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csv955 B

Pine Property Services: Rent roll whose unit areas do not sum to the building area

Rent roll whose unit areas do not sum to the building area for Pine Property Services. The same 6 demises with one number changed: U-03 reads 211.50 sq m instead of 230.00. Unit areas now sum to 1181.50 against the 1200.00 that every row still declares as building_area_sq_m, a shortfall of 18.50 sq m. The rent columns are untouched, so U-03 annual rent no longer equals its area times its rate either, and the two failures are the same mutation seen twice.

csv

text/csv

955 B
Document Set
property
Industry
trades-property
Source Kit
trades-property
Entity
Pine Property Services
Synthetic
true
As Of
2026-09-08

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

Specifications

Document Set
property
Industry
trades-property
Source Kit
trades-property
Entity
Pine Property Services
Synthetic
true
As Of
2026-09-08
Rows
6
Mutated Row
4
Mutated Column
area_sq_m
Declared Building Area
1200.00
Actual Area Sum
1181.50
Shortfall
18.50
Secondary Failure
annual_rent no longer equals area times rate on the mutated row

Testing contract

Expected to fail
Scenario
Sum area_sq_m and compare with building_area_sq_m, then check annual rent against area times rate on each row.
Expected result
Areas sum to 1181.50 against a declared 1200.00, a shortfall of 18.50 sq m on row 4 of the file. That same row now prices 211.50 sq m at 240.00, which is 50760.00 and not the 55200.00 its annual_rent column still states.

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

“Pine Property Services: Rent roll whose unit areas do not sum to the building area” is a deterministic Novus Examples fixture for Data import, CSV parsing, Error handling. Realistic faker-generated datasets with documented schemas for testing import and ETL flows.

Documented properties for this file: 6 rows. 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("rent-roll-area-mismatch.csv")
print(df.head())
print(df.dtypes)

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