JSON to CSV

The JSON to CSV Converter transforms JSON arrays or objects into comma-separated values format, ready for Excel, Google Sheets, or any spreadsheet application. Handles the tricky case that most converters get wrong: nested objects and arrays. If your JSON has user.address.street, the converter creates a column user_address_street (or user.address.street — your choice) so the data lives in a flat table while preserving all information. Built-in options for flattening strategies (dot notation, underscore, array index brackets), custom delimiters (comma, semicolon, tab, pipe), header configuration, and Excel-compatible output (UTF-8 BOM, CRLF line endings).

Converting JSON to CSV is essential for data analysts who receive JSON from APIs but need Excel pivot tables, for developers exporting database query results (MongoDB, PostgreSQL JSONB columns), for migrating between systems that prefer different formats, and for creating human-readable reports from structured data. This converter runs entirely in your browser — your JSON (which might include customer data, API responses with sensitive fields, or proprietary data) never uploads to any server.

Converting JSON to CSV requires flattening hierarchical data into a 2D table. The challenge: CSV has no native support for nesting.

Flattening strategies:

Given this JSON:
``json
{
"user": {
"name": "Alice",
"address": {
"city": "NYC",
"zip": "10001"
},
"tags": ["admin", "vip"]
}
}
``

Dot notation (most common):
``csv
user.name,user.address.city,user.address.zip,user.tags[0],user.tags[1]
Alice,NYC,10001,admin,vip
``

Underscore (SQL-friendly):
``csv
user_name,user_address_city,user_address_zip,user_tags_0,user_tags_1
Alice,NYC,10001,admin,vip
``

Bracket notation for arrays:
``csv
user.name,user.address.city,user.address.zip,user.tags
Alice,NYC,10001,"[admin,vip]"
``

Array of objects (common API response):
``json
[
{ "id": 1, "name": "Alice", "tags": ["a", "b"] },
{ "id": 2, "name": "Bob", "tags": ["c"] }
]
``

Converts to:
``csv
id,name,tags.0,tags.1
1,Alice,a,b
2,Bob,c,
``

Empty cells for missing values (row 2 has no tags.1).

CSV escaping rules (RFC 4180):

- Fields containing commas, quotes, or newlines must be enclosed in double quotes.
- Double quotes within quoted fields are escaped as two double quotes (Hello "World" becomes "Hello ""World""").
- Line endings: CRLF (Windows) is the spec; LF (Unix) is commonly accepted.

Excel compatibility:

- UTF-8 BOM — Excel requires BOM to recognize UTF-8 encoding. Without it, non-ASCII chars (accents, CJK) appear garbled.
- CRLF line endings — Excel accepts both LF and CRLF, but CRLF is safer.
- Semicolon delimiter — European Excel uses semicolons. Same data file, different regional settings.
- Separator hint — First line sep=, or sep=; tells Excel which delimiter to use.

Handling primitives vs objects:

- Top-level array of objects: each object becomes a row. Most common case.
- Top-level single object: becomes a single-row CSV (one row with the keys as columns).
- Top-level primitive or array of primitives: limited CSV representation.

Column order:

- Alphabetical (deterministic, default).
- First-seen order (original JSON key order, may vary).
- Manual ordering (specify column list).

Missing fields / inconsistent shapes:

JSON allows objects in an array to have different keys:

``json
[
{ "name": "Alice", "age": 30 },
{ "name": "Bob", "city": "NYC" }
]
``

CSV has fixed columns. The converter takes the union of all keys and leaves empty cells for missing values.

JSON to CSV vs CSV to JSON: Opposite conversions. JSON to CSV is lossy (flattens structure). CSV to JSON is reversible (preserves the 2D nature). See our CSV to JSON for the reverse direction.

JSON to CSV vs JSON to Excel (.xlsx): Excel format supports multiple sheets, formatting, formulas. CSV is plain text. For simple data export, CSV is sufficient. For rich formatting, use tools like SheetJS to produce .xlsx directly.

JSON to CSV vs JSON to SQL: SQL INSERT statements are another way to get JSON into a database. Use our JSON to SQL for direct database import. CSV is simpler; SQL is more precise.

JSON to CSV vs jq/jtbl (CLI tools): CLI tools handle huge files better and integrate into pipelines. This browser tool handles interactive conversion with visual feedback. Use CLI for automation, this tool for one-off conversion.

Flattening strategies: Dot notation is the most common and readable. Underscore is SQL-friendly (column names without dots). Bracket notation preserves array syntax. Pick based on where the CSV will be consumed.

CSV vs TSV (Tab-separated): TSV uses tabs instead of commas. Advantage: tabs rarely appear in text data, reducing escaping needs. Good for scientific data, database dumps. CSV is more universally recognized.