Budget Template (ODS, with formulas)
A budget template as OpenDocument Spreadsheet — budget-versus-actual rows with live SUM formulas for the totals. A usable planning template and a fixture for testing ODS formula parsing and recalculation.

Rendered preview of the ods file (1.9 KB). Download above for the original.
Specifications
- Format
- OpenDocument Spreadsheet (ODS)
- Type
- budget
- Formulas
- SUM totals
- Editable
- true
What is a .ods file?
ODS is the OpenDocument Spreadsheet format, an ISO-standardized spreadsheet stored as a ZIP archive of XML. It is the native spreadsheet format of LibreOffice and OpenOffice Calc, supporting multiple sheets, formulas, and formatting. It is the open-standard counterpart to XLSX.
How to use this file
Use an example ODS to test OpenDocument spreadsheet parsing, formula and multi-sheet handling, and converters between ODS and XLSX or CSV.
How to use this file for testing
“Budget Template (ODS, with formulas)” is a deterministic Novus Examples fixture for Templates, Spreadsheet testing, Conversion testing. Professional, neutral starting-point documents you can download and adapt — invoices, resumes, budgets, and more.
Documented properties for this file: OpenDocument Spreadsheet (ODS) · budget. 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.
This template ships filled with realistic sample content and documented fields and formulas. Download it as a starting point, or point a converter/parser at it — format twins (for example DOCX↔PDF) let you diff conversion fidelity.
Code examples
import pandas as pd # pip install odfpy
df = pd.read_excel("budget.ods", engine="odf")
print(df.head())Related files
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