/xlsx-official

name: xlsx-official
description: "Unless otherwise stated by the user or existing template"
risk: unknown
source: community
date_added: "2026-02-27"

Requirements for Outputs

All Excel files

Zero Formula Errors

• Every Excel model MUST be delivered with ZERO formula errors (#REF!, #DIV/0!, #VALUE!, #N/A, #NAME?)

Preserve Existing Templates (when updating templates)

• Study and EXACTLY match existing format, style, and conventions when modifying files
• Never impose standardized formatting on files with established patterns
• Existing template conventions ALWAYS override these guidelines

Financial models

Color Coding Standards

Unless otherwise stated by the user or existing template

Industry-Standard Color Conventions

• **Blue text (RGB: 0,0,255)**: Hardcoded inputs, and numbers users will change for scenarios
• **Black text (RGB: 0,0,0)**: ALL formulas and calculations
• **Green text (RGB: 0,128,0)**: Links pulling from other worksheets within same workbook
• **Red text (RGB: 255,0,0)**: External links to other files
• **Yellow background (RGB: 255,255,0)**: Key assumptions needing attention or cells that need to be updated

Number Formatting Standards

Required Format Rules

• **Years**: Format as text strings (e.g., "2024" not "2,024")
• **Currency**: Use $#,##0 format; ALWAYS specify units in headers ("Revenue ($mm)")
• **Zeros**: Use number formatting to make all zeros "-", including percentages (e.g., "$#,##0;($#,##0);-")
• **Percentages**: Default to 0.0% format (one decimal)
• **Multiples**: Format as 0.0x for valuation multiples (EV/EBITDA, P/E)
• **Negative numbers**: Use parentheses (123) not minus -123

Formula Construction Rules

Assumptions Placement

• Place ALL assumptions (growth rates, margins, multiples, etc.) in separate assumption cells
• Use cell references instead of hardcoded values in formulas
• Example: Use =B5*(1+$B$6) instead of =B5*1.05

Formula Error Prevention

• Verify all cell references are correct
• Check for off-by-one errors in ranges
• Ensure consistent formulas across all projection periods
• Test with edge cases (zero values, negative numbers)
• Verify no unintended circular references

Documentation Requirements for Hardcodes

• Comment or in cells beside (if end of table). Format: "Source: [System/Document], [Date], [Specific Reference], [URL if applicable]"
• Examples:
• "Source: Company 10-K, FY2024, Page 45, Revenue Note, [SEC EDGAR URL]"
• "Source: Company 10-Q, Q2 2025, Exhibit 99.1, [SEC EDGAR URL]"
• "Source: Bloomberg Terminal, 8/15/2025, AAPL US Equity"
• "Source: FactSet, 8/20/2025, Consensus Estimates Screen"

XLSX creation, editing, and analysis

Overview

A user may ask you to create, edit, or analyze the contents of an .xlsx file. You have different tools and workflows available for different tasks.

Important Requirements

**LibreOffice Required for Formula Recalculation**: You can assume LibreOffice is installed for recalculating formula values using the `recalc.py` script. The script automatically configures LibreOffice on first run

Reading and analyzing data

Data analysis with pandas

For data analysis, visualization, and basic operations, use **pandas** which provides powerful data manipulation capabilities:

import pandas as pd

# Read Excel
df = pd.read_excel('file.xlsx')  # Default: first sheet
all_sheets = pd.read_excel('file.xlsx', sheet_name=None)  # All sheets as dict

# Analyze
df.head()      # Preview data
df.info()      # Column info
df.describe()  # Statistics

# Write Excel
df.to_excel('output.xlsx', index=False)

Excel File Workflows

CRITICAL: Use Formulas, Not Hardcoded Values

**Always use Excel formulas instead of calculating values in Python and hardcoding them.** This ensures the spreadsheet remains dynamic and updateable.

❌ WRONG - Hardcoding Calculated Values

# Bad: Calculating in Python and hardcoding result
total = df['Sales'].sum()
sheet['B10'] = total  # Hardcodes 5000

# Bad: Computing growth rate in Python
growth = (df.iloc[-1]['Revenue'] - df.iloc[0]['Revenue']) / df.iloc[0]['Revenue']
sheet['C5'] = growth  # Hardcodes 0.15

# Bad: Python calculation for average
avg = sum(values) / len(values)
sheet['D20'] = avg  # Hardcodes 42.5

✅ CORRECT - Using Excel Formulas

# Good: Let Excel calculate the sum
sheet['B10'] = '=SUM(B2:B9)'

# Good: Growth rate as Excel formula
sheet['C5'] = '=(C4-C2)/C2'

# Good: Average using Excel function
sheet['D20'] = '=AVERAGE(D2:D19)'

This applies to ALL calculations - totals, percentages, ratios, differences, etc. The spreadsheet should be able to recalculate when source data changes.

Common Workflow

1. **Choose tool**: pandas for data, openpyxl for formulas/formatting 2. **Create/Load**: Create new workbook or load existing file 3. **Modify**: Add/edit data, formulas, and formatting 4. **Save**: Write to file 5. **Recalculate formulas (MANDATORY IF USING FORMULAS)**: Use the recalc.py script

   python recalc.py output.xlsx

6. **Verify and fix any errors**:

• The script returns JSON with error details
• If `status` is `errors_found`, check `error_summary` for specific error types and locations
• Fix the identified errors and recalculate again
• Common errors to fix:
• `#REF!`: Invalid cell references
• `#DIV/0!`: Division by zero
• `#VALUE!`: Wrong data type in formula
• `#NAME?`: Unrecognized formula name

Creating new Excel files

# Using openpyxl for formulas and formatting
from openpyxl import Workbook
from openpyxl.styles import Font, PatternFill, Alignment

wb = Workbook()
sheet = wb.active

# Add data
sheet['A1'] = 'Hello'
sheet['B1'] = 'World'
sheet.append(['Row', 'of', 'data'])

# Add formula
sheet['B2'] = '=SUM(A1:A10)'

# Formatting
sheet['A1'].font = Font(bold=True, color='FF0000')
sheet['A1'].fill = PatternFill('solid', start_color='FFFF00')
sheet['A