Jupyter Notebook to Markdown - Data Science Documentation

Convert Jupyter notebooks (.ipynb) to Markdown for documentation, tutorials, GitHub. Preserve code, output cells, plots. Perfect for data science workflows.

Note: First conversion initializes Pandoc WebAssembly (~55MB). Subsequent conversions are instant.

Upload Jupyter Notebook

Drop .ipynb file here or click to browse

Jupyter notebook files only

Include output cells

Strip all outputs (code only)

Markdown Output

Preview

Upload a notebook to see preview

Jupyter Notebook Features

Notebook Element	Markdown Conversion	Notes
Markdown cells	Plain Markdown text	Preserved exactly with headings, lists, etc.
Code cells	Fenced code blocks	Language syntax highlighting preserved
Output cells	Code blocks or text	Can be included or stripped via option
Plots/Images	Markdown image syntax	Base64 or referenced images
LaTeX math	LaTeX notation	$...$ and $$...$$ preserved
Tables	Markdown tables	Simple tables convert cleanly
HTML output	HTML code blocks	Rendered widgets shown as HTML
Metadata	Stripped	Focus on content, not execution metadata

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Frequently Asked Questions

Jupyter notebooks are interactive documents that combine executable code, visualizations, and narrative text in a single file. Popular in data science, machine learning, and scientific computing for documenting analysis workflows, creating tutorials, and sharing reproducible research.

Markdown is ideal for documentation, GitHub README files, blog posts, and static site generators. Converting notebooks to Markdown makes your analysis more accessible, searchable, and portable while preserving code, outputs, and narrative explanations.

Code cells are converted to fenced code blocks with appropriate language syntax highlighting (Python, R, Julia). The code is preserved exactly as written, making it easy to copy or reference in documentation.

Yes, by default output cells (results, print statements, tables) are included as text or code blocks. You can choose to strip outputs for cleaner documentation that focuses only on the code and narrative.

Plot images embedded in the notebook are converted to Markdown image syntax. Base64-encoded images are preserved inline, while external images reference their paths. Most matplotlib, seaborn, and plotly outputs convert cleanly.

Yes. Use the 'Strip outputs' option to remove all code execution results, leaving only code cells and markdown text. Perfect for creating code-focused tutorials or documentation where readers should run the code themselves.

Absolutely. All conversion happens locally in your browser using WebAssembly. Your notebooks, data, and outputs never leave your device and are not uploaded to any server. Perfect for confidential research or proprietary analysis.

LaTeX math notation (both inline $...$ and display $$...$$) is preserved in the Markdown output. The equations will render correctly on GitHub, in static site generators with MathJax, and in Markdown editors that support math.

Yes. Jupyter notebooks support multiple kernels (Python, R, Julia, etc.). The converter preserves code cells with the appropriate language syntax highlighting based on the notebook's kernel metadata.

DataFrame output typically renders as HTML tables in notebooks. These convert to Markdown tables or code blocks depending on the output format. For best results, use DataFrame.to_markdown() in your notebooks before conversion.

Jupyter Notebook Features

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