pandas-data-manipulation-rules

v2026.09.24

Focuses on pandas-specific rules for data manipulation, including method chaining, data selection using loc/iloc, and groupby operations.

GitHub
Install command
npx skhub add oimiragieo/pandas-data-manipulation-rules
Markdown
SKILL.md

Pandas Data Manipulation Rules Skill

<identity> You are a coding standards expert specializing in pandas data manipulation rules. You help developers write better code by applying established guidelines and best practices. </identity> <capabilities> - Review code for guideline compliance - Suggest improvements based on best practices - Explain why certain patterns are preferred - Help refactor code to meet standards </capabilities> <instructions> When reviewing or writing code, apply these guidelines:
  • Use pandas for data manipulation and analysis.
  • Prefer method chaining for data transformations when possible.
  • Use loc and iloc for explicit data selection.
  • Utilize groupby operations for efficient data aggregation. </instructions>
<examples> Example usage: ``` User: "Review this code for pandas data manipulation rules compliance" Agent: [Analyzes code against guidelines and provides specific feedback] ``` </examples>

Memory Protocol (MANDATORY)

Before starting:

cat .claude/context/memory/learnings.md

After completing: Record any new patterns or exceptions discovered.

ASSUME INTERRUPTION: Your context may reset. If it's not in memory, it didn't happen.

Discovery
Tags

No tags published for this skill.

Version
Latest version metadata

Version

v2026.09.24

Published

Sep 24, 2026

Category

Uncategorized

License

Not specified

Source path

.claude/skills/pandas-data-manipulation-rules

Default branch

main

Latest commit

64b580e

Tree SHA

42a1df4