numeric_distribution_check
OfficialValidate numeric and categorical field distributions in structured data.
Data & Analytics#data quality#data validation#distribution analysis#field analysis#statistical checks
Authorcas-bigdatalab
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill automates the validation of numeric and categorical field distributions in structured data files, helping users ensure data quality and integrity.
Core Features & Use Cases
- Numeric Distribution Validation: Check statistical measures like mean, standard deviation, median, and percentiles for numeric fields.
- Categorical Frequency Validation: Analyze the frequency distribution of categorical fields for anomalies in category count and single category dominance.
- Use Case: When you need to verify that your data meets certain statistical or categorical criteria, such as a specific range for numerical values or a reasonable distribution of categories.
Quick Start
Run the numeric_distribution_check skill with the input file 'data.csv', output file 'checked.csv', and specify 'numeric' as the mode.
Dependency Matrix
Required Modules
pandas
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: numeric_distribution_check Download link: https://github.com/cas-bigdatalab/piflow/archive/main.zip#numeric-distribution-check Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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