Back Fill

This transform will fill the missing or null values with the value succeeding the null value in the dataset. However, this transform is limited to numericals.

tags: [“Data Preparation”]

Parameters

The table gives a brief description about each parameter in Back fill 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 after filling the null values in the dataset value succeeding the missing or null value. (Required: True, Multiple: False)

Sample input for Back Fill transform:

The output after running the Back fill 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 Back Fill transform:

template=TemplateV2.get_template_by('Back Fill')

recipe_Back_Fill= project.addRecipe([car_data, employee_data, temperature_data, only_numeric], name='Back Fill')

transform=Transform()
transform.templateId = template.id
transform.name='Back Fill'
transform.variables = {
'input_dataset':'car',
'output_dataset':'car_bfill'}
recipe_Back_Fill.add_transform(transform)
recipe_Back_Fill.run()

Requirements

pandas