N Root Column

This transform finds the specific root of every element in a column of the dataset (which can be 2nd root of a number, 4th of a number, 8th of a number, and so on).

tags: [“Data Preparation”]

Parameters

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

Name:

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

Input Dataset:

The file name of the input dataset. You can select the dataset that was uploaded from the drop-down list. (Required: True, Multiple: False)

Output Dataset:

The file name with which the output dataset is created. This contains the nth root of every element in the given column. (Required: True, Multiple: False)

Column:

The name of the column to which the nth root must be applied. (Required: True, Multiple: False, Datatypes: [“STRING”], Options: [“FIELDS”], Datasets: [“df”])

N Root:

The specific number to be applied as a root to every element in the given column. (Required: True, Multiple: False, Datatypes: [“FLOAT”], Options: [“CONSTANT”])

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

../../../_images/nthrootcolumn_input.png

The output after running the N Root Column transform on the dataset appears as below:

../../../_images/nroot_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 N Root Column transform:

template=TemplateV2.get_template_by('N Root Column')

recipe_N_Root_Column= project.addRecipe([car_data, employee_data, temperature_data, only_numeric], name='N Root Column')

transform=Transform()
transform.templateId = template.id
transform.name='N Root Column'
transform.variables = {
'input_dataset':'only_numeric',
'output_dataset':'ncds',
'col':"Age",
'n':5}
recipe_N_Root_Column.add_transform(transform)
recipe_N_Root_Column.run()

Requirements

pandas