CSV to Markdown Table

Paste CSV, TSV, or semicolon-separated data — get a clean GitHub-flavored Markdown table. Runs in your browser.

Delimiter:

Free. No signup. Browser-only.

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Why this matters

READMEs and docs

GitHub-flavored Markdown tables render natively in READMEs, GitLab, Notion, and most modern doc systems. Paste-ready output.

LLM context windows

Markdown tables are dramatically cheaper in tokens than CSV or pretty JSON. Paste a sliced spreadsheet into ChatGPT or Claude for analysis.

Browser-only, private

No upload, no server. Safe for pasting internal spreadsheets, financial data, or anything else you'd rather not send to a third party.

How it works

1

Paste CSV — or pick a delimiter for TSV or semicolon-separated data

2

We parse it correctly (RFC 4180 quoting, embedded commas, escaped quotes) into a Markdown table

3

Copy the table — drop it into a README, Notion page, or LLM prompt

Frequently Asked Questions

Does this handle quoted fields and commas inside values?

Yes. The parser implements RFC 4180 quoting — fields wrapped in double quotes can contain commas, newlines, and escaped quotes (""). Unquoted fields are split on the chosen delimiter.

Can I use tab-separated (TSV) data?

Yes. There's a delimiter selector — choose between comma, semicolon, or tab. Tab handles TSV files and data pasted from Excel or Google Sheets.

Does it stay in my browser?

Yes. Conversion happens entirely client-side — no upload, no server, no logs. Safe for sensitive spreadsheet data.

What's the output format?

Standard GitHub-flavored Markdown tables — `| col1 | col2 |` with a `| --- | --- |` separator row. Renders correctly in GitHub READMEs, Notion, GitLab, Obsidian, and any modern Markdown processor.

How are pipes and newlines in cells handled?

Pipes are escaped (`\|`) so they don't break the table syntax. Newlines inside a cell are converted to spaces — Markdown tables don't support multi-line cells.

Is there a row limit?

No hard limit, but tables with thousands of rows can be slow to render in some Markdown viewers. For very large CSVs, consider keeping them as CSV and only converting summary slices.

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