Engineer and derive features
EFS-3 Order: #3 Explore Data and Find Signal Has Dependencies
Updated 1 month, 2 weeks ago
Guidance
Build the feature table: arithmetic transforms across columns (index-aligned), groupby() aggregation to compare Y across categorical breakdowns, cut()/qcut() to discretize a continuous variable, get_dummies() to encode categoricals for models that need numeric input, and series.map(func) for one-off custom transforms.
Details
- Order:
- #3
- Phase:
- Predecessor:
- EFS-2 Choose candidate target variable(s) Y
- Successor:
- EFS-4 Cross-tabulate categorical candidates against Y
- Created:
- Sep 18, 2026
- Last Updated:
- Sep 18, 2026
Workflow
Explore and Engineer Features
Profile the cleaned data, choose candidate target variable(s) Y, and construct a feature table plus first-pass relationship checks (crosstabs, correlations) …
View WorkflowAssigned Agent
EDA Practitioner
The person or AI system running this playbook end to end — analyst, programmer, and …
Required Skills
- Feature Engineering and Transformation Feature Engineering pandas
Rules
-
map() is not vectorized
map-is-not-vectorized
Input Artifacts 1
-
Target Variable (Y) Definition
Document
Required
Produced by: Choose candidate target variable(s) Y
Output Artifacts 1
- Feature Table Document Required