JSON to CSV Converter

What is JSON to CSV?

JSON dominates web APIs; CSV dominates spreadsheets and BI tools. Converting JSON → CSV bridges that gap, letting you take API responses, MongoDB exports, or log data and analyze them in Excel, Google Sheets, Tableau, or import into databases.

Common scenarios: API response analysis (paste API output into Excel for deeper analysis), NoSQL → SQL migration (MongoDB JSON → PostgreSQL via CSV import), data deliverables for non-technical stakeholders, backup/audit logs for spreadsheet review.

Conversion example

# JSON input
[
  { "name": "Alice", "age": 30, "city": "Seoul" },
  { "name": "Bob",   "age": 25, "city": "Tokyo" }
]

# CSV output
name,age,city
Alice,30,Seoul
Bob,25,Tokyo

Handling complex structures

• Different keys per object: tool collects all unique keys as headers; missing values are empty
• Nested objects: serialized as JSON strings inside cells (preserves data, but ugly in spreadsheet view)
• Arrays inside objects: same — serialized as JSON strings
• Nested array of objects: not flattened — keep at top level for clean CSV
• Boolean/null values: true/false kept as text; null becomes empty string
• Special characters in values: commas/quotes/newlines properly escaped per RFC 4180

For deeply nested JSON

If your JSON has many nested levels (3+ deep), CSV is the wrong format — flat tables can't represent hierarchies cleanly. Options:

• Pre-flatten with jq: jq '[.users[] | {name, email, status}]' input.json
• Pre-flatten with Python: pandas' json_normalize() handles nesting elegantly
• Use Parquet or Arrow instead: better for hierarchical analytics data
• Stay in JSON: use jq for filtering instead of converting

How to Use

1. Paste a JSON array of objects, or upload a .json file.
2. Click Convert.
3. Review the CSV — open in Excel/Sheets to verify columns and rows.
4. Copy or download as .csv.

Privacy: All conversion runs in your browser. No upload.

FAQ