Tab-Separated Values (TSV)
A tab-separated values file with a header and 20 rows — for testing TSV parsing and delimiter handling.
id name city amount
1 Grace Paris 516.7
2 Alan Berlin 950.96
3 Katherine Toronto 152.72
4 Linus Austin 949.16
5 Radia Oslo 318.71
6 Tim Tokyo 429.09
7 Barbara Nairobi 829.43
8 Dennis London 415.11
9 Margaret Paris 554.1
10 Ada Berlin 37.28
11 Grace Toronto 755.98
12 Alan Austin 542.76
13 Katherine Oslo 336.43
14 Linus Tokyo 790.54
15 Radia Nairobi 310.16
16 Tim London 458.96
17 Barbara Paris 142.7
18 Dennis Berlin 409.08
19 Margaret Toronto 211.42
20 Ada Austin 269.69
Specifications
- Rows
- 20
- Columns
- 4
- Delimiter
- tab
- Encoding
- UTF-8
What is a .tsv file?
TSV (Tab-Separated Values) is a plain-text tabular format like CSV but using tab characters as field delimiters. Because tabs rarely appear in data, it often needs less quoting than CSV. It is common in bioinformatics, logs, and command-line data workflows.
How to use this file
Use an example TSV to test tab-delimited parsing, header and column handling, and pipelines that ingest tabular data from Unix tools or scientific datasets.
How to use this file for testing
“Tab-Separated Values (TSV)” is a deterministic Novus Examples fixture for CSV parsing. Clean and deliberately messy CSVs — quoted commas, embedded newlines, ragged rows, odd delimiters, and encodings.
Documented properties for this file: 20 rows · 4 columns · UTF-8. Compare results against paired or grouped companions on this page when present (clean↔damaged, searchable↔scanned, or format twins) so scores stay reproducible across runs.
Download the file once, keep the path stable in CI or local scripts, and treat the spec table as the contract: dimensions, seeds, field lists, and roles are intentional. Corrupt or invalid samples are labelled as such — expect parsers to fail loudly rather than silently accept them.
Data fixtures document their exact quirks — delimiters, encodings, null handling, schema, and row counts — in the spec table. Point your parser or importer at the file and assert it handles the documented edge cases; clean and deliberately-messy siblings make before/after diffs straightforward.
Feed the file to your parser and assert it handles the documented quirks — quoted delimiters, embedded newlines, ragged rows, or invalid syntax; the valid↔invalid distinction is labelled in the title.
Code examples
import pandas as pd
df = pd.read_csv("data.tsv", sep="\t")
print(df.head())Related files
- csv10,000-Row CSVA CSV with 10,000 data rows — for testing streaming parsers, memory handling, and import performance.
- csvClean CSVA clean, well-formed CSV with a header and 20 rows — the baseline case for CSV parser testing.
- csvCSV Edge — Empty FieldsTiny SAMPLE CSV (empty-fields) exercising delimiter/quoting edge behaviour.
- csvCSV Edge — Hash CommentedTiny SAMPLE CSV (hash-commented) exercising delimiter/quoting edge behaviour.
- csvCSV Edge — Header OnlyTiny SAMPLE CSV (header-only) exercising delimiter/quoting edge behaviour.
- csvCSV Edge — Mixed QuotingTiny SAMPLE CSV (mixed-quoting) exercising delimiter/quoting edge behaviour.
Generated by generation/data_tabular.py. Free for any use, no attribution required — license.