csv
What is a .csv file?
text/csv
CSV (Comma-Separated Values) is a plain-text tabular format where rows are lines and fields are separated by commas, with quoting rules for values that contain delimiters, quotes, or newlines. It has no formal type system and depends on encoding and dialect conventions. It is the most portable format for tabular data exchange.
How to use a .csv file
Use an example CSV to test parsers against quoting and embedded-delimiter edge cases, header handling, encoding detection, and import pipelines into databases or spreadsheets.
Download example .csv files
- Clean CSVA clean, well-formed CSV with a header and 20 rows — the baseline case for CSV parser testing.
- Messy CSV (quoted commas, newlines, ragged rows)A deliberately messy CSV: a quoted field with a comma, a quoted field with an embedded newline, escaped double-quotes, and ragged rows with too few and too many fields — the cases that break naïve parsers.
- Semicolon-Delimited CSVA CSV that uses semicolons as the delimiter (common in European locales) — for testing delimiter detection.
- Headerless CSVA CSV with no header row — for testing parsers that must infer or be told the column names.
- 10,000-Row CSVA CSV with 10,000 data rows — for testing streaming parsers, memory handling, and import performance.
- Latin-1 Encoded CSVA CSV encoded in Latin-1 (ISO-8859-1) with accented names — for testing encoding detection and mis-decoding (it will look wrong if read as UTF-8).
- Fake Users Dataset (CSV, 500 rows)A 500-row dataset of fake but realistic users (name, email, address, date of birth), generated with a fixed seed. Paired with a JSON twin.
- Fake Orders Dataset (CSV, 1000 rows)A 1000-row orders dataset whose user_id references the users dataset — a relational fixture for testing joins and import flows. Paired with a JSON twin.
and 6 more in the library.