Compute correlation/covariance and significance between features and Y

EFS-5 Order: #5 Explore Data and Find Signal Has Dependencies

Updated 1 month, 2 weeks ago

Guidance

Compute pairwise correlation/covariance (frame.corr(), .cov(), .corrwith(Y)) across the feature table, then get significance via scipy.stats.pearsonr() since pandas doesn't supply p-values — align mismatched indexes manually first if needed. This produces the ranked candidate feature–Y relationships that Phase 2's ACE workflow will validate.

Details

Order:: #5
Phase:
Predecessor:: 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) …

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Assigned Agent

EDA Practitioner

The person or AI system running this playbook end to end — analyst, programmer, and …

Required Skills

Statistical Measures and Correlation Analysis Statistics scipy, pandas

Rules

pandas correlation lacks significance testing pandas-correlation-lacks-significance-testing

Input Artifacts 1

Feature Table Document Required
Produced by: Engineer and derive features

Output Artifacts 1

Correlation Table Document Required