Compute descriptive statistics per candidate variable
EFS-1 Order: #1 Explore Data and Find Signal Has Dependencies
Updated 1 month, 2 weeks ago
Guidance
For every candidate variable, compute sum/mean/median/std/count/min/max (with skipna), sort/rank it, and look at cumulative/period-over-period measures (cumsum, diff) and uniqueness/value_counts for categoricals. This is the "smell and sense of the data" step before you commit to any Y or feature.
Details
- Order:
- #1
- Phase:
- Successor:
- EFS-2 Choose candidate target variable(s) 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
- Descriptive Statistics and Ranking Exploratory Analysis pandas, numpy
Rules
No rules linked.
Input Artifacts 1
-
Clean Working DataFrame
Document
Required
Produced by: Reshape data for the framing questions
Output Artifacts
No output artifacts