Cedar Street Tacos — Guest review import CSV
Guest review import CSV for Cedar Street Tacos. 18 data rows, 5 columns and 18 expected accepted rows.
Source,Date,Rating,Review,Location
Website feedback,2026-08-15,5,Friendly service and a well prepared order.,Main kitchen
Receipt survey,2026-08-16,4,The queue was longer than expected.,Main kitchen
Website feedback,2026-08-17,3,Clear choices and helpful staff.,Main kitchen
Receipt survey,2026-08-18,4,Friendly service and a well prepared order.,Main kitchen
Website feedback,2026-08-19,5,The queue was longer than expected.,Main kitchen
Receipt survey,2026-08-20,4,Clear choices and helpful staff.,Main kitchen
Website feedback,2026-08-21,2,Friendly service and a well prepared order.,Main kitchen
Receipt survey,2026-08-22,5,The queue was longer than expected.,Main kitchen
Website feedback,2026-08-23,4,Clear choices and helpful staff.,Main kitchen
Receipt survey,2026-08-24,5,Friendly service and a well prepared order.,Main kitchen
Website feedback,2026-08-25,4,The queue was longer than expected.,Main kitchen
Receipt survey,2026-08-26,3,Clear choices and helpful staff.,Main kitchen
Website feedback,2026-08-27,4,Friendly service and a well prepared order.,Main kitchen
Receipt survey,2026-08-28,5,The queue was longer than expected.,Main kitchen
Website feedback,2026-08-29,4,Clear choices and helpful staff.,Main kitchen
Receipt survey,2026-08-30,2,Friendly service and a well prepared order.,Main kitchen
Website feedback,2026-08-31,5,The queue was longer than expected.,Main kitchen
Receipt survey,2026-09-01,4,Clear choices and helpful staff.,Main kitchen
Specifications
- Kit
- restaurant-food-truck
- Industry
- food-service
- Schema Version
- 1
- Synthetic
- true
- As Of
- 2026-09-08
- Rows
- 18
- Columns
- 5
- Encoding
- UTF-8
Testing contract
Expected to pass- Scenario
- Use guest review import csv in the Cedar Street Tacos purchasing, price-history, menu-costing, inventory, sales, reviews, modifiers, refunds, reservations, staffing, stock-movements, menu-pricing workflow.
- Expected result
- 18 data rows, 5 columns and 18 expected accepted rows.
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
“Cedar Street Tacos — Guest review import CSV” is a deterministic Novus Examples fixture for Data import. Realistic faker-generated datasets with documented schemas for testing import and ETL flows.
Documented properties for this file: 18 rows · 5 columns · UTF-8. 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("reviews.csv")
print(df.head())
print(df.dtypes)Related files
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Generated by generation/business_fixtures.py. Free for any use, no attribution required, license.