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JSON to CSV

Flatten complex data structures into clean, tabular CSV format.

JSON SourceValid JSON

CSV Output

id,name,email,status,metadata.department,metadata.level 1,Jane Cooper,jane.c@example.com,active,Security,4 2,John Doe,john.doe@example.com,inactive,Analytics,2

settings

General Rules

Include Header row

Flatten Objects

Formatting

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Tabular Preview

id	name	email	status	metadata.department	metadata.level
1	Jane Cooper	jane.c@example.com	active	Security	4
2	John Doe	john.doe@example.com	inactive	Analytics	2

Technical FAQ

Can it handle nested JSON objects?

Yes, the flattening engine recursively traverses nested hierarchies. You can define a custom separator (like '.' or '_') to map these paths to flat CSV columns.

How are arrays processed?

Arrays can be stringified as comma-separated values within a single cell, or flattened into indexed columns depending on your configuration requirements.

Is there a file size limit?

The tool processes everything locally in your browser for privacy. While modern browsers handle up to 50MB comfortably, massive datasets may benefit from pre-splitting.

Is my data sent to any server?

No. Conversion happens entirely on your machine. UtilVox maintains zero-knowledge architecture for all developer tools.

Flattening JSON for People Who Live in Excel

What flattens cleanly — and what resists

CSV is a flat grid; JSON is a tree. The conversion works exactly as well as the data is flat:

JSON shape	CSV result
Array of flat objects	Perfect — keys become columns, objects become rows
Objects with missing keys	Fine — gaps become empty cells
Nested objects (address.city)	Workable — dotted column names like address.city
Arrays inside objects (tags: [a, b])	Awkward — joined into one cell or exploded into rows
Wildly different objects per row	Messy — a sparse grid with many empty cells

The audience is the point

This conversion exists because the people who need the data — accounts, operations, a client — live in spreadsheets, not API consoles. An export of orders, a usage report, a contact dump: one conversion turns developer output into something filterable, sortable and pivot-table-ready. For deeply nested API responses, consider extracting just the array you need (the JSON formatter's tree view makes the path obvious) before converting.

Excel will mangle a few things — pre-empt them

Long numbers (CNIC, account numbers) become scientific notation, leading zeros vanish from phone numbers, and anything date-like gets reformatted. The defense: open the CSV via Excel's import dialog and declare those columns as text, rather than double-clicking the file. The reverse trip is CSV to JSON, and quick conversions between developer formats continue in YAML to JSON.