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xlsx

Create, edit, and recalculate Excel spreadsheets with formulas using openpyxl and pandas.

Updated May 23, 2026
Search Tags:#financial modeling#pandas#openpyxl#spreadsheet#excel#xlsx#formula recalculation
One-click install
npx skills add https://github.com/kiranimmadi2/promptforge-ai --skill xlsx-kiranimmadi2
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: xlsx
Source: https://github.com/kiranimmadi2/promptforge-ai/tree/main/anthropic-skills/skills/xlsx
Command: npx skills add https://github.com/kiranimmadi2/promptforge-ai --skill xlsx-kiranimmadi2

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires openpyxl, pandas, defusedxml, lxml, and includes scripts (resource) components.

What problem does it solve? Working with spreadsheet files programmatically often produces broken formulas, hardcoded values, and inconsistent formatting. This Skill provides a complete workflow for creating, editing, and analyzing .xlsx, .xlsm, .csv, and .tsv files while guaranteeing zero formula errors and professional financial-model formatting standards. ## Core Features & Use Cases - Formula-first spreadsheet generation: Builds Excel files with live formulas (SUM, AVERAGE, growth rates) instead of hardcoded Python-computed values, keeping workbooks dynamic and updateable. - Automated recalculation and error detection: The scripts/recalc.py tool uses LibreOffice to recalculate all formulas and reports #REF!, #DIV/0!, #VALUE!, #NAME?, and other errors with exact cell locations. - Financial modeling conventions: Enforces industry-standard color coding (blue inputs, black formulas, green cross-sheet links), number formatting (parenthesized negatives, 0.0% percentages, 0.0x multiples), and source documentation for hardcoded values. - Use Case: A user asks to build a revenue projection model from a messy CSV export. The Skill cleans the data with pandas, constructs the model in openpyxl with assumption cells and formulas, recalculates via LibreOffice, and fixes any reported errors before delivery. ## Quick Start Use the xlsx skill to create a financial model spreadsheet from my sales data CSV with formulas for totals and growth rates, then verify it has no formula errors.

Frequently Asked Questions about xlsx

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I create an Excel file with formulas in Python?▼

Use openpyxl to write formula strings like '=SUM(B2:B9)' directly into cells, then save the workbook. Formulas are stored but not evaluated, so run the recalc.py script with LibreOffice to compute values and verify no errors exist.

Should I use pandas or openpyxl for Excel files?▼

Use pandas for data analysis, bulk operations, and simple exports via read_excel and to_excel. Use openpyxl when you need formulas, cell formatting, multiple sheets, or edits to existing workbooks while preserving their structure.

Why do my openpyxl formulas show no calculated values?▼

openpyxl stores formulas as strings without evaluating them. Recalculate with LibreOffice using the recalc.py script, which computes all formulas and scans every cell for errors like #REF! and #DIV/0!.

How do I fix #REF! and #DIV/0! errors in generated spreadsheets?▼

Run recalc.py to get a JSON report listing each error type with cell locations. Fix invalid cell references for #REF! errors and guard denominators against zero for #DIV/0! errors, then recalculate again to confirm.

Can openpyxl read calculated values from an Excel file?▼

Yes, load the workbook with data_only=True to read cached calculated values. However, never save a workbook opened this way, because formulas will be permanently replaced with their static values.

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