CSV to JSON Converter
Convert CSV to JSON instantly. Transform comma-separated values from spreadsheets and databases into structured JSON arrays. Handles numbers, booleans, quoted values, and empty cells automatically. Perfect for developers working with spreadsheet data and database exports.
- Input
- CSV Format
- Output
- JSON Array
- Time
- Instant
- Price
- Free
Smart Type Detection
Automatically converts numeric strings to numbers and 'true'/'false' strings to booleans for better JSON output.
Quoted Value Support
Properly handles CSV values with quotes, commas, and newlines. Correctly parses escaped quotes and complex CSV structures.
100% Private
Everything runs locally in your browser. Your CSV data never leaves your device.
Convert CSV to JSON online
Paste your CSV data, choose JSON indentation options, and get structured JSON output.
First row should contain column headers. Values are separated by commas (,). Quoted values are supported.
Choose JSON indentation style.
Privacy-first
All conversion happens locally. No uploads.
What is CSV to JSON Conversion?
Understanding how comma-separated values transform into structured JSON data
CSV to JSON conversion is the process of transforming comma-separated values (CSV) into structured JSON (JavaScript Object Notation) format. CSV is a simple text format where data is organized in rows and columns, with commas (,) separating each value. JSON stores data as structured objects and arrays, making it ideal for APIs, databases, and programmatic data manipulation.
When you convert CSV to JSON, each row in the CSV file becomes an object in a JSON array, and each column header becomes a property name. For example, a CSV file with headers "name," "age," and "email" will produce a JSON array where each object has these properties. This transformation makes spreadsheet data immediately usable in web applications, APIs, and modern development workflows.
CSV Format (Comma-Separated)
name,age,email John Doe,30,john@example.com Jane Smith,25,jane@example.com
Commas (,) separate values
JSON Format (Structured)
[
{
"name": "John Doe",
"age": 30,
"email": "john@example.com"
},
{
"name": "Jane Smith",
"age": 25,
"email": "jane@example.com"
}
]Structured objects with proper types
How CSV to JSON Conversion Works
The conversion process parses the CSV file line by line: the first row contains column headers, and subsequent rows contain data values. Each data row is split by commas, with special handling for quoted values (values containing commas, quotes, or newlines). The tool automatically detects and converts numeric strings to numbers and boolean strings ('true'/'false') to actual boolean values, making the JSON output more useful for programmatic use.
For CSV to JSON conversion, this means your spreadsheet data (exported from Excel, Google Sheets, or databases) can be immediately transformed into structured JSON that works seamlessly with APIs, web applications, and modern development tools. This is why CSV to JSON conversion is essential for developers working with spreadsheet exports, database dumps, and data migration tasks.
CSV vs TSV vs JSON
CSV (Comma-Separated Values) uses commas as delimiters and is the most widely supported format. TSV (Tab-Separated Values) uses tabs and is better for data containing commas. JSON is structured and hierarchical, perfect for APIs and web applications. CSV to JSON conversion bridges the gap between spreadsheet formats and modern web development, allowing you to use spreadsheet data in JSON-based systems.
Quoted Value Handling
This tool properly handles CSV values that are quoted (containing commas, quotes, or newlines). Quoted values are correctly parsed, and escaped quotes (\"\") are handled properly. This ensures accurate conversion even for complex CSV data with special characters.
Why Convert CSV to JSON?
Common use cases where CSV to JSON conversion is essential
API Integration
Convert spreadsheet exports to JSON for API requests and responses. Modern APIs expect JSON format, and CSV to JSON conversion makes your spreadsheet data API-ready instantly.
Database Imports
Import CSV exports into NoSQL databases (MongoDB, CouchDB) that use JSON format. Convert spreadsheet data to JSON for seamless database integration.
Data Migration
Migrate data from legacy systems that export CSV to modern JSON-based applications. Convert historical spreadsheet data to JSON for new systems.
Web Applications
Use spreadsheet data in web applications that consume JSON. Convert CSV exports from Excel or Google Sheets to JSON for frontend applications.
Data Science
Convert CSV data to JSON for use in data science tools and scripts. JSON is widely supported in Python, R, and JavaScript data processing libraries.
Configuration Files
Transform spreadsheet-based configuration data to JSON format. Many modern tools and frameworks use JSON for configuration, and CSV to JSON conversion makes this transition seamless.
CSV to JSON Conversion in Numbers
Why developers convert CSV data to JSON format
How to Convert CSV to JSON
Three simple steps to transform your CSV data into JSON format
Paste your CSV data
Copy your CSV data from a spreadsheet (Excel, Google Sheets), database export, or text file and paste it into the input field. The first row must contain column headers, and subsequent rows should contain data values separated by commas (,). CSV format is the most widely supported format for spreadsheet data exchange.
Example CSV format:
name,age,email,city John Doe,30,john@example.com,New York Jane Smith,25,jane@example.com,Los Angeles
Choose JSON indentation options
Select your preferred JSON indentation: 0 spaces for compact JSON (smallest size), 2 spaces for standard readable format, or 4 spaces for extra readability. The tool automatically detects and converts numeric strings to numbers and 'true'/'false' strings to boolean values, making the JSON output immediately usable in your applications.
Convert and export
Click the Convert to JSON button to transform your CSV data. The tool parses comma-separated values, handles quoted values correctly, maps them to column headers, and generates a JSON array of objects with proper data types. The output shows conversion statistics (rows, columns, file sizes) and the formatted JSON. Copy the result to your clipboard or download it as a .json file for immediate use in APIs, databases, or web applications.
Example JSON output:
[
{
"name": "John Doe",
"age": 30,
"email": "john@example.com",
"city": "New York"
},
{
"name": "Jane Smith",
"age": 25,
"email": "jane@example.com",
"city": "Los Angeles"
}
]Ready to use in APIs and applications
Best Practices for CSV to JSON Conversion
Expert tips for accurate and efficient CSV to JSON conversion
Always include a header row
The first row of your CSV should contain column names. These become property names in the JSON objects. Without headers, the tool cannot create meaningful JSON structure. Ensure headers are unique and don't contain special characters that might cause issues in JSON property names.
Quote values containing commas
If your CSV data contains commas within values (like addresses or lists), wrap those values in double quotes. For example: "New York, NY" or "apple, banana, orange". The tool properly handles quoted values and escaped quotes (\"\").
Let the tool handle type conversion
The tool automatically converts numeric strings to numbers and 'true'/'false' strings to booleans. Don't manually format these values—let the tool detect and convert them for you. This ensures consistent type handling across all rows.
Don't use spaces in headers unnecessarily
While spaces in headers are allowed, they can make JSON property names harder to work with programmatically. Consider using camelCase or snake_case for headers (e.g., "firstName" instead of "First Name") for better JSON compatibility.
Don't mix delimiters
CSV files must use commas (,) consistently. Mixing commas with tabs, semicolons, or other characters will cause parsing errors. If your data has inconsistent delimiters, clean it up before conversion or use a text editor to standardize the format.
Don't ignore empty cells
Empty cells in CSV are converted to empty strings in JSON. If you need null values instead, preprocess your CSV to use "null" as a string, or handle empty strings in your application code. The tool preserves all data structure including missing values.
CSV to JSON Conversion Methods
Compare different approaches to converting CSV data to JSON format
| Method | Best For | Setup Time | Type Detection | Ease of Use |
|---|---|---|---|---|
Online Tool FixTools (this page) | Quick conversions, testing, one-off files | Instant | ✓ Automatic | ✓ Very Easy |
Python pandas pd.read_csv().to_json() | Data science, large files, automation | Python install | ✓ Automatic | ⚠ Requires code |
Node.js csv-parse csv-parse library | Server-side, Node.js applications | npm install | ✗ Manual | ⚠ Requires code |
Excel Power Query Built-in Excel feature | Excel users, spreadsheet workflows | Pre-installed | ✗ Manual | ⚠ Complex UI |
Command Line (jq) csv-to-json script | Shell scripts, automation, CI/CD | Script setup | ✗ Manual | ⚠ Requires CLI |
When to Use This Online Tool
This online converter is ideal for quick testing, one-off conversions, and situations where you need automatic type detection with zero setup. It requires no installation and works entirely in your browser with complete privacy. For production applications with high volume or complex requirements, integrate CSV parsing directly into your codebase using libraries like pandas (Python) or csv-parse (Node.js).
Frequently Asked Questions
Everything you need to know about CSV to JSON conversion
How do I convert CSV to JSON?
Paste your CSV data into the input field (first row should contain column headers), choose JSON indentation options, and click Convert. The tool will automatically parse the CSV and generate a JSON array of objects.
What is CSV format?
CSV (Comma-Separated Values) is a text format where data is organized in rows and columns, with commas (,) separating each value. It's the most widely used format for exporting data from spreadsheets and databases.
Does the tool handle quoted CSV values?
Yes. The tool properly handles CSV values that are quoted (containing commas, quotes, or newlines). Quoted values are correctly parsed, and escaped quotes (\"\") are handled properly.
What's the difference between CSV and TSV?
CSV uses commas (,) as delimiters while TSV uses tabs (\\t). CSV is more widely supported, while TSV is better for data containing commas. Both can be converted to JSON with our tools.
Can I convert large CSV files?
Yes! The tool processes files entirely in your browser, so size limits depend on your browser's memory. Most files under 50MB work smoothly. For very large files, consider processing in chunks.
Does the tool handle empty cells?
Yes. Empty cells in CSV are converted to empty strings in JSON. The tool preserves all data structure including missing values.
Is my CSV data stored on your servers?
No. All conversion happens locally in your browser using JavaScript. Your CSV data never leaves your device and is not uploaded to any server.
Can the tool parse numbers and booleans?
Yes. The tool automatically detects and converts numeric strings to numbers, and 'true'/'false' strings to boolean values. This makes the JSON output more useful for programmatic use.
What if my CSV has inconsistent columns?
The tool uses the header row to determine column structure. Rows with fewer values will have empty strings for missing columns. Rows with extra values will be truncated to match the header count.
Can I convert CSV with special characters?
Yes. CSV format handles special characters by quoting values. Values containing commas, quotes, or newlines should be wrapped in double quotes. The tool properly parses quoted values and escaped quotes.
How do I export CSV from Excel?
In Excel, go to File → Save As, choose "CSV (Comma delimited) (*.csv)" format. This creates a CSV file that you can paste directly into this converter. Google Sheets: File → Download → Comma-separated values (.csv).
What JSON format does the tool output?
The tool outputs a JSON array of objects. Each CSV row becomes an object, and each column header becomes a property name. You can choose indentation (0, 2, or 4 spaces) for readability.
Can I use this for production applications?
This tool is perfect for testing, debugging, and one-off conversions. For production apps with high volume, integrate CSV parsing directly into your codebase using libraries (pandas in Python, csv-parse in Node.js) for better performance and error handling.
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