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xlsx5.8 KB

Cobalt Operations Team: Payroll register workbook

Payroll register workbook for Cobalt Operations Team. One worksheet with the 8 employee rows and the TOTAL row, the same values as payroll-register.csv. Amounts are stored as text with two decimals, so a net pay ending in a zero cent is not displayed short and cannot be silently re-rounded by a recalculation.

Rendered preview of Cobalt Operations Team: Payroll register workbook

Rendered preview of the xlsx file (5.8 KB). Download above for the original.

Specifications

Document Set
payroll
Industry
people-operations
Source Kit
people-operations
Synthetic
true
As Of
2026-09-08
Sheets
1
Rows
9
Columns
14

Testing contract

Expected to pass
Scenario
Open the workbook and reconcile it against payroll-register.csv.
Expected result
The sheet has 10 rows and 14 columns and matches the CSV cell for cell, with net_pay totalling 6649.44 on the TOTAL row.

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

“Cobalt Operations Team: Payroll register 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: 9 rows · 14 columns · 1 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("payroll-register.xlsx")
ws = wb.active
print(ws.title, ws.max_row, ws.max_column)

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