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Novus Examples
csv244 B

Willow Community Fund: Fund balance roll-forward by restriction class

Fund balance roll-forward by restriction class for Willow Community Fund. The same money as restricted-funds-report.csv collapsed to two restriction classes and a TOTAL row. Nothing was released from restriction in the period, so the unrestricted class does not move: it opens and closes at 1200.00. The restricted class opens at 0.00, receives 6300.00, spends 4395.25 and closes at 1904.75.

csv

text/csv

244 B
Document Set
nonprofit
Industry
nonprofit
Source Kit
nonprofit-fundraising
Synthetic
true
As Of
2026-09-08
Rows
3

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
3
Closing Usd
3104.75
Encoding
UTF-8

Testing contract

Expected to pass
Scenario
Collapse the fund report by restriction class and compare with this roll-forward.
Expected result
Both classes satisfy opening + donations + grants - expenditure = closing, and the TOTAL row equals the TOTAL row of restricted-funds-report.csv: 3104.75 closing. The unrestricted row is flat because no restricted funds were released; a roll-forward that moves spend out of the unrestricted class instead would show the same total and the wrong classes.

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: Fund balance roll-forward by restriction class” 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: 3 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("fund-balance-rollforward.csv")
print(df.head())
print(df.dtypes)

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