JSON to CSV Converter

How to convert JSON to CSV

An API response such as [{"name":"Ada","age":36}] is easy for software to read but less useful as a table. JSON to CSV preserves each record as a row, so you can inspect fields and pass the result to a system that accepts CSV.

1. You can add JSON. Paste an array of objects, a single object, or JSON Lines. The converter reads the keys and builds columns.
2. You can choose the separator. Comma, semicolon, tab, and pipe separators cover common spreadsheet and import formats. The matching separator keeps each field in the right column.
3. You can review and save CSV. Check the preview, then copy the table or download data.csv. A quick review catches missing keys and unexpected nested values before another system reads the file.

What JSON and CSV contain

What is JSON?

JSON stores values in objects with named keys, arrays, and nested structures. For example, an array with one object for each person maps naturally to rows, while each key becomes a possible column.

What is CSV?

CSV stores a table as text, with one record per line and fields separated by a chosen character. Commas, semicolons, tabs, and pipes are useful because the receiving spreadsheet or data system can split the same rows consistently.

Sample JSON and CSV

[
  {"Name": "Ada", "Age": 36, "City": "London"},
  {"Name": "Lin", "Age": 29, "City": "Taipei"}
]

Name,Age,City
Ada,36,London
Lin,29,Taipei

The two objects share the keys Name, Age, and City, so those keys become the header row. The same pattern works for API records with different values, but a missing key can produce an empty cell that deserves a quick review.

Common JSON to CSV problems

Nested data does not form separate columns

A nested value such as {"address":{"city":"London"}} is not a flat field. The converter keeps that object in one cell, which preserves the value but does not create a column for every nested key.

Leading zeros change after opening CSV

A value such as 00123 can lose its zeros when a spreadsheet guesses that the field is a number. Keep the source value quoted and check the column type after opening the file, because the conversion itself does not remove the zeros.

All values appear in one column

A separator mismatch causes this result, for example when a semicolon file is read as comma separated. The selected Value Separator must match the file or receiving system so fields split into the intended columns.

Text characters look wrong

Accented characters can look incorrect when the source uses a different encoding from the text you pasted. UTF-8 is the clearest shared choice for JSON and CSV because it represents a broad range of characters consistently.

Convert JSON to CSV in code

import csv, json
rows = json.load(open("data.json"))
w = csv.DictWriter(open("out.csv","w",newline=""), fieldnames=rows[0])
w.writeheader(); w.writerows(rows)

This example expects an array of objects with shared keys. A stable key set helps the code create predictable headers and rows.