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CSV to JSON

Convert CSV data into a JSON array of objects.

Convert CSV data into a JSON array of objects.

Quick start: Paste your CSV text into the input box, or open a .csv file you exported from a spreadsheet. → Confirm the first row is treated as the header - those values become the JSON object keys. → Click Convert to generate a JSON array, with one object per data row.

How to use CSV to JSON

  1. 1

    Paste your CSV text into the input box, or open a .csv file you exported from a spreadsheet.

  2. 2

    Confirm the first row is treated as the header - those values become the JSON object keys.

  3. 3

    Click Convert to generate a JSON array, with one object per data row.

  4. 4

    Review the output for any rows that did not parse cleanly, such as ragged or empty lines.

  5. 5

    Copy the JSON or download it to use in an API request, config file, or import script.

Real examples of CSV to JSON in action

Basic rows
Before
name,age
Ada,36
Grace,45
After
[
  { "name": "Ada", "age": "36" },
  { "name": "Grace", "age": "45" }
]
Quoted comma
Before
name,city
"Smith, John",London
After
[
  { "name": "Smith, John", "city": "London" }
]
Popular tools

Try our most-used tools

Who is CSV to JSON for?

Developers seeding a database or feeding a REST API from spreadsheet exports

Data analysts moving CSV downloads into JSON for scripts and dashboards

QA engineers building JSON test fixtures from sample data

No-code and automation users prepping JSON payloads for webhooks

Why use CSV to JSON?

  • Detects the header row automatically and uses each column name as the JSON object key.
  • Correctly parses quoted fields, so a value like "Smith, John" stays as one field instead of splitting on the comma.
  • Produces a standard JSON array of objects that drops straight into JavaScript, Python, or any REST API body.
  • Shows the result instantly as you paste, so you can spot a wrong delimiter or stray column right away.
  • Runs entirely in your browser, so customer lists, exports, and other sensitive CSV data never leave your device.

Common use cases

  • Turn a spreadsheet export into JSON to seed a database or feed a REST API.
  • Convert an analytics or CRM CSV download into JSON for a script or dashboard.
  • Build test fixtures from sample data without writing a parser by hand.
  • Prepare a JSON payload for a no-code tool or webhook that only accepts JSON.

How CSV to JSON compares to alternatives

Honest comparison to other popular options — pick the right tool for the job.

ToolMain limitation
Excel / Google SheetsEdits CSV well but has no built-in export to a JSON array of objects
ConvertCSV.comFlexible but ad-heavy and uploads larger files to its server
A custom script (Python csv / pandas)Powerful and repeatable but overkill for a one-off paste-and-convert
CSV to JSONFree, runs in your browser, no sign-up, no watermarks, no file-size limits beyond your device memory.

Limitations & things to know

  • Treats every cell as a string by default, so numbers and booleans may need casting after conversion
  • Assumes the first row is a header; files without one will use real data as object keys

About CSV to JSON

A CSV to JSON converter transforms comma-separated values, the format every spreadsheet can export, into a JSON array of objects that code and APIs can consume directly. This free tool reads the first line of your CSV as the header row and uses those column names as the keys for each object, then turns every following row into one JSON object. So a file with columns name, email, and age becomes an array where each entry is {"name": ..., "email": ..., "age": ...}. The trickiest part of parsing CSV is quoting, and this tool handles it correctly: a field wrapped in double quotes can contain commas, line breaks, or escaped quotes without breaking the row, following the common RFC 4180 convention. That means an address like "221B Baker St, London" stays as a single field rather than splitting into two columns. One thing worth knowing is that CSV has no concept of data types. Every cell is just text, so by default numbers and booleans come out as JSON strings, for example "42" rather than 42. If your downstream code needs real numbers, dates, or booleans, convert them after parsing or enable number inference if available. Watch out for ragged rows, where a line has more or fewer fields than the header, and for files that lack a header line entirely, since the first data row would then be misread as the keys. CSV to JSON conversion is everyday work when seeding a database from a spreadsheet, feeding a REST API that expects JSON, building test fixtures, or moving data between tools that speak different formats. Everything runs locally in your browser, so even a CSV full of customer records or financial data is never uploaded.

Frequently asked questions

Yes. Fields wrapped in double quotes are treated as a single value, so "Paris, France" stays intact instead of splitting into two columns. This follows the standard CSV quoting rule (RFC 4180).
The first row is read as column names and becomes the keys of every JSON object. If your file has no header row, the first data row would be mistakenly used as keys, so add a header line first.
By default each cell becomes a JSON string, because CSV itself has no types. A value of 42 in CSV may appear as "42" in JSON unless the tool is set to infer numbers, so cast types in your code if you need real numbers or booleans.
No. Parsing happens in your browser with JavaScript. Nothing you paste is sent to a server, logged, or stored.

Your files never leave your device

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