Gridded Air Temperature — CSV Ground Truth (.csv)
Every value from the CF-1.8 NetCDF grid flattened to one row per cell, with the axis values spelled out in full. Diff a NetCDF-to-table export against this file to prove the reader walked the dimensions in (time, lat, lon) order and did not silently transpose the array.
time_hours,lat_degrees_north,lon_degrees_east,tas_kelvin
0,-60.0,0.0,270.000
0,-60.0,60.0,268.500
0,-60.0,120.0,265.500
0,-60.0,180.0,264.000
0,-60.0,240.0,265.500
0,-60.0,300.0,268.500
0,-30.0,0.0,280.500
0,-30.0,60.0,279.000
0,-30.0,120.0,276.000
0,-30.0,180.0,274.500
0,-30.0,240.0,276.000
0,-30.0,300.0,279.000
0,0.0,0.0,291.000
0,0.0,60.0,289.500
0,0.0,120.0,286.500
0,0.0,180.0,285.000
0,0.0,240.0,286.500
0,0.0,300.0,289.500
0,30.0,0.0,280.500
0,30.0,60.0,279.000
0,30.0,120.0,276.000
0,30.0,180.0,274.500
0,30.0,240.0,276.000
0,30.0,300.0,279.000
0,60.0,0.0,270.000
0,60.0,60.0,268.500
0,60.0,120.0,265.500
0,60.0,180.0,264.000
0,60.0,240.0,265.500
0,60.0,300.0,268.500
6,-60.0,0.0,271.500
6,-60.0,60.0,270.000
6,-60.0,120.0,267.000
6,-60.0,180.0,265.500
6,-60.0,240.0,267.000
6,-60.0,300.0,270.000
6,-30.0,0.0,282.000
6,-30.0,60.0,280.500
6,-30.0,120.0,277.500
6,-30.0,180.0,276.000
6,-30.0,240.0,277.500
6,-30.0,300.0,280.500
6,0.0,0.0,292.500
6,0.0,60.0,291.000
6,0.0,120.0,288.000
6,0.0,180.0,286.500
6,0.0,240.0,288.000
6,0.0,300.0,291.000
6,30.0,0.0,282.000Specifications
- Rows
- 120
- Columns
- 4
- Layout
- long (one row per grid cell)
- Units
- hours, degrees_north, degrees_east, K
- Precision
- 3 decimals
Testing contract
Reference control- Scenario
- Flatten the paired NetCDF grid to long format with a reader of your choice and diff the result against this file.
- Expected result
- All 120 rows match to three decimal places with time varying slowest and lon fastest; any transposition of the lat/lon axes produces a mismatch on row 2.
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
“Gridded Air Temperature — CSV Ground Truth (.csv)” is a deterministic Novus Examples fixture for Scientific data, Conversion testing, Editor testing. 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: 120 rows · 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("gridded-temperature-cf.csv")
print(df.head())
print(df.dtypes)Related files
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- sdfEthanol — SDfile With Data Fields (.sdf)An SDfile wrapping the identical ethanol molfile plus five tagged data fields and the mandatory $$$$ terminator. The property block syntax — a header line, a value and a blank line — is where SDfile parsers usually diverge from molfile parsers.

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