univariate-analysis
OfficialQuickly explore distributions and feature power
Data & Analytics#data quality#credit risk#univariate analysis#feature binning#IV computation#WoE table#cross distribution
Authoraliyun
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill helps you quickly understand how one or a few features are distributed and, when you have a binary target, how predictive each feature is via IV and bin-level details.
Core Features & Use Cases
- Single-feature distribution analysis: Compute binning-based distribution tables (quantile/interval binning), basic stats, and data quality flags like high missing rate or low cardinality.
- Cross-feature distribution (optional): Analyze the joint distribution of exactly two features using a binned cross table.
- Feature screening with a target: When a binary target is provided, compute IV, generate the best binning/IV table (WoE, IV per bin), and produce keep/drop suggestions.
- Use cases: Before modeling, rapidly inspect feature behavior, detect problematic columns, and shortlist variables for credit-risk / finance-style supervised learning.
Quick Start
Ask the AI to run univariate-analysis on your dataset file, analyzing the feature columns you specify and (optionally) computing IV against your binary target column.
Dependency Matrix
Required Modules
numpypandasoptbinning
Components
scripts
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: univariate-analysis Download link: https://github.com/aliyun/qwen-dianjin/archive/main.zip#univariate-analysis Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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