JSON to CSV Converter

Convert JSON arrays to CSV

JSON is useful for APIs and application data, while CSV is easier to open in spreadsheets, import into databases, and process with command-line tools. This converter accepts a JSON array of objects, discovers columns from every object, and writes one CSV row per array element.

Basic example

Input:

[
  {"name": "Alice", "age": 30},
  {"name": "Bob", "city": "London"}
]

Output:

name,age,city
Alice,30,
Bob,,London

Headers use the order in which keys first appear. Missing properties become empty cells, so records with different shapes can still be exported as one table.

Delimiter choices

Delimiter	Common use	Example
Comma	General CSV files and most APIs	name,age
Semicolon	Locales where comma is a decimal separator	name;age
Tab	Spreadsheet paste and TSV workflows	name<TAB>age
Pipe	Data containing many commas	`name

Select the delimiter expected by the destination application. A file can be valid CSV while still importing incorrectly if spreadsheet locale settings expect a different separator.

Quoting and nested values

CSV cells containing a delimiter, quotation mark, or line break are wrapped in double quotes. A quotation mark inside a quoted cell is represented by two quotation marks:

[
  {"name": "Ada", "note": "He said \"hello\"", "tags": ["math", "logic"]}
]

name,note,tags
Ada,"He said ""hello""","[""math"",""logic""]"

Objects and arrays are serialized as JSON text inside one cell. Flatten nested data first when the destination requires one scalar value per column.

Generate CSV in code

JavaScript

const rows = [
  { name: "Alice", age: 30 },
  { name: "Bob", city: "London" },
];

const headers = [...new Set(rows.flatMap((row) => Object.keys(row)))];
const csv = [
  headers.join(","),
  ...rows.map((row) => headers.map((header) => row[header] ?? "").join(",")),
].join("\n");

Python

import csv
import json
import sys

rows = json.load(sys.stdin)
headers = list(dict.fromkeys(key for row in rows for key in row))
writer = csv.DictWriter(sys.stdout, fieldnames=headers)
writer.writeheader()
writer.writerows(rows)

Command line

jq -r '(map(keys) | add | unique) as $headers
  | $headers, (.[] | [.[$headers[]]]) | @csv' input.json

Use a library when processing untrusted or very large files in production. It will handle encoding, streaming, and edge cases that are easy to miss in a short script.

Common uses

• Exporting API responses for spreadsheet review
• Preparing JSON records for database imports
• Converting configuration data for legacy systems
• Creating TSV or pipe-delimited files for data pipelines
• Sharing browser-local data without uploading it

Conversion happens locally in the browser. The tool does not validate a business schema, infer data types, or flatten nested structures; it only maps JSON object keys and values into escaped CSV cells.