JSON to Markdown Table

Paste JSON or CSV — get a Markdown table with alignment control and column selection.

Input
Markdown Output
Paste JSON or CSV above to generate a Markdown table.

How to Convert JSON to a Markdown Table

  1. Choose a mode — "Array → Table" for JSON arrays of objects, "Object → Table" for a single JSON object, or "CSV → Table" for comma-separated data.
  2. Paste your data into the input area or click "Try Example" to load sample data.
  3. Adjust columns — after parsing, checkboxes let you exclude columns, and alignment badges cycle through Left, Center, and Right.
  4. Copy or Download the finished Markdown.

What Is a Markdown Table?

A Markdown table uses pipe characters (|) as column separators and a separator row of dashes to define the header boundary. Column alignment is set in the separator row: :--- for left, :---: for center, ---: for right. Most Markdown renderers — GitHub, GitLab, Notion, Obsidian, and VS Code — support the GFM (GitHub Flavored Markdown) table specification that this tool generates.

Input Format Details

  • Array mode — expects a JSON array of flat objects. Nested objects are JSON-stringified into a single cell. All unique keys across all objects become columns; missing values render as empty cells.
  • Object mode — converts a single JSON object into a two-column Key/Value table. Useful for configuration summaries or metadata blocks.
  • CSV mode — expects a header row followed by data rows. Commas inside quoted fields ("a,b") are handled correctly. Rows with fewer columns than the header are padded with empty cells.

Column Alignment

Alignment matters for readability in rendered tables. Left-align descriptive text columns, right-align numeric columns (scores, prices, counts), and center-align short labels or status values. Click the alignment badge next to each column name to cycle through the three options — the Markdown output regenerates immediately.

Supported Markdown Renderers

This tool generates GFM tables which are supported in: GitHub READMEs and wikis, GitLab Markdown, Bitbucket, Confluence (with Markdown macro), Notion, Obsidian, Typora, VS Code preview, Hugo, Jekyll, Gatsby, Docusaurus, and most other Markdown-based documentation systems. If your renderer does not support tables, consider our JSON Formatter to display data as structured JSON instead.

Common Use Cases

  • API documentation — convert a JSON schema or example response into a readable parameters table.
  • GitHub README — display features, comparisons, or changelogs as a formatted table.
  • Sprint reports — paste a CSV export from Jira or Linear and generate a Markdown table for a daily standup or retrospective document.
  • Config documentation — convert environment variable objects into a two-column reference table.
  • Data exploration — quickly visualise a small dataset from a REST API without spinning up a spreadsheet.

Limitations and Edge Cases

Markdown tables are designed for flat, tabular data. Deeply nested JSON objects are serialised as JSON strings inside cells, which can make the table hard to read. For nested data, consider flattening with a tool like JSON Formatter first. Very wide tables (20+ columns) render poorly on mobile screens — use column selection to show only the most important fields. Cells containing pipe characters (|) are automatically escaped to prevent breaking the table structure.

Frequently Asked Questions

This tool accepts three input formats: JSON arrays of objects (the most common), JSON objects (converted to a two-column key/value table), and CSV text (comma-separated values with a header row). Select the appropriate mode chip before pasting your data.
After conversion, click on any alignment badge next to a column name. Each click cycles through Left (:---), Center (:---:), and Right (---:) alignment for that column independently. The Markdown output updates immediately.
Yes. When converting a JSON array, checkboxes appear below the tool for every field found in your data. Uncheck any field to exclude that column from the generated Markdown table.
No. Everything runs in your browser using JavaScript. Your JSON or CSV data never leaves your machine — there is no server, no API call, and no logging.
Markdown tables are supported in GitHub READMEs, GitLab, Bitbucket, Notion, Confluence, Obsidian, VS Code preview, Reddit, and most static site generators (Jekyll, Hugo, Gatsby). They are the standard way to display tabular data in documentation.