JSON to CSV Converter

CSV is inherently a flat, two-dimensional format (rows and columns) while JSON supports arbitrary nesting depth. The converter handles: flat JSON arrays of objects (perfect fit, one row per object), nested objects (flattened with dot notation like user.name or user.address.city), arrays within objects (joined with delimiter or expanded with index dots), and heterogeneous arrays (objects with different schemas are unified with nulls for missing fields). Limitations: deeply nested structures may produce many columns when flattened, arrays of primitive values with inconsistent lengths are joined into single cells, and very wide JSON objects (100+ properties) produce very wide CSV files that may exceed spreadsheet column limits. For extremely complex JSON, consider first simplifying the structure or converting to multiple related CSV files with foreign key relationships.

The converter uses configurable strategies for nested data. Nested objects are handled by flattening: an object like {user: {name: John, address: {city: NYC}}} becomes columns user.name and user.address.city. Arrays within objects are handled in three modes: join mode (combines items into a single comma-delimited cell like red,green,blue), expand mode (creates item[0], item[1], item[2] columns for indexed access), and rows mode (duplicates the other columns for each array item, creating multiple CSV rows). For arrays of objects (the most common conversion scenario), each array element becomes one CSV row with columns from the object's properties. The converter automatically detects the most common structure and applies appropriate flattening, but you can override per-field behavior in advanced settings.

The tool supports comma (,), semicolon (;), tab (\t), pipe (|), and custom single-character or multi-character delimiters. The choice depends on your data and target application: comma is the most widely used and recognized as the CSV standard, but requires proper quoting of values containing commas; semicolon is the default separator in many European locales that use comma as decimal separator (avoids conflict between field separators and decimal points); tab (TSV format) is ideal when your data contains many commas that would require quoting; pipe is useful when both commas and semicolons appear in data values. Regardless of delimiter chosen, values containing the delimiter character are automatically quoted with double quotes per RFC 4180, and embedded double quotes are escaped as two consecutive double quotes.

While this tool focuses on JSON to CSV conversion, making edits in a spreadsheet and converting back is a common workflow. The round-trip is straightforward for flat data: your CSV columns map back to JSON field names and rows map to array items. However, information is lost during conversion: flattened nested structures (user.name column) cannot automatically reconstruct the nested object {user: {name: value}} without schema hints (you can use our separator configuration like . as the nesting indicator to enable reconstruction), and joined arrays (red,green,blue) need to be split back by their delimiter. For round-trip workflows, choose a delimiter that does not appear in your data, use consistent column naming, and document any manual schema mappings. We recommend using our companion tools or schema definitions for complex round-trip scenarios.

For files up to approximately 5MB, the entire conversion happens in your browser with no server upload, ensuring complete data privacy and fast processing. The converter processes the JSON array row by row rather than loading everything into a string stream, preventing memory bottlenecks. For encoding: the tool outputs UTF-8 by default (the standard encoding for modern applications), with optional BOM (Byte Order Mark) inclusion for Excel compatibility (Excel historically has trouble auto-detecting UTF-8 encoding in CSV files without BOM, displaying special characters as garbled text). When special characters (Chinese, Japanese, Arabic, emoji) appear in your data, always use UTF-8 output with BOM enabled if importing to Excel. For files exceeding browser memory limits, consider splitting the JSON into smaller chunks or using command-line tools like jq for initial filtering before conversion.