Markdown Table Generator
Build Markdown tables with a visual editor. Add rows and columns, set column alignment (left, center, right), and type content directly into cells. The tool generates properly formatted Markdown table syntax that you can copy and paste into any Markdown document or README file.
| Header 1 | Header 2 | Header 3 |
| :--- | :--- | :--- |
| | | |
| | | |
| | | |About Markdown Table Generator
- Visual editing — Edit cells directly in the table grid
- Column alignment — Click alignment buttons to cycle between Left, Center, and Right
- Tab navigation — Use Tab to move between cells
- All processing happens locally in your browser
How to Use
- 1
Set Table Size
Use the row and column controls to set your table dimensions.
- 2
Fill in Content
Click cells to edit their content. Use Tab to navigate between cells.
- 3
Set Alignment
Choose left, center, or right alignment for each column using the alignment buttons.
- 4
Copy Markdown
Copy the generated Markdown table syntax and paste it into your document.
Examples by Niche
Create a parameters table: | Name | Type | Required | Description |
Build a feature comparison table for a README or product page
Format research data or metrics into a clean Markdown table
Frequently Asked Questions
How do I set column alignment?
Each column has alignment buttons (left, center, right) in the header. This controls the separator row syntax (:---, :---:, ---:) in the generated Markdown.
What is the maximum table size?
You can create tables with up to 20 rows and 20 columns. For larger data sets, consider using CSV or a spreadsheet tool.
Can I paste data from a spreadsheet into the table editor?
You can manually enter data cell by cell in the visual editor. For large datasets, consider using the JSON to CSV or CSV to JSON converters first, then format the output as a Markdown table.
Where can I use Markdown tables?
Markdown tables work on GitHub READMEs, GitLab, Bitbucket, Notion, Jira, Confluence, dev.to, and most documentation platforms that support Markdown. They are especially common in API documentation, changelogs, and comparison charts.
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