How to Convert JSON to CSV

JSON is the default format for APIs and modern data storage. CSV is what most humans want when they open data — Excel, Google Sheets, and most BI tools read it directly. Converting between the two is a daily task for developers and data analysts.

Mizakii's JSON to CSV converter handles it in one paste — no code, no setup.

How JSON to CSV Conversion Works

CSV is a flat format: rows and columns. JSON can be deeply nested. The conversion only works cleanly when the JSON is an array of objects with consistent keys.

Ideal input (array of objects)

[
  { "name": "Ali Hassan", "email": "ali@example.com", "plan": "pro" },
  { "name": "Jane Doe", "email": "jane@example.com", "plan": "free" },
  { "name": "Bob Smith", "email": "bob@example.com", "plan": "pro" }
]

This maps directly to CSV:

name,email,plan
Ali Hassan,ali@example.com,pro
Jane Doe,jane@example.com,free
Bob Smith,bob@example.com,pro

The keys from the first object become headers. Each object becomes a row.

Common Issues and How to Handle Them

Missing keys in some objects

[
  { "name": "Ali", "email": "ali@example.com", "plan": "pro" },
  { "name": "Jane", "email": "jane@example.com" }
]

Jane has no plan key. Most converters leave the cell empty in that column — which is correct behaviour. The column still appears; the value is just blank.

Nested objects

[
  {
    "name": "Ali",
    "address": { "city": "London", "country": "UK" }
  }
]

Nested objects don't map cleanly to CSV columns. Common solutions:

Flatten: create columns address.city and address.country
Stringify: put the JSON string of the nested object in a single cell
Ignore: drop the nested key entirely

For most reporting use cases, flattening is the most useful option.

Arrays inside objects

[
  { "name": "Ali", "tags": ["developer", "designer"] }
]

Arrays inside objects are even harder to map to CSV — how many columns do you allocate for tags? Common approaches:

Join to a single string: "developer,designer" in one cell
Take only the first value
Drop the key

JSON wrapped in a top-level object

APIs often return:

{
  "data": [
    { "name": "Ali", "email": "ali@example.com" }
  ],
  "total": 1
}

You need to extract the inner array first. Either edit the JSON to pull out the data array before converting, or use a tool that accepts a JMESPath or dot-notation selector.

Convert JSON to CSV in Python

For repeatable conversions, a few lines of Python using the standard library:

import json
import csv

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

# data should be a list of dicts
keys = data[0].keys()

with open('output.csv', 'w', newline='') as f:
    writer = csv.DictWriter(f, fieldnames=keys)
    writer.writeheader()
    writer.writerows(data)

print("Done. output.csv created.")

For nested JSON, use pandas:

import pandas as pd
import json

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

df = pd.json_normalize(data)  # flattens nested objects with dot notation
df.to_csv('output.csv', index=False)

pd.json_normalize handles one level of nesting automatically. For deeper nesting, pass max_level=2 or similar.

When to Use an Online Tool vs Code

| Situation | Best approach | |-----------|--------------| | One-off conversion, simple flat JSON | Online tool | | Repeated conversion (daily/weekly) | Python/Node.js script | | CI/CD pipeline | Code (scripted) | | Large files (100MB+) | Code (streaming) | | Complex nested JSON needing custom logic | Code | | Non-technical user needs the output | Online tool |

For quick, one-off conversions where you just need the CSV to paste into a spreadsheet, an online converter is faster than writing and running a script.

Convert JSON to CSV in Node.js

If you prefer JavaScript or are working in a Node.js pipeline:

const fs = require('fs');

const data = JSON.parse(fs.readFileSync('data.json', 'utf8'));

// Get all unique keys across all objects
const headers = [...new Set(data.flatMap(obj => Object.keys(obj)))];

const csvRows = [
  headers.join(','),
  ...data.map(row =>
    headers.map(header => {
      const val = row[header] ?? '';
      // Wrap in quotes if the value contains a comma, quote, or newline
      const escaped = String(val).replace(/"/g, '""');
      return /[,"\n]/.test(escaped) ? `"${escaped}"` : escaped;
    }).join(',')
  )
];

fs.writeFileSync('output.csv', csvRows.join('\n'));
console.log('Done. output.csv written.');

This handles missing keys (fills blank) and properly escapes values that contain commas or quotes.

Handling Special Characters in CSV

CSV has a few tricky cases that break naive converters:

Values containing commas — the value must be wrapped in double quotes: "London, UK". If your converter doesn't do this, the comma splits into an extra column.

Values containing double quotes — the quote must be escaped by doubling it: "He said ""hello""". A value of He said "hello" becomes "He said ""hello""" in CSV.

Values containing newlines — rare but possible in addresses or multi-line text fields. Must also be wrapped in quotes.

Unicode and non-ASCII characters — CSV has no encoding standard, but UTF-8 is the modern default. If your CSV opens in Excel and shows garbled characters, save with UTF-8 BOM (Excel requires the BOM to detect UTF-8).

Importing the CSV into Excel and Google Sheets

Google Sheets — File → Import → Upload → choose your CSV. Set delimiter to comma. Data imports cleanly.

Excel — double-clicking a CSV usually opens it, but if characters look wrong: Data tab → From Text/CSV → choose your file → set encoding to UTF-8. Don't double-click UTF-8 CSV files with special characters — Excel defaults to a legacy encoding.

Large files — Excel has a 1,048,576 row limit. Google Sheets has a 10 million cell limit. For larger datasets, use a proper database or BI tool (DuckDB, Pandas, Tableau).

Convert JSON to CSV Now

Open Mizakii JSON to CSV →

Paste your JSON array, get a CSV instantly. Copy to clipboard or download the file. Free, no signup, runs in your browser.

How to Convert JSON to CSV (Online, Python, and More)