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Novus Examples
csv310 B

Pine Property Services: Retainage ledger

Retainage ledger for Pine Property Services. Two payment applications. Application 001 certified 1341.00 and retained 149.00; application 002 adds 1758.00 of completed and stored value, retains a further 175.80 and certifies 1582.20. Cumulative retainage reaches 324.80, which is 10 percent of the 3248.00 completed and stored to date.

csv

text/csv

310 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
Cumulative Retainage Usd
324.80
Certified Total Usd
2923.20
Encoding
UTF-8

Testing contract

Expected to pass
Scenario
Replay both applications and check the cumulative columns and the certified amounts.
Expected result
cumulative_completed_and_stored reaches 3248.00 and cumulative retainage 324.80, exactly ten percent of it and exactly lines 4 and 5 of application-for-payment-002-summary.csv. The two certified_for_payment figures sum to 2923.20, which is line 6 of the same summary.

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: Retainage ledger” 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("retainage-ledger.csv")
print(df.head())
print(df.dtypes)

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