CSV to JSON Converter
Convert CSV data to JSON instantly. Supports headers, quoted fields and custom delimiters.
Why CSV to JSON Conversion Is a Daily Developer Need
CSV (Comma-Separated Values) is the universal format for data exports from Excel, Google Sheets, databases and CRMs. JSON is the universal format for APIs, NoSQL databases and JavaScript applications. Converting between them is a daily need for data engineers, frontend developers, API integrators and analysts. Our converter handles headers, quoted fields containing commas, custom delimiters (tabs, semicolons, pipes) and gives you clean, indented JSON output.
Frequently Asked Questions
How to convert a CSV file to JSON in Python? ▼
import csv, json; with open("data.csv") as f: reader = csv.DictReader(f); data = list(reader); print(json.dumps(data, indent=2)) — DictReader automatically uses the first row as keys. For large files, use pandas: pd.read_csv("data.csv").to_json(orient="records").
What is the difference between CSV and TSV format? ▼
CSV uses commas as delimiter; TSV (Tab-Separated Values) uses tab characters. TSV is preferred when data values contain commas (e.g., addresses: "123, Main Street"). Our converter supports both — select Tab delimiter for TSV files.
How to convert CSV with special characters to JSON? ▼
If your CSV contains commas within values (e.g., "New Delhi, India"), those values should be wrapped in double quotes in the CSV file: "New Delhi, India". Our parser handles quoted fields correctly. For UTF-8 characters (Hindi, Chinese), ensure your CSV is saved with UTF-8 encoding.
How to handle null/empty values in CSV to JSON conversion? ▼
Empty CSV cells convert to empty strings "" in JSON by default. For null values, you can post-process the JSON to replace "" with null. Numeric columns where the cell is blank should be handled in your application — our converter preserves the original string representation for maximum compatibility.
What is the maximum CSV file size for online conversion? ▼
Our browser-based converter handles CSV files up to 50–100MB reliably depending on your browser and device memory. For very large CSVs (1GB+), command-line tools (jq, csvkit) or pandas in Python are more appropriate.