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Convert JSON data to CSV format online.
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JSON (JavaScript Object Notation) and CSV (Comma-Separated Values) are two of the most widely used data formats in the world. JSON is the lingua franca of modern APIs — it’s hierarchical, supports nested objects and arrays, and handles mixed data types with ease. CSV, on the other hand, is the workhorse of tabular data: a simple, flat format where each row is a record and each field is separated by a delimiter. CSV files open natively in Excel, Google Sheets, and every database import tool on the planet.
Converting JSON to CSV bridges these two worlds. When an API returns data as a JSON array of objects, you often need that data in a spreadsheet for analysis, reporting, or sharing with non-technical colleagues. Manually transcribing hundreds of records into Excel is impractical. A JSON to CSV converter automates this transformation: it reads each object in the JSON array, extracts the values for each key, and writes them as rows in a CSV file — complete with a header row containing the column names.
The conversion is straightforward when the JSON is a flat array of objects with consistent keys. However, real-world JSON is rarely that clean. Objects may have nested properties (e.g., {"address": {"city": "NYC"}}), some keys may be missing from certain objects, values may contain commas, quotes, or newlines that need escaping, and data types range from strings and numbers to booleans, nulls, and arrays. DevToolsHub’s JSON to CSV converter handles all of these scenarios correctly, following RFC 4180 (the CSV specification) for proper field quoting and escaping.
Common use cases include: exporting API response data for analysis in Excel, preparing data for database imports (most SQL databases accept CSV), migrating data between systems that use different formats, creating reports from JSON log files, sharing tabular data with stakeholders who prefer spreadsheets, and feeding JSON data into BI tools like Tableau or Power BI that accept CSV input.
Unlike many online converters, DevToolsHub’s tool runs entirely in your browser. Your data is never uploaded to a server, ensuring complete privacy and zero latency. It works offline once loaded and is fully responsive for use on any device.
[{"name":"Alice"}, {"name":"Bob"}]). Click “Load Example” to see how it works with sample data.{"address":{"city":"NYC"}}). When enabled, nested keys are flattened using dot notation (address.city). When disabled, nested objects are serialized as JSON strings in the cell.user.address.city), or keep them as JSON strings in the cell.JSON data frequently contains nested objects — for example, a user record might have an address property that is itself an object with city, country, and zipCode fields. Since CSV is a flat format, these nested structures need special handling. This tool offers two approaches:
With flattening enabled (recommended for most use cases): Nested objects are recursively flattened using dot notation. The key address.city becomes a separate column named “address.city”. This gives you individual columns for every nested field, which is ideal for spreadsheet analysis and database imports. Deeply nested objects like a.b.c.d are fully supported.
With flattening disabled: Nested objects are serialized as compact JSON strings within a single cell. For example, the address column would contain the value {"city":"NYC","country":"USA"}. This preserves the original structure but makes the data less convenient for flat-file analysis. It’s useful when you need to preserve the exact JSON structure for round-trip conversion.
Note that arraysare always serialized as JSON strings in CSV cells, regardless of the flatten setting. This is because arrays represent multiple values that don’t map cleanly to a single CSV cell. If you need each array element as a separate row, consider flattening your data before conversion.
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