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Fieldnote Learning Centre: Invoice register with bursaries

Invoice register with bursaries for Fieldnote Learning Centre. 18 invoices, one per enrolment. tuition plus materials_fee plus registration_fee equals gross_fee, and gross_fee less bursary_amount equals net_payable, on every row. Gross totals 5250.00, bursaries 807.50 and net payable 4442.50. One invoice is reduced to 0.00 by a full bursary and no invoice is negative. payment_plan is true on the 8 invoices whose net exceeds 250.00.

csv

text/csv

2.4 KB
Document Set
education
Industry
education
Source Kit
education-training
Synthetic
true
As Of
2026-09-08
Rows
18

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

Specifications

Document Set
education
Industry
education
Source Kit
education-training
Synthetic
true
As Of
2026-09-08
Rows
18
Gross Usd
5250.00
Bursary Usd
807.50
Net Usd
4442.50
Zero Net Invoices
1
Encoding
UTF-8

Testing contract

Expected to pass
Scenario
Import the register, recompute both identities and check the bursary against the award register.
Expected result
All 18 rows satisfy both identities to the cent. Gross sums to 5250.00, bursary to 807.50 and net to 4442.50. Every non-zero bursary_amount names an award_id that resolves in bursary-register.csv, and the 8 rows flagged for a payment plan are exactly those with net_payable above 250.00.

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

“Fieldnote Learning Centre: Invoice register with bursaries” 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: 18 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("invoice-register.csv")
print(df.head())
print(df.dtypes)

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