JSON to CSV Instantly

Key Features and Benefits

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  Automatic Header Generation from JSON Keys — The converter inspects every object in your JSON array and extracts a union of all unique keys to build the CSV header row. This matters when your JSON records are not uniform — some objects might have an email field while others do not. The converter creates a column for every key that appears in any record and fills in empty cells where a particular record lacks that field. You get a complete, consistent header without manually specifying column names.
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  Dot-Notation Flattening for Nested Objects — Nested JSON objects get flattened into single-level keys using dot notation. A structure like {user: {profile: {name: "Alice"}}} becomes a column header user.profile.name with the value Alice. This approach preserves the path to every value, so you can reconstruct the original nesting if needed. The alternative — ignoring nested data or serializing entire sub-objects as strings — loses information and creates messy CSV output that no spreadsheet can parse meaningfully.
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  RFC 4180 Compliant Output — The generated CSV strictly follows RFC 4180. Fields containing commas, double quotes, or newlines are wrapped in double quotes. Any double quote inside a field is escaped by doubling it — so a value like He said "hello" becomes "He said ""hello""" in the output. Line endings use CRLF as the spec requires. This compliance means the output imports cleanly into Excel, Google Sheets, LibreOffice Calc, database import tools, and any other software that respects the standard.
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  Array Value Handling — When a JSON field contains an array of primitive values — like tags: ["javascript", "python", "go"] — the converter joins them into a single delimited string within the CSV cell, typically separated by semicolons or pipes to avoid conflict with the comma delimiter. Arrays of objects get flattened further, with indexed keys like items.0.name and items.1.name becoming separate columns. This gives you full visibility into array data without losing structure.
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  Custom Delimiter Support — While comma is the default, the converter supports tab, semicolon, and pipe delimiters for output. Semicolons are the standard CSV delimiter in European locales where the comma serves as a decimal separator. Tab-separated values — TSV — work well for data that contains many commas naturally, like address fields or product descriptions. Choosing the right delimiter upfront saves you from escaping headaches downstream.
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  Client-Side Processing for Data Privacy — The conversion runs entirely in your browser. Your JSON data — which might contain customer records, API secrets, financial figures, or personal information — never leaves your machine. There is no upload, no server-side processing, no logging. For teams working under GDPR, HIPAA, or SOC 2 requirements, this is not a nice-to-have. It is a requirement.

How to Convert JSON to CSV

1. 1

   Prepare Your JSON Input

   Start with a JSON array of objects. Each object represents one row in the resulting CSV, and each key represents a column. Make sure your input is valid JSON — missing commas, trailing commas, and unquoted keys will cause parse errors. If your data comes from an API response, the array is often nested under a key like data or results, so extract just the array portion before converting. A quick way to validate: paste it into a JSON formatter first and confirm it parses without errors.

2. 2

   Configure Flattening Depth

   Decide how deep you want nested objects flattened. A depth of 1 flattens only the top-level nested objects. A depth of 3 handles structures like order.shipping.address.zip. Setting the depth too shallow means nested data gets serialized as JSON strings in your CSV cells. Setting it too deep on deeply recursive structures can generate hundreds of columns. For most API responses, a depth of 3 or 4 covers everything you need without creating column sprawl.

3. 3

   Choose Your Delimiter and Options

   Pick the output delimiter — comma for standard CSV, semicolon for European locale compatibility, tab for TSV. Decide whether to include a byte order mark (BOM) at the start of the file. Excel on Windows often needs the UTF-8 BOM (\uFEFF) to correctly display non-ASCII characters like accented letters, Chinese characters, or emoji. Without it, Excel may misinterpret the encoding and show garbled text. On macOS and Linux, the BOM is unnecessary and can actually cause problems with command-line tools.

4. 4

   Run the Conversion

   Click convert and let the tool process your data. The converter iterates through every object in the array, collects all unique keys across all records, sorts them to produce a stable column order, and then writes each record as a row. Fields that exist in some records but not others get empty cells. The processing happens in a single pass for flat data and two passes for nested data — one to discover all flattened key paths, one to extract values.

5. 5

   Review and Download the CSV

   Preview the first few rows of output to verify the conversion looks right. Check that nested fields expanded into the expected column headers, that array values serialized correctly, and that special characters did not break the quoting. Then download the file or copy it to your clipboard. The downloaded file uses the .csv extension and UTF-8 encoding by default. If you plan to open it in Excel, remember the BOM setting from step three — it makes the difference between readable text and question-mark soup.

Expert Tips for JSON to CSV Conversion

Related Tools

JSON to CSV conversion is one step in a larger data pipeline. You might format and validate your JSON first, convert it to CSV for analysis, then convert the CSV back to JSON after making edits in a spreadsheet. Comparing file sizes between the two formats helps you decide which one to use for storage and transfer — CSV is often smaller for flat tabular data, while JSON is more efficient for deeply nested structures. These tools chain together naturally in everyday data workflows.