Harbour Kitchen Group: Waste and spoilage log
Waste and spoilage log for Harbour Kitchen Group. 15 dated waste entries across 11 columns, totalling 31.90 CAD at standard cost. The quantities per ingredient are exactly the recorded waste that inventory-variance.xlsx and cogs-report.xlsx deduct.
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
- 15
- Columns
- 11
- Total Value Cad
- 31.9
- Half Cent Tie Rows
- Rounding
- half up, 2 places
- Delimiter
- ,
- Encoding
- UTF-8
- Line Endings
- LF
Testing contract
Expected to pass- Scenario
- Use waste and spoilage log in the Harbour Kitchen Group costing and daily operations workflow.
- Expected result
- 15 dated waste entries across 11 columns, totalling 31.90 CAD at standard cost. The quantities per ingredient are exactly the recorded waste that inventory-variance.xlsx and cogs-report.xlsx deduct.
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: Waste and spoilage log” is a deterministic Novus Examples fixture for Data import, CSV parsing. Realistic faker-generated datasets with documented schemas for testing import and ETL flows.
Documented properties for this file: 15 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("waste-spoilage-log.csv")
print(df.head())
print(df.dtypes)Related files
- csvAlder Table Bistro: Allergen matrixAllergen matrix for Alder Table Bistro. 4 menu items across 18 columns: the fourteen listed allergens plus a count and a sources column naming the ingredient behind every Y. Derived from the recipe lines, so a dish whose recipe contains a dairy ingredient reads Y under milk. 2 of 4 dishes declare at least one allergen.
- csvAlder Table Bistro: Allergen matrix missing a menu itemAllergen matrix missing a menu item for Alder Table Bistro. Intentionally incomplete. 3 rows where the recipes cost 4 menu items. MENU-04 (Potato gratin) has no row, although it has costed recipe lines in plate-costs.csv and sales in sales-mix-pmix.csv. Its correct row would declare: milk: Cream.
- csvAlder Table Bistro: Cleaning scheduleCleaning schedule for Alder Table Bistro. 18 tasks across 6 areas and 11 columns, with frequency in days, the responsible role, the chemical and its contact time, the last completion date and a next-due date that is exactly last_completed plus frequency_days. 4 task(s) are overdue at the period end.
- csvAlder Table Bistro: Cost of goods sold that contradicts the count sheetCost of goods sold that contradicts the count sheet for Alder Table Bistro. Intentionally inconsistent. Row 3 reports a closing count of 22.20 kg for ING-03 (Potatoes), the counted figure with the two decimal digits transposed, where inventory-count-sheet.csv, inventory-variance.xlsx and cogs-report.json all count 22.02 kg. Every derived value follows the wrong count, so the file is internally consistent and its total of 1574.49 CAD differs from the correct 1574.81 CAD by -0.32 CAD.
- csvAlder Table Bistro: HACCP temperature logHACCP temperature log for Alder Table Bistro. 84 readings across 13 columns: 3 units checked twice a day for fourteen days. Each row carries its own lower and upper limit, so the within_limit column can be recomputed from the row beside it. 2 readings fall outside their limit (TEMP-038, TEMP-071) and only those rows carry a corrective action.
- csvAlder Table Bistro: Inventory count sheetInventory count sheet for Alder Table Bistro. 6 ingredients across 17 columns: par level, opening count, receipts, theoretical usage, recorded waste, theoretical closing, counted closing and the variance between them, priced at standard cost. 0 item(s) close below par. These counted closing quantities are the ones cogs-report-inconsistent.csv contradicts.
Generated by generation/restaurant_costing.py. Free for any use, no attribution required, license.