SmartMarkdown

Excel to Markdown Table Converter

Upload an Excel, LibreOffice, or CSV spreadsheet and convert any sheet into a clean GitHub-Flavored Markdown table. Pick the sheet, preview the rendered result, set column alignment, and copy or download — all parsed locally in your browser.

Upload Spreadsheet

Drop your spreadsheet here

or click to browse

.XLSX,.XLS,.CSV,.ODS files supported

Supports .xlsx, .xls, .ods and .csv. Formula results are read as static values. Everything is parsed locally — no upload.

Markdown Table Output

Upload a spreadsheet to convert the active sheet into a Markdown table.

Reviewers

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166 people find this tool helpful

What This Tool Does

This converter reads a spreadsheet file and turns a selected sheet into a GitHub-Flavored Markdown pipe table. It is built for the everyday task of moving tabular data out of Excel and into documentation, a README, or a pull request — without exporting to CSV, screenshotting, or hand-typing pipes.

How to Use It

  1. Drop or browse for an .xlsx, .xls, .ods, or .csv file.
  2. Choose a sheet if the workbook has more than one.
  3. Toggle the header option and set per-column alignment.
  4. Copy or download the Markdown table.

Multi-Sheet Workbooks

Workbooks frequently hold several related sheets — quarterly figures, a summary tab, reference data. The sheet picker lets you convert whichever one you need, with its own header row and alignment, and switch between them instantly. Each conversion is independent so you can export several tables from a single file.

Values, Formulas & Formats

Cells are read as their displayed, formatted values. Formula cells contribute their cached results rather than the formula text, and number formats (dates, currency, percentages) are preserved as shown. This produces a Markdown table that matches what you see on screen in the spreadsheet application.

Common Use Cases

  • Reference tables: status codes, config parameters, or pricing tiers maintained in Excel.
  • Reporting: KPI and summary tables embedded in technical reports or wikis.
  • Data review: dropping a sample dataset into a PR or issue for discussion.
  • Migration: moving spreadsheet-based docs into a Markdown-first repo.

Tips

  • Unmerge cells and fill in values before uploading for the most accurate output.
  • Keep the first row as clean column headers — avoid blank or merged header spans.
  • Trim the data range to what you actually want; you can also delete unwanted rows in the output editor afterward.

FAQ

Frequently Asked Questions