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csv1.6 KB

Fieldnote Supply Shop: Inventory and price feed with variants

Inventory and price feed with variants for Fieldnote Supply Shop. 12 variant rows over 6 products, two finishes each. Every gtin is a valid 13-digit GS1 number whose final digit is the modulo-10 check digit, and all 12 begin with a zero, so a spreadsheet that types the column as a number destroys the identifier. Quantities sum to 285 units and match the variant stock in the shop model.

csv

text/csv

1.6 KB
Document Set
ecommerce
Industry
retail
Source Kit
retail-commerce
Synthetic
true
As Of
2026-09-08
Rows
12

Binary csv: no in-browser preview. Download it above to open in a compatible application.

Specifications

Document Set
ecommerce
Industry
retail
Source Kit
retail-commerce
Synthetic
true
As Of
2026-09-08
Rows
12
Columns
14
Leading Zero Identifiers
12
Units Available
285
Encoding
UTF-8

Testing contract

Expected to pass
Scenario
Import the feed, then reopen it in a spreadsheet, save it, and import it again.
Expected result
The first import reads 12 variants whose gtin check digits all verify. After a spreadsheet round trip the leading zero is gone, every gtin is 12 digits and the check digit fails, which is the regression this fixture is for.

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

“Fieldnote Supply Shop: Inventory and price feed with variants” is a deterministic Novus Examples fixture for Data import. Realistic faker-generated datasets with documented schemas for testing import and ETL flows.

Documented properties for this file: 12 rows · 14 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.

Code examples

import pandas as pd

df = pd.read_csv("inventory-feed.csv")
print(df.head())
print(df.dtypes)

Generated by generation/industry_documents.py. Free for any use, no attribution required, license.