Convert JSON to CSV Online

Turn JSON files into CSV format for easy use in Excel, Google Sheets, and data tools—upload your JSON and convert in a click.

Read Only

Convert JSON to CSV — Export JSON Data as Spreadsheet-Ready CSV

Convert JSON data to CSV format instantly with the XConvert JSON to CSV Converter. Paste your JSON array, configure flattening and column options, and get a clean CSV file ready for spreadsheets, databases, or data analysis tools. This free, client-side tool processes everything in your browser — your data never leaves your device.

JSON is the lingua franca of APIs and web applications, but when it comes to data analysis, reporting, and bulk editing, CSV remains king. Spreadsheet applications like Excel and Google Sheets, database import tools, and many business intelligence platforms expect tabular CSV data. The XConvert JSON to CSV Converter bridges this gap by flattening JSON structures into clean, well-formatted CSV output.

How to Convert JSON to CSV with XConvert (4 Steps)

  1. Open the JSON to CSV Converter — Navigate to the XConvert JSON to CSV Converter in any modern browser. No account or installation is needed.
  2. Input Your JSON Data — Paste a JSON array of objects into the input field, or upload a .json file. Each object in the array becomes a row in the CSV output.
  3. Configure Export Options — Choose the delimiter (comma, semicolon, tab), select which fields to include as columns, and configure how nested objects should be flattened (dot notation, bracket notation, or ignored).
  4. Copy or Download the CSV — The converted CSV appears in the output panel. Copy it to your clipboard or download it as a .csv file, ready to open in any spreadsheet application.

The converter automatically generates a header row from the JSON object keys and handles nested structures, arrays, and mixed data types gracefully.

What Is JSON to CSV Conversion?

JSON to CSV conversion is the process of transforming structured, hierarchical JSON data into a flat, tabular CSV format. JSON supports nested objects, arrays, and mixed types, while CSV is inherently two-dimensional — rows and columns with no nesting. The conversion process must "flatten" the JSON structure to fit the CSV model.

For example, this JSON:

[
  {"name": "Alice", "age": 30, "address": {"city": "New York", "zip": "10001"}},
  {"name": "Bob", "age": 25, "address": {"city": "London", "zip": "EC1A"}}
]

Becomes this CSV:

name,age,address.city,address.zip
Alice,30,New York,10001
Bob,25,London,EC1A

The nested address object is flattened using dot notation, creating separate columns for address.city and address.zip. This flattening strategy preserves the data hierarchy in the column names while fitting everything into a tabular structure.

JSON to CSV conversion is the reverse of CSV to JSON conversion, and together these tools enable round-trip data transformation between the two most common data exchange formats.

Comparison Table

Feature XConvert JSON to CSV Online Alternatives Scripting (Python/Node)
Client-side processing ✅ Yes ⚠️ Varies ✅ Yes (local)
No data upload ✅ Yes ❌ Often uploads ✅ Yes
Nested object flattening ✅ Dot notation ⚠️ Limited ✅ Configurable
Array handling ✅ Multiple strategies ⚠️ Varies ✅ Configurable
Custom delimiter ✅ Yes ⚠️ Limited ✅ Yes
Column selection ✅ Yes ❌ Rarely ✅ Yes
Header generation ✅ Automatic ✅ Usually ✅ Yes
Excel compatibility ✅ Proper quoting ⚠️ Varies ✅ With libraries
No installation ✅ Yes ✅ Yes ❌ Requires setup
Cost Free Free/Paid Free

Common Use Cases

  1. Exporting API Data to Spreadsheets — When you fetch data from a REST API, the response is typically JSON. Converting it to CSV lets you open it in Excel or Google Sheets for analysis, filtering, sorting, and charting without writing any code.

  2. Creating Database Import Files — Many relational databases and data warehouses accept CSV for bulk imports. Converting JSON API responses or document database exports to CSV prepares the data for import into MySQL, PostgreSQL, or data warehouse tools.

  3. Generating Reports for Non-Technical Stakeholders — Business users and managers are comfortable with spreadsheets. Converting JSON data from dashboards, analytics APIs, or monitoring tools to CSV makes it accessible to anyone who can open a spreadsheet.

  4. Data Migration from NoSQL to SQL — When migrating from document databases (MongoDB, DynamoDB) to relational databases, the first step is often flattening the JSON documents into tabular CSV format that maps to SQL table schemas.

  5. Preparing Data for Visualization Tools — Many data visualization tools (Tableau, Power BI, D3.js) can import CSV directly. Converting JSON datasets to CSV provides a universal input format that works across visualization platforms.

  6. Archiving and Backup — CSV is a simple, human-readable format that will remain accessible for decades. Converting JSON data to CSV creates archives that can be opened with any text editor, ensuring long-term data accessibility regardless of technology changes.

Technical Details of JSON Flattening

The core challenge of JSON to CSV conversion is flattening hierarchical data into a two-dimensional table. The XConvert converter uses several strategies to handle different JSON structures.

Nested objects are flattened using dot notation by default. A key path like user.address.city becomes a single column header. This preserves the structural information in the column name while creating a flat table. For deeply nested objects, the dot-separated path can become long, but it remains unambiguous and can be programmatically parsed back into a nested structure if needed.

Arrays within objects present a more complex challenge because they introduce a one-to-many relationship that does not map cleanly to a single CSV row. The converter offers several strategies: joining array elements into a single cell with a separator (e.g., "red;blue;green"), creating numbered columns for each array element (e.g., colors.0, colors.1, colors.2), or serializing the array as a JSON string within the cell. The best strategy depends on your downstream use case — joined values work well for simple lists, while numbered columns are better for structured data.

Inconsistent schemas are common in real-world JSON data, where different objects in the array may have different keys. The converter scans all objects to build a complete set of column headers (the union of all keys), then fills in empty values for objects that lack certain keys. This ensures every row has the same number of columns, which is a requirement for valid CSV. Fields that exist in some objects but not others will have empty cells in the rows where they are absent.

Tips for Best Results

  1. Start with an array of objects — The converter expects a JSON array where each element is an object. If your JSON is a single object or has a wrapper, extract the array first. Use the JSON Formatter to inspect the structure before converting.
  2. Choose the right flattening strategy — For simple nested objects, dot notation works well. For arrays, consider whether joined values or numbered columns better suit your spreadsheet workflow.
  3. Select only the columns you need — If your JSON objects have many fields, use the column selection feature to include only the relevant ones. This produces a cleaner, more focused CSV.
  4. Use semicolons for European locales — If your spreadsheet application uses commas as decimal separators (common in European locales), switch the CSV delimiter to semicolons to avoid parsing conflicts when opening the file.
  5. Validate your JSON first — Invalid JSON will produce errors or unexpected output. Paste your data into the JSON Formatter first to check for syntax errors, missing brackets, or trailing commas.
  6. Check for special characters — CSV fields containing commas, quotes, or newlines must be properly quoted. The converter handles this automatically, but verify the output if your data contains unusual characters. The HTML Entity Decoder can help if your JSON contains encoded HTML entities.

Frequently Asked Questions

What JSON structure does the converter expect?

The converter expects a JSON array of objects, where each object represents a row and each key-value pair represents a column and its value. For example: [{"name": "Alice", "age": 30}, {"name": "Bob", "age": 25}].

How does the converter handle nested JSON objects?

Nested objects are flattened using dot notation. For example, {"user": {"name": "Alice"}} becomes a column named user.name with the value Alice. This preserves the hierarchical structure in the column header while creating a flat CSV row.

What happens to arrays inside JSON objects?

Arrays can be handled in several ways depending on your configuration: joined into a single cell with a separator, expanded into numbered columns (e.g., tags.0, tags.1), or serialized as a JSON string within the cell. Choose the strategy that best fits your downstream use case.

Can I convert the CSV back to JSON?

Yes. Use the CSV to JSON Converter to reverse the process. If you used dot notation for flattening, the CSV to JSON converter can reconstruct the nested structure from the dot-separated column headers.

Does the converter handle missing fields in some objects?

Yes. The converter builds a complete set of columns from all objects in the array. Objects that lack certain fields will have empty cells in those columns. This ensures every row has the same number of fields, producing valid CSV.

Can I choose which columns to include in the CSV?

Yes. The converter provides a column selection feature that lets you include or exclude specific fields. This is useful when your JSON objects contain many fields but you only need a subset for your spreadsheet or import.

How does the converter handle special characters in values?

Values containing the delimiter character, double quotes, or newlines are automatically enclosed in double quotes following RFC 4180 conventions. Double quotes within values are escaped by doubling them. This ensures the CSV is correctly parsed by spreadsheet applications.

Is there a size limit for the JSON input?

The converter runs in your browser, so the practical limit is your device's available memory. Most modern devices can handle JSON files of several megabytes without issues. For very large datasets (hundreds of megabytes), consider using a command-line tool or scripting approach.

Can I use tab as the delimiter?

Yes. The converter supports multiple delimiters including comma, semicolon, tab, and pipe. Tab-separated output (TSV) is useful for pasting directly into spreadsheet applications or for data that contains many commas in its values.

Is my data sent to any server?

No. The XConvert JSON to CSV Converter processes all data locally in your browser using client-side JavaScript. Your JSON data never leaves your device, making it safe for sensitive, proprietary, or confidential information.

Related XConvert Tools: CSV to JSON Converter · JSON Formatter · HTML Entity Decoder · Date to Unix Timestamp · Base64 Encoder/Decoder