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JSON to CSV

Convert JSON to CSV — API data into spreadsheet rows, instantly.

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Updated Sep 2026

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How to use JSON to CSV

  1. Paste a JSON array of objects — the standard shape from API list endpoints.
  2. Read the CSV output: keys as the header row, one line per object, proper escaping.
  3. Copy or save as .csv — it opens directly in Excel, Google Sheets or Numbers.
  4. For nested JSON, expect flattened columns or stringified cells — reshape upstream when the consumer needs cleaner columns.

What is JSON to CSV?

A JSON to CSV converter flattens an array of JSON objects into rows and columns: keys become the header row, each object becomes a data row, and the result opens directly in Excel or Google Sheets. [{"name":"Ada","age":36},{"name":"Alan","age":41}] becomes a two-row table with name and age columns.

It's the standard bridge between developer data and everyone else: APIs, logs and exports speak JSON; analysis, reporting and colleagues speak spreadsheet. The shape requirement is the one catch — CSV is flat, so the natural input is an array of similar objects; deeply nested structures must flatten or stringify into cells.

About the JSON to CSV

Paste a JSON array of objects and get CSV with headers derived from the keys — quoted and escaped correctly, ready to save or paste into a spreadsheet.

The conversions people run daily: an API's user/order/product list into Excel for someone who asked for "the data in a spreadsheet"; exported analytics or log records into a pivot table; a database dump in JSON into a CSV import for another system; survey or form results into analysis-ready rows. Objects with differing keys union their columns (missing values become empty cells), and commas or quotes inside values are escaped per the CSV rules — the fiddly part manual conversion always gets wrong.

Nested objects flatten by convention (a user.address.city path becomes a dotted column or a stringified cell). For the reverse direction — spreadsheets into JSON — the CSV to JSON converter mirrors the process.

Frequently Asked Questions

An array of flat objects with matching keys — each object a row, keys the columns. Anything else (nested objects, mixed types, top-level object) needs flattening or restructuring first.
The columns union: every key that appears anywhere becomes a column, and objects missing it get empty cells. Fine for spreadsheets; worth normalizing upstream if the CSV feeds a strict importer.
Values containing commas, quotes or line breaks get wrapped in double quotes (with internal quotes doubled) per RFC 4180 — the escaping rule hand-rolled conversions miss, producing shifted columns.
Excel auto-types on open: 03-04 becomes a date, 00042 loses zeros. Import via Data → From Text with columns set to Text, or open in Google Sheets which is gentler. The CSV itself is correct.
Flattened to dotted columns (address.city) or stringified JSON in a cell, depending on depth. CSV is two-dimensional — deep hierarchy has to compromise somewhere; choose based on what the spreadsheet consumer needs to see.

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