Workflow Automation Templates
A library of ready-to-use workflow templates to accelerate your data journey
Basic Feature Building
Create features through filtering & grouping
Overview
This workflow demonstrates simple feature engineering techniques to transform raw housing data into meaningful insights using filtering and aggregation methods.
Details
The process starts by reading the housing dataset and filtering relevant columns using the Column Filter node. Rows with prices above a defined threshold (e.g., 4500) are retained with the Row Filter node to focus on higher-value properties.
Next, the Group By node aggregates the filtered data to compute the average house price by the number of bedrooms. The Print N Rows nodes are used throughout to preview intermediate and final results.
This example illustrates foundational steps in feature creation, preparing clean and structured data that enhances analytical accuracy and model effectiveness.