# Jupyter

> Create and execute Jupyter notebooks for interactive data analysis using jupyter_execute and jupyter_notebook tools

- Skill: `zaoqu-liu/jupyter` (Agent Skill)
- Install (CLI): `npx skillmds@latest add zaoqu-liu/jupyter`
- Raw SKILL.md: https://api.skillmd.com/api/skills/zaoqu-liu/jupyter/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: zaoqu-liu (https://skillmd.com/u/zaoqu-liu)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/zaoqu-liu/jupyter

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# Jupyter Notebook Skill

## Description
Create and execute Jupyter notebooks for interactive data analysis and visualization.

## Tools Used
- `jupyter_execute` - Execute Python code in Jupyter kernel (auto-switches to Jupyter)
- `jupyter_notebook` - Create, read, update, delete, and list notebooks
- `update_notebook` - Add or update cells in the notebook without executing
- `update_gallery` - Display generated plots and visualizations in gallery view
- `update_data_grid` - Display structured tabular data (DataFrames, query results) in AG Grid
- `update_code` - Show code examples and scripts in the Code Playground
- `save_artifact` - Save generated artifacts (plots, data files) to workspace collection

## Capabilities

- Create new notebooks with proper structure
- Add and execute code cells
- Add markdown documentation cells
- Display inline visualizations
- Display tabular data in interactive grid view
- Show code examples with syntax highlighting
- Export to various formats (HTML, PDF)

## Usage Patterns

### Create Analysis Notebook
When user says: "Create a notebook for [analysis]"
1. Create notebook with title and imports
2. Add data loading cell
3. Add exploration cells
4. Structure with markdown headers
5. Execute cells sequentially

### Execute and Debug
When user says: "Run this code"
1. Execute cell
2. Capture output and errors
3. If error, diagnose and fix
4. Show results or visualizations

### Document Workflow
When user says: "Add explanation for this step"
1. Add markdown cell before code
2. Explain methodology
3. Note assumptions and limitations

## Best Practices

1. **Cell Independence**: Each cell should run independently when possible
2. **Import First**: All imports at notebook start
3. **Clear Outputs**: Clean outputs before sharing
4. **Markdown Structure**: Use headers for navigation
5. **Save Often**: Checkpoint regularly