Units on a Second Header Row — Not Data (.csv)
The same instrument export with units on a second header row instead of inside the column names, which is how a great many laboratory instruments write CSV. An importer that treats row two as data types every measurement column as text and then quietly refuses to plot anything.
wavelength,absorbance,u_absorbance,temperature
nm,AU,AU,degC
400,0.02003,0.00424,22.40
410,0.02018,0.00424,22.41
420,0.02083,0.00425,22.42
430,0.02338,0.00428,22.43
440,0.03187,0.00438,22.44
450,0.05600,0.00467,22.45
460,0.11417,0.00537,22.46
470,0.23246,0.00679,22.47
480,0.43341,0.00920,22.48
490,0.71380,0.01257,22.49
500,1.02426,0.01629,22.50
510,1.27375,0.01928,22.51
Specifications
- Header Rows
- 2
- Data Rows
- 12
- Columns
- 4
- Row2 Contents
- nm, AU, AU, degC — unit symbols, not measurements
- Naming Convention
- units in a separate row rather than in the column name
- Failure If Ignored
- every numeric column is typed as text
Testing contract
Expected to recover- Scenario
- Import the file treating the first row as names and the second as units, then check the inferred type of the absorbance column.
- Expected result
- Twelve data rows are read, absorbance is inferred as numeric with unit AU, and an importer that reads row two as data reports thirteen rows with a text-typed absorbance column instead.
What is a .csv file?
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 this 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.
How to use this file for testing
“Units on a Second Header Row — Not Data (.csv)” is a deterministic Novus Examples fixture for Scientific data, CSV parsing, Editor testing, Data import. Citation catalogs (BibTeX, RIS), chemistry structures (MDL Molfile, PDB), and gridded binary data (NetCDF, FITS) — for testing reference managers, molecule viewers, and scientific-data loaders.
Documented properties for this file: 4 columns. 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.
Scientific fixtures are small, valid, and fully synthetic — no real organism, patient, sample, or observation. Point your parser or loader at the file and check it reads the documented records, variables, or headers; binary formats ship a readable twin or metadata listing for comparison.
Code examples
import pandas as pd
df = pd.read_csv("units-in-second-header-row.csv")
print(df.head())
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