JSON to CSV Converter

Convert JSON into CSV format directly in your browser for spreadsheet imports, reporting exports, analytics workflows, and quick data cleanup. This page is built for turning arrays of records into rows and columns you can scan, copy, and move into spreadsheet-style tools without sending the data to a remote service.

Data

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Examples

Simple object array to CSV

Input

[{"id":1,"name":"Alice","active":true},{"id":2,"name":"Bob","active":false}]

Output

id,name,active
1,Alice,true
2,Bob,false

Rows with different keys

Input

[{"sku":"A-100","price":"4.99"},{"sku":"B-205","stock":"40"}]

Output

sku,price,stock
A-100,4.99,
B-205,,40

Best JSON structures for this converter

This converter works best with a single object or, more commonly, an array of similarly shaped objects. That is the most natural match for CSV because each object becomes one row and the object keys become the column headers. Flat records are easiest to export cleanly.

How columns are created from JSON keys

The page gathers keys across the objects it finds and uses those keys to build the CSV header row. If some objects have extra fields, those extra fields become additional columns. If some objects are missing fields, their exported rows will contain blank cells in those positions.

That behavior is helpful when you are reviewing inconsistent API records or exports, but it is also a sign that you may want to normalize your records before using the CSV in a strict import workflow.

Flat JSON vs nested JSON

Flat key-value objects convert cleanly because CSV is a row-and-column format. Deeply nested objects and arrays are much harder to represent as simple cells. If your JSON contains nested structures, convert with caution and consider simplifying or flattening those records first if you need spreadsheet-friendly output.

Common cleanup steps before converting

Before exporting, make sure the JSON is valid, keep your records in an array when possible, and check whether all rows use consistent keys. If one record includes fields that the others do not, the output can still be useful, but the CSV will contain blank cells for missing values.

How CSV formatting affects spreadsheet apps

CSV is plain text, so fields that contain commas, quotes, or line breaks need to be quoted to stay readable in spreadsheet imports. This page writes those fields safely by quoting them when needed and doubling embedded quotes. That makes the result easier to paste into Excel, Google Sheets, or other CSV-based tools.

Troubleshooting conversion problems

Before You Rely on This CSV for Reporting or Imports

Before importing or sharing the CSV, check header names, blank cells, flattened values, and spreadsheet formatting behavior. A conversion that looks good in plain text may still need cleanup before it is suitable for reporting, import tools, or downstream analysis.

Where JSON-to-CSV Conversion Can Lose Structure or Meaning

JSON can represent nested relationships and mixed data types that CSV cannot express cleanly. During conversion, arrays, objects, and optional fields may be simplified into a flatter shape that works for spreadsheets but does not preserve every structural detail from the source payload.

How to Interpret Flattened Fields and Missing Values in CSV Output

CSV output turns structured JSON into rows and columns, which often means nested objects or arrays have to be flattened, simplified, or omitted. Missing fields may appear as blank cells rather than explicit null values. Review the column layout carefully so you know how the original structure was represented in the exported table.

If conversion fails, the most common causes are invalid JSON syntax, pasted data that is not a simple object or array of objects, or records with structure that does not fit a row-based CSV export. This page is intended for quick conversion and inspection, not for advanced schema mapping or complex relational exports.