Harbour Kitchen Group: Cost of goods sold that contradicts the count sheet
Cost of goods sold that contradicts the count sheet for Harbour Kitchen Group. Intentionally inconsistent. Row 3 reports a closing count of 91.00 each for ING-03 (Beef Patty), the counted figure with the last two whole digits transposed, where inventory-count-sheet.csv, inventory-variance.xlsx and cogs-report.json all count 19.00 each. Every derived value follows the wrong count, so the file is internally consistent and its total of 3075.48 CAD differs from the correct 3241.08 CAD by -165.60 CAD.
csv
text/csv
- Kit
- restaurant-group
- 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-group
- 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
- 7
- Columns
- 11
- Intentionally Invalid
- true
- Defect
- closing-inventory-contradicts-count-sheet
- Contradicts
- p9c-restaurant-group-count-sheet
- Delimiter
- ,
- Encoding
- UTF-8
- Line Endings
- LF
Testing contract
Expected to fail- Scenario
- Use cost of goods sold that contradicts the count sheet in the Harbour Kitchen Group costing and daily operations workflow.
- Expected result
- Intentionally inconsistent. Row 3 reports a closing count of 91.00 each for ING-03 (Beef Patty), the counted figure with the last two whole digits transposed, where inventory-count-sheet.csv, inventory-variance.xlsx and cogs-report.json all count 19.00 each. Every derived value follows the wrong count, so the file is internally consistent and its total of 3075.48 CAD differs from the correct 3241.08 CAD by -165.60 CAD.
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
“Harbour Kitchen Group: Cost of goods sold that contradicts the count sheet” 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: 7 rows · 11 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("cogs-report-inconsistent.csv")
print(df.head())
print(df.dtypes)Related files
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Generated by generation/restaurant_costing.py. Free for any use, no attribution required, license.