CSV vs JSON
When a flat table beats nested documents, and how to convert between them safely.
Pick the right shape
CSV is a flat grid of rows and columns — perfect for tabular data exported from spreadsheets and databases. JSON expresses nested, heterogeneous structures (objects inside arrays inside objects) that CSV cannot represent without conventions.
| Use CSV when… | Use JSON when… |
|---|---|
| Data is a simple table | Data is hierarchical / nested |
| Humans edit it in Excel | An API consumes it |
| One type of record | Mixed or optional fields |
Converting safely
💡
CSV has no standard type system — everything is text. Decide explicitly whether
"123" becomes a number or stays a string, or you will get silent type bugs.import csv, json
with open('data.csv', newline='', encoding='utf-8') as f:
rows = list(csv.DictReader(f))
with open('data.json', 'w', encoding='utf-8') as f:
json.dump(rows, f, indent=2, ensure_ascii=False)Going the other way (JSON → CSV) only works cleanly when every record shares the same flat keys; otherwise you must flatten nested fields into dotted column names.
FAQ
Why does my CSV have quotes everywhere?
Fields containing the delimiter, a quote, or a newline are quoted per RFC 4180. A correct parser handles this; a naive split(',') does not.
Is TSV better than CSV?
When your data contains commas, tab-separated (TSV) avoids most quoting. It is common in bioinformatics and logs.
Related
Last refreshed 2026-09-17.