data-science-notebooks
Interactive Notebooks
Use this skill for creating reproducible, well-structured notebooks for data exploration, analysis, and communication.
When to use this skill
- Exploratory analysis — interactively investigate data
- Reproducible research — document methodology with code and results
- Teaching/demos — explain concepts with executable examples
- Stakeholder communication — share insights with narrative + visuals
- Prototyping — quickly iterate on data transformations or models
Tool selection
| Tool | Best For | Key Feature |
|---|---|---|
| JupyterLab | Traditional data science, extensions ecosystem | Full IDE experience |
| marimo | Reproducible notebooks, reactive execution | Python-native, version-control friendly |
| VS Code + Jupyter | IDE-native notebook experience | Intellisense, debugging, git integration |
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