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:
The output after running the Normalize dataset 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 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