CSV to JSON Converter - Convert CSV & JSON

Frequently asked questions

What is CSV to JSON conversion?

CSV (Comma-Separated Values) to JSON (JavaScript Object Notation) conversion transforms tabular data into a structured object format. CSV files store data in rows and columns with delimiters (usually commas), making them simple but limited in structure. JSON uses key-value pairs and supports nested objects, arrays, and multiple data types (strings, numbers, booleans, null). Converting CSV to JSON is essential when: (1) Migrating data from Excel/spreadsheets to web applications or databases, (2) Preparing data for RESTful APIs that require JSON payloads, (3) Processing data with JavaScript where objects are easier to manipulate than raw text, (4) Building single-page applications that consume structured data, (5) Integrating legacy systems that export CSV with modern systems that expect JSON. The conversion process parses CSV rows, identifies headers (first row typically), and maps each row's values to object properties, creating an array of objects or other structured formats.

How do I convert CSV to JSON?

Converting CSV to JSON with this tool: (1) **Paste or Upload** - Enter CSV data directly into the input box or click 'Upload File' to load a .csv file from your computer. (2) **Choose Delimiter** - Select 'Auto-detect' to automatically identify comma, semicolon, tab, or pipe delimiters, or manually specify if your CSV uses a custom separator. (3) **Configure Options** - Enable 'First row as headers' (default) to use the first row for object property names. Enable 'Auto-detect data types' to convert strings like '123' to numbers and 'true' to booleans automatically. (4) **Select Output Format** - Choose from Array of Objects (default, best for most use cases), Object with Keys, Array of Arrays, or Column-Oriented format. (5) **Click Convert** - Preview the parsed data in table format, then view the formatted JSON output. (6) **Copy or Download** - Use the Copy button to send JSON to clipboard or Download to save as a .json file. The tool handles quoted fields, escaped characters, and empty cells correctly.

What are the CSV to JSON output formats?

This converter supports four JSON output formats: **Array of Objects** (default) - Creates an array where each row becomes an object with header names as keys: `[{"name":"John","age":30},{"name":"Jane","age":25}]`. This is the most common format, ideal for APIs, databases, and JavaScript array methods. **Object with Keys** - Wraps each row in a parent object with row identifiers: `{"row1":{"name":"John"},"row2":{"name":"Jane"}}`. Useful when you need indexed access by row number. **Array of Arrays** - Preserves the raw tabular structure: `[["name","age"],["John",30],["Jane",25]]`. First array contains headers, subsequent arrays contain data. Best for maintaining exact CSV structure or when column order matters more than named access. **Column-Oriented** - Reorganizes data by columns instead of rows: `{"name":["John","Jane"],"age":[30,25]}`. Ideal for data analysis, charting libraries, and when you need to process entire columns at once. Choose based on how you'll consume the data in your application.

How do I convert JSON to CSV?

Converting JSON to CSV: (1) **Switch Mode** - Click 'JSON to CSV' at the top of the tool. (2) **Paste JSON** - Enter a JSON array of objects in the input box or upload a .json file. The JSON must be an array format: `[{},{},...]`. Single objects or nested structures need adjustment. (3) **Configure CSV Options** - Enable 'Flatten nested objects' to convert nested structures like `{"user":{"name":"John"}}` into flat columns `user.name`. Choose 'Array handling': join arrays with semicolons, create separate columns, or use first element only. Set 'Null/Undefined as' to specify how empty values appear (blank by default). (4) **Line Ending** - Select LF (Unix/Mac) or CRLF (Windows) based on your target system. (5) **Quote Options** - Enable 'Quote all fields' to wrap every value in quotes (safer for fields with special characters), or let the tool quote only when necessary. (6) **Convert** - Preview the data table, then view CSV output. (7) **Download** - Save as .csv file for use in Excel, Google Sheets, or database import tools.

What CSV delimiters are supported?

The converter supports five delimiter types: **Comma (,)** - The standard CSV delimiter used in US/UK regions and most software. Default for Excel in English locales. **Semicolon (;)** - Common in European countries where commas are used as decimal separators (e.g., '1,5' for 1.5). Default Excel delimiter in many EU locales. **Tab (\t)** - Tab-separated values (TSV), often used for data exports from databases and web applications. Better for data containing commas. **Pipe (|)** - Alternative delimiter when data frequently contains commas and semicolons. Common in log files and Unix tools. **Custom** - Define any single or multi-character delimiter for specialized formats. **Auto-detect** (recommended) - Analyzes the first row to automatically identify the most likely delimiter by counting occurrences. Works reliably for standard formats. Choose 'Auto-detect' unless you know your CSV uses an unusual delimiter or the detection fails. The tool handles quoted fields correctly regardless of delimiter, so 'Product Name,Description' with commas in quotes won't break parsing.

What does 'First row as headers' mean?

'First row as headers' determines how the converter interprets your CSV structure. **Enabled (default)** - The first row contains column names/headers, not data. These headers become JSON object property names. Example: CSV `name,age\nJohn,30` converts to `[{"name":"John","age":30}]`. This is standard for most CSV exports from databases, Excel, and web applications. Use this when your CSV has descriptive column names in row 1. **Disabled** - The first row is treated as data, not headers. The converter generates generic property names: `column1`, `column2`, etc. Example: Same CSV converts to `[{"column1":"name","column2":"age"},{"column1":"John","column2":30}]`. Use this for: (1) CSV files with no header row (rare), (2) Data-only files where you'll manually define headers later, (3) Numeric data matrices without column labels. Most real-world CSVs have headers, so leave this enabled. If your conversion looks wrong, check whether row 1 is headers or data and toggle accordingly.

What is data type auto-detection?

Data type auto-detection automatically converts CSV string values to appropriate JSON data types, making the output ready for direct use in applications. **Enabled (recommended)** - The converter analyzes each cell and converts: (1) **Numbers** - '123', '45.67', '-10' become numeric `123`, `45.67`, `-10` instead of strings. Essential for mathematical operations and sorting. (2) **Booleans** - 'true', 'false' (case-insensitive) become boolean `true`, `false`. (3) **Null** - 'null' string becomes JSON `null` value. (4) **Strings** - Everything else remains a string. This prevents type coercion issues when using the JSON in JavaScript, TypeScript, or databases that expect proper types. **Disabled** - All values remain strings: `{"age":"30"}` instead of `{"age":30}`. Use this when: (1) You need to preserve leading zeros ('0123' should stay '0123', not become 123), (2) All data should be treated as text regardless of content, (3) You'll handle type conversion manually in your application. For most use cases, enable auto-detection to avoid bugs caused by '30' + 5 = '305' instead of 35.

How do I handle nested JSON objects when converting to CSV?

CSV is inherently flat (rows and columns), while JSON supports nested structures, creating challenges when converting JSON to CSV. **Flatten Nested Objects (recommended)** - Converts nested structures into dot-notation columns. Example: `{"user":{"name":"John","email":"john@example.com"},"active":true}` becomes CSV columns: `user.name, user.email, active` with values `John, john@example.com, true`. This preserves all data in a flat format that spreadsheets can handle. Use when you need to preserve structure and don't mind multiple columns. **Keep Nested (JSON strings)** - Disable flattening to convert nested objects to JSON strings within CSV cells: `user, active` with values `{"name":"John","email":"john@example.com"}, true`. The nested object becomes a single escaped string. Use when you want to preserve exact JSON structure and will parse cells back to objects later. **Manual restructuring** - For complex nested structures, consider restructuring your JSON before conversion. Deeply nested arrays-of-objects often need custom processing. Flattening works for 2-3 levels but becomes unwieldy with deeper nesting.

What are common CSV to JSON conversion errors?

Common conversion errors and solutions: **'No data found in CSV'** - Your input is empty or contains only whitespace. Paste actual CSV content or upload a valid file. **'Invalid JSON' (JSON to CSV)** - Your JSON has syntax errors (missing quotes, trailing commas, unescaped characters). Validate JSON at jsonlint.com first. **'JSON must be an array'** - JSON to CSV requires an array format `[{},{},...]`. Wrap single objects in brackets: `{"name":"John"}` → `[{"name":"John"}]`. **Misaligned columns** - Wrong delimiter selected. Try 'Auto-detect' or manually check if your CSV uses semicolons (European format) instead of commas. **Quoted fields not parsing** - CSV has improperly quoted fields. Ensure quotes are doubled inside quoted strings: `"Product ""Pro"" Edition"` for `Product "Pro" Edition`. **Type conversion issues** - Numbers stay as strings. Enable 'Auto-detect data types' to convert '123' to numeric 123. **Empty rows** - Enable 'Skip empty rows' to ignore blank lines in CSV. **Extra columns** - CSV has inconsistent column counts across rows. Ensure all rows have the same number of delimiters.

Can I convert large CSV or JSON files?

Yes, but browser memory limits apply. **File size limits:** This tool processes data entirely in your browser (client-side), so performance depends on your device's RAM and browser. **Realistic limits:** (1) **Small files (<1MB / <10,000 rows)** - Process instantly with full preview and no issues. Ideal for most use cases. (2) **Medium files (1-10MB / 10,000-100,000 rows)** - Process within seconds. Preview may paginate due to DOM rendering limits. Works well on modern computers. (3) **Large files (10-50MB / 100,000-500,000 rows)** - May take 10-30 seconds to convert. Browser might become temporarily unresponsive. Disable preview for better performance. (4) **Very large files (>50MB / >500,000 rows)** - May fail due to memory limits. Browser tab might crash. Consider splitting files or using server-side tools. **Performance tips:** (1) Close other browser tabs to free memory, (2) Use a desktop computer rather than mobile, (3) For multi-gigabyte files, use command-line tools like `csvkit` or Python pandas instead. This tool prioritizes convenience for typical data conversion tasks (<10,000 rows) where instant browser-based processing is most valuable.

Is my data safe when using this converter?

**100% safe - all processing happens in your browser.** This tool uses pure client-side JavaScript with zero server communication for data processing: (1) **No uploads** - Your CSV and JSON data never leaves your device. Unlike cloud-based converters that upload files to remote servers, this tool processes everything locally in your browser's memory. (2) **No tracking** - No analytics track your data, conversion patterns, or file contents. The tool doesn't know what you're converting. (3) **No storage** - Data is not saved to cookies, localStorage, or any persistent storage. Close the tab and everything is erased from memory. (4) **Works offline** - Once the page loads, you can disconnect from the internet and continue converting files indefinitely. (5) **Open source** - The JavaScript code is visible in your browser's developer tools. You can audit exactly what the tool does with your data. This privacy-first architecture makes the converter safe for: sensitive business data, personal information, confidential client data, proprietary information under NDA, financial records, healthcare data, and any other information you wouldn't want sent to third-party servers. For absolute maximum security with highly sensitive data, download the tool's code and run it on an air-gapped computer.