csv5.6 KB

Ember Lane Pizza: Supplier price list CSV, semicolon and decimal comma

Supplier price list CSV, semicolon and decimal comma for Ember Lane Pizza. The same 48 price rows re-exported the way a European supplier portal writes them: UTF-8 with a byte-order mark (EF BB BF), semicolon field separators, CRLF line endings, and decimal commas in list_unit_price, price_per_case and contract_tier_unit_price. Column names, column order and every value are identical to price-list.csv; only the encoding and the separators differ.

Data import CSV parsing Encoding detection

csv

text/csv

5.6 KB

Kit: restaurant-pizzeria
Schema Version: 1
Synthetic: true
As Of: 2026-09-08
Currency: CAD
Tax Name: GST

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

Specifications

Kit: restaurant-pizzeria
Schema Version: 1
Synthetic: true
As Of: 2026-09-08
Currency: CAD
Tax Name: GST
Tax Rate: 0.05
Rows: 48
Columns: 15
Delimiter: semicolon
Encoding: UTF-8
Byte Order Mark: true
Line Endings: CRLF
Decimal Separator: ,

Testing contract

Expected to pass

Scenario: Detect the byte-order mark, the semicolon separator and the decimal comma, then prove the parsed values equal those parsed from price-list.csv.
Expected result: The same 48 price rows re-exported the way a European supplier portal writes them: UTF-8 with a byte-order mark (EF BB BF), semicolon field separators, CRLF line endings, and decimal commas in list_unit_price, price_per_case and contract_tier_unit_price. Column names, column order and every value are identical to price-list.csv; only the encoding and the separators differ.

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

“Ember Lane Pizza: Supplier price list CSV, semicolon and decimal comma” is a deterministic Novus Examples fixture for Data import, CSV parsing, Encoding detection. Realistic faker-generated datasets with documented schemas for testing import and ETL flows.

Documented properties for this file: 48 rows · 15 columns · UTF-8 · CRLF. 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("price-list-semicolon-decimal-comma.csv")
print(df.head())
print(df.dtypes)

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