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csv477 B

Fieldnote Supply Shop: Sales tax payable control account

Sales tax payable control account for Fieldnote Supply Shop. The ledger account behind the filing: opening 0.00, credited 96.34 of tax collected, debited 7.46 of tax refunded, leaving 88.88 USD payable at the end of the period. The 0.13 vendor allowance and the 88.75 remittance then clear it to exactly 0.00 on 2026-09-20. The balance after row 3 is the same number the filing worksheet reaches by summing six jurisdictions.

csv

text/csv

477 B
Document Set
tax
Industry
retail
Source Kit
retail-commerce
Entity
Fieldnote Supply Shop
Synthetic
true
As Of
2026-09-08

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

Specifications

Document Set
tax
Industry
retail
Source Kit
retail-commerce
Entity
Fieldnote Supply Shop
Synthetic
true
As Of
2026-09-08
Rows
5
Period Balance
88.88
Closing Balance
0.00
Remittance
88.75

Testing contract

Expected to pass
Scenario
Run the running balance down the account and check the closing figure and the balance at the end of the tax period.
Expected result
The balance after the period entries is 88.88, which is the sum of net_tax_due in sales-tax-filing-worksheet.csv, and the closing balance after the remittance and the allowance is exactly 0.00.

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 Supply Shop: Sales tax payable control account” is a deterministic Novus Examples fixture for Data import, CSV parsing. Realistic faker-generated datasets with documented schemas for testing import and ETL flows.

Documented properties for this file: 5 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("sales-tax-payable-control-account.csv")
print(df.head())
print(df.dtypes)

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