CSV ↔ JSON

About this tool

Spreadsheet rows and JSON arrays describe the same data — this converter turns one into the other in your browser without a custom parser or uploading to a third-party server. It handles the RFC 4180 edge cases that a naive comma-split breaks on: quoted commas, escaped double-quote pairs, and multi-line cell values. Paste comma-separated text with a header row and each column name becomes a JSON key, giving you an array of objects ready for an API, MongoDB, or a Python script. The 'Detect numbers, booleans, and null' option turns numeric strings into real numbers, true and false into booleans and empty cells into null, while values with leading zeros such as 02139 stay strings. Uncheck it to keep every value as a string. The JSON → CSV button works in reverse: paste a JSON array of objects and receive CSV with a union-of-keys header row. Because the parser runs in JavaScript inside your tab, customer emails, internal SKUs, and PII never leave your machine.

Why use it

• RFC 4180 Quote-Aware Parser: Handles edge cases that break naive split(',') implementations: quoted fields containing commas, escaped double-quote pairs written as """, and multi-line cell values wrapped in quotes. Your Salesforce and HubSpot exports parse correctly every time.

• First Row Becomes JSON Keys: The header row is used as object keys, so a CSV column named id becomes {"id": ...} without any manual mapping step. Header names are trimmed of surrounding spaces before they become keys.

• Optional Type Detection: With the checkbox on, "42" and "3.14" become JSON numbers, true and false become booleans, and empty cells become null. Strings with leading zeros like 02139 stay strings. Uncheck it to keep every cell as a string.

• Both Directions in One Tool: A JSON array of objects converts back to CSV using a union-of-keys header, so round-tripping data through a spreadsheet takes one paste each way. Separate CSV → JSON and JSON → CSV buttons work on the same input box.

• Zero Upload, Zero Logs: Customer emails, internal SKUs, financial figures, and any PII never leave your browser tab. The JS parser runs entirely in memory — no fetch request is made and no server ever sees your data.

How to use

1. Paste your comma-separated text, including the header row, into the CSV or JSON box
2. Leave 'Detect numbers, booleans, and null' checked for typed values, or uncheck it to keep every value as a string
3. Click CSV → JSON to build an array of objects keyed by the header row
4. To go the other way, paste a JSON array of objects and click JSON → CSV
5. Copy the result, or click Download to save it as output.json or output.csv

When it helps

• Converting a Stripe, Salesforce, or Excel CSV export into a JSON array to feed into an API or database import script
• Wiring a CSV dataset into a JavaScript or Python prototype without writing a custom parser
• Transforming a Mixpanel or Google Analytics export into JSON for further processing in Node.js or pandas
• Roundtripping data through a spreadsheet: exporting JSON from an API, editing it in Excel, then reimporting as JSON
• Validating that a CSV file from a third-party vendor parses cleanly before loading it into a data pipeline
• Quickly inspecting the shape of an unfamiliar CSV by seeing the keys and types in the JSON preview

Examples

id,name,email,active
1,Ada Lovelace,ada@example.com,true
2,Alan Turing,alan@example.com,false

[
  {
    "id": 1,
    "name": "Ada Lovelace",
    "email": "ada@example.com",
    "active": true
  },
  {
    "id": 2,
    "name": "Alan Turing",
    "email": "alan@example.com",
    "active": false
  }
]

company,city,note
"Acme, Inc.","New York","O'Brien said ""hi"""
Globex,Springfield,"Multi
line"

[
  {
    "company": "Acme, Inc.",
    "city": "New York",
    "note": "O'Brien said \"hi\""
  },
  {
    "company": "Globex",
    "city": "Springfield",
    "note": "Multi\nline"
  }
]

[{"sku":"A-1","qty":3,"price":19.99},{"sku":"B-2","qty":1,"price":4.50}]

sku,qty,price
A-1,3,19.99
B-2,1,4.5

Tips

• If your CSV opens with sep=, in the first row (an Excel artifact), delete that line before pasting — it is a hint to Excel, not actual data.
• Values with leading zeros like ZIP code 02139 stay strings even with type detection on; uncheck it only if you also want numbers such as 42 to stay strings.
• If columns get shifted after a paste, your CSV likely has an unescaped quote — find the row count discrepancy and add the missing closing quote.
• JSON output is always indented with 2 spaces; if you need it on one line, minify it before embedding it in code.
• Save large outputs with the Download button rather than selecting and copying them by hand.

Frequently Asked Questions

Glossary

RFC 4180

The informal standard that defines how CSV files are structured, including quoting rules for fields that contain commas, newlines, or double-quote characters. Most spreadsheet programs follow this when exporting.

Header row

The first row of a CSV file that names each column. When converting to JSON, header row values become the keys in each output object.

Delimiter

The character used to separate fields in each row. Commas are most common, but semicolons, tabs, and pipes are also widely used depending on locale and tool.

Quoted field

A CSV field wrapped in double quotes, allowing it to contain the delimiter character, newlines, or literal double-quote characters without breaking the row structure.

Escape character

In CSV, a double-quote inside a quoted field is escaped by doubling it ("" represents one literal "). This differs from most programming languages, which use a backslash as the escape character.

Type coercion

The process of converting a string value to a more specific data type — for example, turning the string "42" into the number 42 or "true" into a boolean. Optional in CSV-to-JSON conversion.