JSON ↔ CSV Converter

JSON and CSV solve different problems. JSON holds hierarchical, nested data and suits APIs and config files; CSV is flat and tabular and suits spreadsheets. Moving data between them is not just reformatting, it is restructuring. This tool runs in your browser and converts a JSON array into CSV for Excel or Google Sheets, and CSV rows back into a JSON array.

How to Use the JSON ↔ CSV Converter

• Choose a direction: JSON to CSV or CSV to JSON. The Mode line under the buttons confirms which way it is running.

  

• Type or paste your input into the Input box.

  

• The Output box fills in as you type — there is no Convert button to press.

  

• Click Copy to take the result, or Download to save it as converted.csv or converted.json.

  

• Click Paste to pull data in from your clipboard, or Clear to start again.

  

• All of it happens in your browser — nothing is uploaded to a server.
• Bad input is reported inline rather than failing silently: paste [{“a”:1,] and the tool answers with the parser’s own message.

What Is JSON ↔ CSV Conversion?

• Convert an array of objects into an array of CSV rows by using JSON to CSV: each object becomes a row, each property becomes a column.
• CSV to JSON turns each row into a JSON object, using the header row for the property names.
• The shape this tool wants is a flat array of objects. A single object works too, as one row — but an object wrapping an array, such as {“users”: […]}, is not unwrapped, and you get a single users column instead.
• The output is always comma-delimited — there is no delimiter setting. If your spreadsheet expects semicolons, set that in its own import dialog rather than looking for an option here.
• CSV has no concept of nesting, so anything nested has to be represented some other way when it crosses over.

How Nested JSON Is Handled

• This is the part most explanations skip, and it decides whether your output is usable:
• Plenty of converters flatten nested objects into dot-notation columns. This one does not: {“address”: {“city”: “NYC”}} becomes a single address column holding the JSON text {“city”: “NYC”}, not an address.city column with NYC in it.
• Nested arrays go the same way. There is no way to spread a list across one cell, so {“tags”: [“x”,”y”]} lands in a tags column as the JSON text [“x”,”y”].
• So both kinds of nesting behave identically here: the value survives intact, but as JSON text inside one cell rather than as columns you can sort or filter on.
• If you need nested values as columns of their own, flatten the JSON before you paste it in — or split the JSON text back out in the spreadsheet afterwards.

When You’d Use This

• Export API response data to a spreadsheet for analysis, reporting or to share non-technical stakeholders.
• A CSV file exported from an Excel or Google spreadsheet to a JSON file for use in an app or script.
• Creating a JSON configuration or log data to view on a spreadsheet application
• Converting form or survey CSV data to structured JSON for a database or API.
• Rapidly scanning the form of nested API data as readable columns
• Copying data from one system to another, with different one expecting JSON and the other expecting CSV.

Worked Example

JSON to CSV: Input:

[
  { "name": "Alice", "age": 30, "city": "New York" },
  { "name": "Bob", "age": 25, "city": "London" }
]

Output:

name,age,city
Alice,30,New York
Bob,25,London

CSV to JSON: Input:

name,age,city
Alice,30,New York
Bob,25,London

Output:

[
  { "name": "Alice", "age": "30", "city": "New York" },
  { "name": "Bob", "age": "25", "city": "London" }
]

CSV has no notion of data types, so numbers come back from a CSV to JSON conversion as strings unless the receiving system converts them.

Nested input behaves differently again: [{“name”:”Ada”,”address”:{“city”:”NYC”}}] converts to the two columns name,address — with the whole address object sitting in one cell as JSON text, not as an address.city column.

Do’s and Don’ts

Do:

• Use a flat array of objects as the JSON input — it is the shortest route to a clean CSV.
• Check what delimiter your spreadsheet expects before importing. This tool always writes commas, so a semicolon locale needs the delimiter set in the import dialog.
• Check the header row before a CSV to JSON conversion — those headers become your JSON property names verbatim.
• Expect nested objects and nested arrays alike to arrive as JSON text inside a single cell.

Don’t:

• Assume nested values will be split across rows or columns — nothing is split, in either direction.
• Forget that CSV values are always text — if your application needs real numbers and booleans, convert them back after a CSV to JSON pass.
• Mix different keys across the objects in your JSON — you get a column for every key that appears anywhere and blank cells wherever one is missing.
• Worry about commas inside your values — anything containing a comma, a quote or a line break is wrapped in double quotes for you automatically.

Common Mistakes

• Inconsistent object keys — if the objects in your array do not share the same keys, the CSV gets a column for every key that appears anywhere and a blank cell wherever one is missing.
• Assuming types survive the round trip — they do not. Send the number 30 out to CSV and back and it returns as the string “30”, because CSV stores everything as text.
• Ignoring a delimiter mismatch — opening a comma-delimited file in a spreadsheet set to semicolons drops everything into one column, and pasting a semicolon file into CSV to JSON here gives you one key holding the whole row.
• Not accounting for nested arrays — expecting a list inside a JSON object to become several CSV rows. It will not; it arrives as JSON text in a single cell.

Good to Know

• The default CSV output will be in RFC 4180 format, which means that any value containing a comma, a quote, or a line break is enclosed in double quotes to ensure it is valid in a CSV file.
• If the columns look misaligned, check your locale: some Excel and spreadsheet locales expect a semicolon rather than a comma, and this tool always writes commas.
• A single JSON object, not wrapped in an array, still converts — as a one-row table with its top-level keys as the header.
• Conversion here runs both ways in the same place, where many converters handle only one direction.
• Numbers and booleans lose their type on the way into CSV, so you may need to convert them back by hand downstream.

FAQ