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JSON to CSV

Convert JSON data to CSV format with customizable options

JSON Input

Conversion Options

CSV Output

Advanced JSON to CSV Converter

Features:

  • • Large file support (up to 100MB)
  • • Smart nested object flattening
  • • Multiple delimiter options
  • • Real-time validation & preview
  • • Progress tracking for large datasets

Supported Formats:

  • • JSON arrays of objects
  • • API responses with data arrays
  • • Nested object structures
  • • Mixed data types
  • • Complex array handling

About JSON to CSV Conversion

JSON to CSV conversion transforms structured JSON data into comma-separated values format, making it compatible with spreadsheet applications, databases, and data analysis tools. Perfect for data export, reporting, and integration with business intelligence platforms.

  • Convert JSON arrays and objects to CSV format
  • Handle nested objects and flatten data structures
  • Customize delimiters, headers, and formatting
  • Support for large datasets and batch processing
  • Preserve data types and handle special characters

Conversion Features

Data Handling

  • Flatten nested JSON objects
  • Handle arrays and primitive values
  • Preserve data relationships
  • Auto-generate column headers
  • Handle missing or null values

Output Options

  • Custom field delimiters (, ; | )
  • Configurable quote characters
  • Header row customization
  • Date format standardization
  • Character encoding options

Frequently Asked Questions

How to convert JSON to CSV?

Paste or upload your JSON array into the utilAZ JSON to CSV tool and click Convert. The tool flattens nested objects using dot notation, extracts all unique keys as column headers, and outputs a downloadable CSV file. Programmatically you can use Python pandas (pd.json_normalize(data).to_csv()), Node.js json2csv, or the jq command line tool.

What is JSON to CSV converter?

A JSON to CSV converter is a tool that transforms hierarchical JSON data into a flat, tabular CSV (comma-separated values) format. Each JSON object in an array becomes one row, and each unique key becomes a column header. This makes the data compatible with spreadsheets like Excel and Google Sheets, databases, and data analysis tools.

How to convert nested JSON to CSV?

Nested JSON is converted by flattening the hierarchy using dot notation. For example, {"user":{"name":"Alice","address":{"city":"NYC"}}} becomes columns user.name and user.address.city. Arrays inside objects can be serialized as comma-separated strings in a single cell or expanded into multiple rows depending on the tool settings.

How to convert JSON to CSV in Python?

Use pandas: import pandas as pd; df = pd.json_normalize(json_data); df.to_csv('output.csv', index=False). For simple flat JSON, the built-in csv module works: csv.DictWriter(file, fieldnames=data[0].keys()). For deeply nested structures, json_normalize handles flattening automatically with dot-separated column names.

How to open JSON file in Excel as CSV?

First convert the JSON to CSV using utilAZ or a script, then open the .csv file in Excel. Alternatively, in Excel 2016+ use Data > Get Data > From File > From JSON to import directly. For older versions, convert to CSV first since Excel cannot natively parse raw JSON arrays into rows and columns.

Best free JSON to CSV converter online?

utilAZ offers a free, no-signup JSON to CSV converter that runs entirely in your browser. It handles nested objects with dot notation, supports custom delimiters, processes large files client-side for privacy, and lets you download the result instantly. No data is sent to any server.

Conversion Examples

Simple JSON Array:

JSON Input:

[
  {
    "name": "John Doe",
    "age": 30,
    "city": "New York"
  },
  {
    "name": "Jane Smith",
    "age": 25,
    "city": "Los Angeles"
  }
]

CSV Output:

name,age,city
"John Doe",30,"New York"
"Jane Smith",25,"Los Angeles"

Nested JSON Objects:

JSON Input:

[
  {
    "user": {
      "name": "Alice",
      "contact": {
        "email": "alice@example.com",
        "phone": "555-0123"
      }
    },
    "order": {
      "id": "ORDER-001",
      "total": 99.99
    }
  }
]

CSV Output:

user.name,user.contact.email,user.contact.phone,order.id,order.total
"Alice","alice@example.com","555-0123","ORDER-001",99.99

How JSON to CSV Conversion Works

Converting JSON to CSV involves transforming hierarchical data into a flat tabular format. The process handles nested objects, arrays, and mixed data types automatically.

1. Flatten

Nested objects are flattened using dot notation (e.g., user.address.city). Arrays can be serialized or expanded into columns.

2. Extract Headers

All unique keys across every JSON object become the CSV column headers. Missing fields default to empty values.

3. Serialize Rows

Each JSON object maps to one CSV row. Values containing commas, quotes, or newlines are properly escaped.

Quick Reference by Language:

JavaScript: JSON.parse() + flatMap keys + .join(',')
Python: csv.DictWriter(output, fieldnames=keys)
CLI (jq): jq -r '[.[] | to_entries[].key] | unique | @csv' file.json

Our tool handles all edge cases (nested objects, special characters, null values) automatically in the browser with no backend processing.

Best Practices

  • Validate JSON: Ensure JSON is valid before conversion
  • Handle Arrays Consistently: Decide how to represent array data (flatten vs. serialize)
  • Escape Special Characters: Properly escape quotes, commas, and newlines
  • Choose Appropriate Delimiters: Use semicolons for European locales, tabs for TSV
  • Preserve Data Types: Consider how numbers, booleans, and dates are represented
  • Test with Sample Data: Verify output with your target application
  • Consider Memory Usage: Use streaming for very large datasets

Common Use Cases

  • API data export to spreadsheets
  • Database migration and imports
  • Business intelligence reporting
  • Data analysis and visualization prep
  • CRM and ERP system integration
  • Log file analysis and processing
  • E-commerce data transformation
  • Research data compilation