Pine Assembly Workshop: Loan amortisation workbook
Loan amortisation workbook for Pine Assembly Workshop. A two-sheet workbook: the 36 schedule rows and a summary sheet holding the inputs and the four control totals. The monthly rate is written to eight decimal places as 0.00575000 so the level payment can be reproduced; at the four places a spreadsheet usually shows, the recomputed payment differs.
Rendered preview of the xlsx file (7.7 KB). Download above for the original.
Specifications
- Document Set
- banking
- Industry
- finance
- Source Kit
- accounting-reconciliation
- Entity
- Pine Assembly Workshop
- Synthetic
- true
- As Of
- 2026-09-08
- Sheets
- 2
- Rows
- 36
- Monthly Rate Decimal Places
- 8
- Closing Balance
- 0.00
Testing contract
Expected to pass- Scenario
- Rebuild the schedule in the workbook from the summary inputs and compare it with the Schedule sheet.
- Expected result
- The rebuild reproduces all 36 rows and the 0.00 closing balance when the monthly rate is taken at eight decimal places. Rounding the rate to four places moves the level payment and the schedule drifts within a few months.
What is a .xlsx file?
XLSX is the default Microsoft Excel format, an Office Open XML spreadsheet stored as a ZIP archive containing worksheet XML, shared strings, styles, and formulas. It supports multiple sheets, cell formatting, charts, and calculated values. It is the standard for editable tabular workbooks.
How to use this file
Use an example XLSX to test spreadsheet parsing, formula and multi-sheet handling, shared-string extraction, and pipelines that read or generate Excel workbooks.
How to use this file for testing
“Pine Assembly Workshop: Loan amortisation workbook” 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: 36 rows · 2 sheets. 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.
Document fixtures list their internal structure (pages, fields, tracked changes, embedded objects) in the spec table. Test extractors, converters, and OCR against that known structure, and compare searchable↔scanned or format-twin companions when present.
Code examples
from openpyxl import load_workbook
wb = load_workbook("loan-amortisation-schedule.xlsx")
ws = wb.active
print(ws.title, ws.max_row, ws.max_column)Related files
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