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Alder Table Bistro: Drinks list as data

Drinks list as data for Alder Table Bistro. 8 rows and 7 columns pairing every printed drink line with the till item code it imports as, the serve size in millilitres and the basis of its price. The three drinks sold both ways appear twice, once per service.

csv

text/csv

666 B
Kit
restaurant-bistro
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-bistro
Industry
food-service
Schema Version
1
Synthetic
true
As Of
2026-09-08
Currency
CAD
Menu Items
4
Rows
8
Columns
7
Delimiter
,
Encoding
UTF-8
Line Endings
LF

Testing contract

Expected to pass
Scenario
Use drinks list as data in the Alder Table Bistro menu, allergen and till import workflow.
Expected result
8 rows and 7 columns pairing every printed drink line with the till item code it imports as, the serve size in millilitres and the basis of its price. The three drinks sold both ways appear twice, once per service.

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

“Alder Table Bistro: Drinks list as data” 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: 8 rows · 7 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("drinks-list.csv")
print(df.head())
print(df.dtypes)

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