normalize_dataset.add_transform(transform)
recipe_Normalize_dataset.run()

Requirements

pandas