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Novus Examples
csv342 B

Pine Property Services: Approved change order register

Approved change order register for Pine Property Services. 2 approved change orders: an addition of 420.00 for extra door hardware and a credit of -165.00 for deleted lighting scope, a net 255.00. The running contract sum moves from 3858.00 to 4113.00, which is line 3 of the payment application. A credit change order is a negative amount, not a separate document type.

csv

text/csv

342 B
Document Set
construction
Industry
trades-property
Source Kit
trades-property
Synthetic
true
As Of
2026-09-08
Rows
2

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

Specifications

Document Set
construction
Industry
trades-property
Source Kit
trades-property
Synthetic
true
As Of
2026-09-08
Rows
2
Net Change Usd
255.00
Contract Sum To Date Usd
4113.00
Encoding
UTF-8

Testing contract

Expected to pass
Scenario
Replay the register over the original contract sum and compare with the payment application.
Expected result
Starting at 3858.00 and applying the two amounts in date order gives 4113.00, exactly line 3 of application-for-payment-002-summary.csv, and both change orders appear as their own lines on the continuation sheet with retainage of 42.00 and -16.50 against them.

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: Approved change order register” 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: 2 rows · 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("change-orders.csv")
print(df.head())
print(df.dtypes)

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