Workflow Automation Templates
A library of ready-to-use workflow templates to accelerate your data journey
Date Time Feature Extraction
Extract and transform date-time features
Overview
This workflow converts date and time information into meaningful numerical features for machine learning models. It extracts components such as year, month, and day, and also computes age-like values from date fields for advanced temporal analysis.
Details
The workflow starts by loading the Bike-Sharing dataset. The DateTime Field Extract node breaks down datetime values into components like year, month, and day, enabling models to capture time-based patterns. Simultaneously, the Date To Age node transforms date fields into numerical age values to represent durations or time differences.
The results from both transformations are displayed using Print N Rows nodes for validation. This process enhances feature richness and enables better handling of time-related data in modeling workflows.