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csv693 B

Copper Oven Bakery: Product mix carrying items the menu does not have

Product mix carrying items the menu does not have for Copper Oven Bakery. Intentionally inconsistent. 6 rows where sales-mix-pmix.csv has 4. MENU-90 and MENU-91 are not in the shared menu table, and the first row renames MENU-01 to "Yeasted loaf (lunch)", which has a doubled space and a suffix the menu does not carry. The remaining rows are correct.

csv

text/csv

693 B
Kit
restaurant-bakery
Industry
food-service
Schema Version
1
Synthetic
true
As Of
2026-09-08
Currency
CAD

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

Specifications

Kit
restaurant-bakery
Industry
food-service
Schema Version
1
Synthetic
true
As Of
2026-09-08
Currency
CAD
Period Start
2026-08-20
Period End
2026-09-02
Rows
6
Columns
12
Intentionally Invalid
true
Defect
menu-items-not-in-the-menu-table
Unknown Ids
MENU-90, MENU-91
Contradicts
p9c-restaurant-bakery-pmix
Delimiter
,
Encoding
UTF-8
Line Endings
LF

Testing contract

Expected to fail
Scenario
Use product mix carrying items the menu does not have in the Copper Oven Bakery costing and daily operations workflow.
Expected result
Intentionally inconsistent. 6 rows where sales-mix-pmix.csv has 4. MENU-90 and MENU-91 are not in the shared menu table, and the first row renames MENU-01 to "Yeasted loaf (lunch)", which has a doubled space and a suffix the menu does not carry. The remaining rows are correct.

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

“Copper Oven Bakery: Product mix carrying items the menu does not have” is a deterministic Novus Examples fixture for Data import, Error handling, CSV parsing. Realistic faker-generated datasets with documented schemas for testing import and ETL flows.

Documented properties for this file: 6 rows · 12 columns · UTF-8 · LF. 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("sales-mix-pmix-unknown-items.csv")
print(df.head())
print(df.dtypes)

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