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Novus Examples
csv936 B

Fieldnote Supply Shop: Refund export that refunds more than was captured

Refund export that refunds more than was captured for Fieldnote Supply Shop. The four valid refunds from refunds.csv plus three rows against order ORD-005, whose captured amount is 78.00. Those three rows refund 36.00, 42.00 and a further 18.00 of merchandise, a total of 96.00, which exceeds the capture by 18.00. RFND-007 also refunds LINE-009 a second time after RFND-005 already returned both units.

csv

text/csv

936 B
Document Set
ecommerce
Industry
retail
Source Kit
retail-commerce
Synthetic
true
As Of
2026-09-08
Rows
7

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

Specifications

Document Set
ecommerce
Industry
retail
Source Kit
retail-commerce
Synthetic
true
As Of
2026-09-08
Rows
7
Offending Rows
3
Captured For Order
78.00
Refunded For Order
96.00
Excess
18.00
Intentionally Invalid
true

Testing contract

Expected to fail
Scenario
Import the refunds and check each refund against the captured amount and the already-refunded quantity of the line it names.
Expected result
A correct importer rejects RFND-007: merchandise refunded against ORD-005 reaches 96.00 against a 78.00 capture, an excess of 18.00, and LINE-009 has already had both of its 2 units refunded by RFND-005. An importer with no cumulative check accepts all seven rows and reports a negative net payout for the order.

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 Supply Shop: Refund export that refunds more than was captured” is a deterministic Novus Examples fixture for Data import, Error handling. Realistic faker-generated datasets with documented schemas for testing import and ETL flows.

Documented properties for this file: 7 rows. 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("refunds-exceed-capture.csv")
print(df.head())
print(df.dtypes)

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