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csv712 B

Willow Community Fund: Grant budget against actual

Grant budget against actual for Willow Community Fund. 10 rows: four budget lines and a Grant total for each of the 2 awarded grants. Each grant's budget lines sum to the amount awarded, 2000.00 and 2500.00, and actual spend of 4395.25 leaves 104.75 unspent. Two lines are overspent and carry a negative variance; the grant totals are still positive, which is how an overspend hides inside a grant that looks fine.

csv

text/csv

712 B
Document Set
nonprofit
Industry
nonprofit
Source Kit
nonprofit-fundraising
Synthetic
true
As Of
2026-09-08
Rows
10

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
10
Grants
2
Budget Usd
4500.00
Actual Usd
4395.25
Unspent Usd
104.75
Encoding
UTF-8

Testing contract

Expected to pass
Scenario
Import the report, check every line and roll each grant up to its award.
Expected result
variance equals budget minus actual on all 10 rows and the percentage columns follow from them. Each Grant total row equals the sum of its four budget lines and its budget equals the awarded amount on grant-register.csv. The two negative variances are Equipment hire and Facilitator fees, overspent by 46.75 and 40.00 while both grants remain underspent overall.

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: Grant budget against actual” 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: 10 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("grant-budget-vs-actual.csv")
print(df.head())
print(df.dtypes)

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