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Jump straight into adjacent tools while the same JSON context and workflow are still fresh.

JSON to CSV

Reverse: convert JSON back to CSV

JSON to Table

View JSON as a readable table

Excel to JSON

Import XLSX spreadsheets directly

JSON Validator

Validate the resulting JSON

JSON to TypeScript

Generate types from the output

JSON to Schema

Create a schema from the output

Free Online CSV to JSON Converter

Convert CSV to JSON instantly in your browser. Paste CSV text or upload a file to get a clean JSON array — no server processing, no uploads, no ads.

Header Mapping: First row becomes JSON object keys.
Type Inference: Numbers, booleans, and null auto-detected.
Quoted Fields: Handles commas inside quoted cells correctly.
Custom Delimiters: Supports comma, semicolon, and tab (TSV).

How to Convert CSV to JSON

Paste your CSV into the left panel or upload a .csv file. Enable Header row if the first line contains column names — each data row becomes a JSON object with those keys. Toggle Type inference to automatically convert numeric strings and booleans. Click Download JSON to save the result.

Reference guide

CSV to JSON Conversion Guide

What is CSV to JSON?

CSV (Comma-Separated Values) stores tabular data as plain text rows. JSON structures the same data as arrays of objects, making it directly usable in APIs, databases, and modern frameworks. Converting between the two is a fundamental data-pipeline step.

Common use cases:

API Import: Feed spreadsheet exports into REST APIs.
Database Seeding: Convert CSV exports to JSON for bulk insert.
Data Migration: Move data between platforms without manual reformatting.
Analytics: Transform CSV reports into structured JSON for processing.

Output Options

Array of Objects

Each row becomes an object where keys are header names. Best for API payloads and database imports.

Array of Arrays

Each row becomes a raw array preserving the grid structure. Useful when you need positional access rather than named keys.

Conversion Example

CSV Input

name,age,active
Alice,30,true
Bob,25,false

JSON Output

[
  { "name": "Alice", "age": 30, "active": true },
  { "name": "Bob", "age": 25, "active": false }
]

CSV to JSON in Python and JavaScript

In Python, csv.DictReader converts each row to a dictionary keyed by headers — then json.dumps(list(reader), indent=2) produces the output. For type inference, wrap values through a conversion function. In JavaScript and Node.js, the papaparse library handles edge cases like quoted commas and multi-line fields robustly. For large datasets fed into an API, validate the output structure with our JSON validator before sending requests.

Frequently Asked Questions

Is my data safe with this JSON tool?

Yes. This tool uses 100% client-side processing. Your JSON data never leaves your browser and is never sent to our servers, ensuring maximum privacy and security.

Does this tool work offline?

Once the page has loaded, all processing happens locally in your browser. You can disconnect from the internet and the tool will continue to work — no server connection is required to format, validate, or convert your JSON.

Is there a file size limit?

No server-side limits apply because everything runs in your browser. Practical limits depend on your device's memory, but modern browsers handle JSON files of tens of megabytes without issue.

What CSV formats does this tool support?

This tool supports standard CSV with comma delimiters, as well as TSV (tab-separated) and semicolon-delimited files. Enable the header row option when the first line contains column names — each subsequent row will become a JSON object with those keys.

What does 'type inference' do?

When type inference is enabled, numeric strings like "42" are converted to numbers, "true"/"false" to booleans, and "null" to null. Disable it if you need all values to remain as strings regardless of content.

What output modes are available?

You can output an array of objects (one object per row, with header keys) or an array of arrays (raw rows). Array of objects is best for API payloads and database imports; array of arrays preserves the raw grid structure.

How do I handle CSVs with quoted commas?

Quoted fields (e.g. "Smith, John") are handled correctly — the content inside double quotes is treated as a single field even if it contains the delimiter character.