Pandas data wrangling
Skill MarieLynneBlock/arcanum-artifex/skills/data-science/pandas-data-wrangling
Prompts, skills, and agents that survive contact with real workflows. No vendor loyalty. Occasionally heretical. 🧙🏻♀️
npx -y skills add MarieLynneBlock/arcanum-artifex --skill pandas-data-wranglingAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
2 things to look at
- no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
- 2 stars2 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
What its author says it does
Copied from the file, not written here
[TODO] Define the specific workflow this skill standardises, including default libraries, quality checks, and expected deliverables.
SKILL.md
1.2 KB, as published. Nobody here has run it
What this skill does
[TODO] Define the specific workflow this skill standardises, including default libraries, quality checks, and expected deliverables.
When to use it
[TODO] List concrete user intents and trigger phrases that should activate this skill.
Instructions
- Clarify the objective, data assumptions, and success metrics.
- Execute a leakage-safe and reproducible workflow for this skill domain.
- Validate outputs with diagnostics, edge-case checks, and documented caveats.
Output format
- A concise plan of action
- Executable code or commands
- Validation summary with assumptions and risks
Examples
Example 1 - baseline workflow
Input: User asks for help in pandas-data-wrangling. Expected output: A reproducible, validated workflow using the skill's core tools.
Notes
- Prefer documented, stable APIs over experimental shortcuts.
- Record assumptions explicitly when data quality or labels are uncertain.