JSON to Markdown Table: Convert JSON Arrays Instantly

Why Convert JSON to Markdown?

Markdown tables are useful for documentation, README files, GitHub wikis, and static site generators. If your data lives in JSON, converting it to Markdown lets you include live data in docs without manually formatting tables.

JavaScript: JSON Array to Markdown Table

function jsonToMarkdownTable(arr) {
  if (!arr.length) return '';
  const headers = Object.keys(arr[0]);
  const divider = headers.map(() => '---').join(' | ');
  const rows = arr.map(row =>
    headers.map(h => String(row[h] ?? '')).join(' | ')
  );
  return [
    headers.join(' | '),
    divider,
    ...rows
  ].join('\n');
}

const data = [
  { name: 'Alice', age: 30, city: 'NYC' },
  { name: 'Bob', age: 25, city: 'London' }
];
console.log(jsonToMarkdownTable(data));
// name | age | city
// --- | --- | ---
// Alice | 30 | NYC
// Bob | 25 | London

Python: JSON to Markdown Table

def json_to_markdown_table(data):
    if not data:
        return ''
    headers = list(data[0].keys())
    rows = [[str(row.get(h, '')) for h in headers] for row in data]
    
    header_row = ' | '.join(headers)
    divider = ' | '.join(['---'] * len(headers))
    body_rows = ['\n'.join(' | '.join(row) for row in rows)]
    
    return f'{header_row}\n{divider}\n' + '\n'.join(' | '.join(row) for row in rows)

import json
with open('data.json') as f:
    data = json.load(f)
print(json_to_markdown_table(data))

Handling Nested Values

function flatten_for_table(arr) {
  return arr.map(row => {
    const flat = {};
    for (const [key, val] of Object.entries(row)) {
      if (typeof val === 'object' && val !== null) {
        flat[key] = JSON.stringify(val); // Serialize nested as JSON string
      } else {
        flat[key] = val;
      }
    }
    return flat;
  });
}

Using tabulate in Python

from tabulate import tabulate
import json

with open('data.json') as f:
    data = json.load(f)

# GitHub Flavored Markdown
print(tabulate(data, headers='keys', tablefmt='github'))

# Pipe format
print(tabulate(data, headers='keys', tablefmt='pipe'))

FAQ