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Convert CSV or Excel to JSON in Your Browser — No Upload, No Server

#json #csv #converter

The Tool

JSON Buddy includes a CSV/Excel converter that runs 100% client-side. Click the CSV/Excel to JSON tab in the toolbar and you get a dedicated conversion panel. No account, no upload, no file sent anywhere.

Supported Input Formats

Format Extension Notes
CSV .csv Comma-separated, UTF-8
TSV .tsv Tab-separated (also works if you paste directly from Excel)
Semicolon-separated .csv Common in European locales
Pipe-separated .txt `
Excel {% raw %}.xlsx, .xls Upload the file directly

The delimiter is detected automatically. You can also override it manually.

How to Use

Option 1: Upload a file

  1. Click CSV/Excel to JSON in the toolbar
  2. Drag & drop your .csv or .xlsx file onto the upload area
  3. The JSON output appears instantly on the right

Option 2: Paste directly

If you copied a table from Excel, Google Sheets, or Notion, just paste it into the text area. Tab-delimited content (the default clipboard format for spreadsheets) is parsed automatically.

name    age city    active
Alice   30  Berlin  true
Bob 25  Paris   false
Carol   35  Tokyo   true
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Paste that and get:

[
  { "name": "Alice", "age": 30, "city": "Berlin", "active": true },
  { "name": "Bob",   "age": 25, "city": "Paris",  "active": false },
  { "name": "Carol", "age": 35, "city": "Tokyo",  "active": true }
]
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Automatic Type Inference

By default, JSON Buddy infers types from cell values:

Cell value JSON type
42 number (integer)
3.14 number (float)
true / false boolean
null / empty null
"hello" string

So a column of ages becomes a JSON number array, not a string array — which is almost always what you want when seeding a database or writing tests.

You can toggle type inference off if you need everything as strings.

Real Examples

Seeding a database

You have a users.csv from a staging database export:

id,name,email,role,created_at
1,Alice,alice@example.com,admin,2024-01-15
2,Bob,bob@example.com,user,2024-02-20
3,Carol,carol@example.com,user,2024-03-05
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Output:

[
  {
    "id": 1,
    "name": "Alice",
    "email": "alice@example.com",
    "role": "admin",
    "created_at": "2024-01-15"
  },
  ...
]
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Paste this directly into your seed script or API test fixture.

Mocking an API response

You're building a front end and the back end isn't ready. Export a table from Notion, convert to JSON, drop it into your mock server or public/mock-data.json.

Data pipeline testing

A data engineer sends you a .xlsx with sample records to validate your ingestion pipeline. Upload it, get JSON, feed it to your tests — without ever writing a pandas script.

Copy the Output Back to the JSON Editor

Once your data is converted, there's a "Use in Editor" button that loads the JSON into the main formatter. From there you can:

  • Format and inspect it in the tree view
  • Run it through the Code Gen to generate typed structs for your language
  • Use Find & Replace to do a bulk value substitution before using it

Why Not Just Use Python?

You can, of course:

import csv, json

with open('data.csv') as f:
    rows = list(csv.DictReader(f))
print(json.dumps(rows, indent=2))
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But that requires Python installed, a terminal, writing and running a script. For a quick one-off conversion during development, a browser tool is faster. And for non-developers (PMs, data analysts, QA engineers), a no-code option is often the only practical one.

Privacy Note

The file never leaves your browser. For Excel files, the parsing uses the SheetJS library running client-side. No file data is transmitted anywhere.

This matters when the spreadsheet contains:

  • Customer PII (GDPR-relevant)
  • Financial data
  • Internal employee records
  • Unreleased product information

Try It

👉 json-formatter.net — click the CSV/Excel to JSON tab

Works on desktop and mobile. Installable as a PWA for offline use.

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