Tables and data

JSON to CSV: choose how to flatten nested objects

CovertonUpdated 2026-10-08

This spreadsheet conversion requires an array whose entries are objects. Decide whether nested objects should become separate columns or remain JSON strings inside cells, because the resulting spreadsheet is read differently in each case.

Open the tool →How to use this tool ↓

Convert JSON to CSV — This illustration explains the tool's workflow. It is not the processed result of an uploaded file.

How to use this tool

Choose files in JSON format. Maximum files per batch: 1.
Review Flatten nested objects, then start processing.
Download the CSV result and check its content and quality.

Choose the right settings

Enable flattening to turn nested object properties into headers joined with dots. Arrays are not expanded into multiple rows, so review those cells separately if you intend to analyze each array item.

Supported input: JSON
Output: CSV
Available settings: Flatten nested objects

Before you start

Establish the meaning of the input

Before converting or arranging data, identify what a row or value represents and keep a source copy. In tabular files, review headers, separators and text encoding; in structured files, inspect the required object or array shape. Identifiers, dates and amounts should not be interpreted solely from how a spreadsheet happens to display them.

Where the tool offers matching columns, type rules or output fields, choose them according to the destination’s requirements. Test a sample with a blank, a repeated value and a value containing punctuation. For labels, charts or personalized documents, check which column supplies each displayed value and whether the source units and wording are correct.

Define a few checks before processing: an identifier that must retain its spelling, a value with a known interpretation and an expected relationship between records. If the tool offers type conversion or matching rules, distinguish a source value from the program’s display of it. Test ambiguous dates or differently written keys before accepting a broad rule. Keep the chosen rules and destination requirements with the result; this makes a discrepancy traceable to input, interpretation or the requested transformation.

Verify values, structure and exceptions

Reopen or import the result using the destination’s settings. Compare headers, record counts and several values with the source, allowing for the operation you requested. A summary, split or duplicate-removal task can legitimately change the count; verify why it changed rather than expecting every transformation to keep identical rows.

Inspect any exception or validation report before continuing. If columns shift, characters are garbled or a key is not found, check delimiters, encoding and exact header spelling first. Encoding data does not encrypt it, and formatting a value does not confirm its meaning. For printed codes or labels, test the actual output before making the full set.

Example input and output

JSON object array → header-and-row CSV

Examples describe the workflow. Results depend on the source file and settings.

Check the saved result before using it

When objects have different properties, check that the CSV headers include all the fields you need. Compare blanks, array values and leading-zero identifiers after importing the file into a spreadsheet.

If the result is different from what you expected

A single top-level object or an array of bare numbers is unsuitable for this conversion. Resolve collisions between existing dotted keys and flattened property names before exporting the data.

Limits to keep in mind

CSV cannot represent every JSON structure. Formula-like cells are escaped as text for spreadsheet safety.

Continue with a related tool

Convert CSV to JSON

The first CSV row supplies the keys for each data row's JSON object. Cell values are stored as strings, so inspect their types before passing the result to a system that expects numbers or boolean values.

Choose the source encoding and use automatic delimiter detection or select the actual delimiter. Resolve empty or duplicate headers and ensure each row has the same number of columns as the header.

Open the tool →

Convert TSV to CSV

Re-save a tab-separated spreadsheet when the receiving system accepts CSV. A field can contain commas or line breaks of its own, so replacing every tab with a comma in plain text would not be enough to preserve cell boundaries.

Check whether the source uses UTF-8 or an EUC-KR-compatible encoding and choose it accordingly. Input fields are read with tabs, while the saved CSV uses commas as its separators.