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Novus Examples
csv244 B

Willow Community Fund: Fair market value of donor benefits

Fair market value of donor benefits for Willow Community Fund. The 2 goods and services supporters received in return for a gift, with the fair market value used to reduce the deductible amount on their receipt: Workshop lunch at 18.00 on 6 receipts and Garden tote bag at 7.50 on 3. No de minimis exception is applied: every benefit is deducted, however small.

csv

text/csv

244 B
Document Set
nonprofit
Industry
nonprofit
Source Kit
nonprofit-fundraising
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
nonprofit
Industry
nonprofit
Source Kit
nonprofit-fundraising
Synthetic
true
As Of
2026-09-08
Rows
2
Total Benefit Usd
130.50
De Minimis Applied
false
Encoding
UTF-8

Testing contract

Reference control
Scenario
Recompute the benefit value on every receipt from this schedule.
Expected result
Applying the schedule to donation-receipts.csv reproduces the benefit_value column exactly on all 9 receipts and totals 130.50: 6 lunches and 3 tote bags.

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

“Willow Community Fund: Fair market value of donor benefits” 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("benefit-value-schedule.csv")
print(df.head())
print(df.dtypes)

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