Back to JSON Formatter
Converter Guide

How the JSON to CSV Converter Works

Flatten nested JSON into spreadsheet-ready data

bryanthaboi
January 7, 2026
4 min
jsoncsvconversiondata-export

CSV (Comma-Separated Values) is the lowest common denominator of data formats. Every spreadsheet app, database tool, and data analysis platform can read it. The challenge? JSON is hierarchical; CSV is flat.

The Flattening Process

Nested objects are flattened using dot notation. A property at user.address.city becomes a column named 'user.address.city'. This preserves the structure information while creating a flat table.

Nested JSONJSON
{
  "user": {
    "name": "John",
    "address": {
      "city": "NYC",
      "zip": "10001"
    }
  }
}
Flattened CSV HeadersText
user.name,user.address.city,user.address.zip
John,NYC,10001

Array Handling

Arrays can't be flattened into columns without losing information. The converter serializes arrays as JSON strings within the CSV cell. This preserves the data while keeping the row structure intact.

name,tags
Project A,"[""urgent"",""frontend""]"

Column Discovery

The converter scans ALL objects in the array to discover every possible column. This means if only the 5th object has a 'nickname' field, it still becomes a column with empty values for other rows.

Special Character Escaping

CSV has specific escaping rules for values containing commas, quotes, or newlines. The converter handles all of these automatically.

ContentEscaped OutputRule
Contains comma"value, here"Wrap in quotes
Contains quote"say ""hello"""Double the quotes, wrap
Contains newline"line1\nline2"Wrap in quotes
Normal textnormalNo escaping needed

Single Object Handling

If you pass a single object instead of an array, the converter wraps it in an array automatically. You'll get a CSV with one header row and one data row.

Column Sorting

Columns are sorted alphabetically in the output. This provides consistent ordering regardless of how the JSON keys were originally arranged.

CSV cannot represent deeply nested structures elegantly. For complex hierarchical data, consider YAML or keeping it as JSON. CSV works best for tabular data with 1-2 levels of nesting.