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How to Transform Data Using IF–ELSE Rules

Transforming data with IF–ELSE rules means applying conditional logic to create new features or categories from existing data. This approach helps convert raw numeric values into more meaningful, human-readable groups that support analysis and decision-making.

Data TransformationData basics how-to
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Workflow
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How to Transform Data Using IF–ELSE Rules

How This Workflow Works

This workflow demonstrates how to use rule-based logic to generate new categorical features from numeric data. It guides you through applying conditional expressions and then reviewing the transformed results.

Key Features:

  • Create new, meaningful categories from numeric data
  • Apply custom business logic to automate feature engineering
  • Simplify complex datasets for easier analysis
  • Review and validate the results interactively

Step-by-step:

1. Apply Rule-Based Logic: 

Conditional expressions are used to define new features based on the values in your data. By setting up IF–ELSE rules, you can group numeric values into categories that reflect business logic or analytical needs.

2. Review Transformed Data: 

After applying the rules, you can view the updated dataset to confirm that the new categories have been created as intended. This step allows you to check the logic and ensure the results align with your goals.

How to Get Started