working-with-spreadsheets
Creates and edits Excel spreadsheets with formulas, formatting, and financial modeling standards.Use when working with .xlsx files, financial models, data analysis, or formula-heavy spreadsheets.Covers formula recalculation, color coding standards, and common pitfalls.
When & Why to Use This Skill
This Claude skill automates the creation, editing, and formatting of Excel spreadsheets using professional financial modeling standards. It specializes in generating dynamic .xlsx files with complex formulas, industry-standard color coding (e.g., blue for inputs, black for formulas), and precise number formatting. By leveraging libraries like openpyxl and pandas, it ensures data integrity through formula-based calculations rather than hardcoded values, making it an essential tool for financial analysts and data engineers.
Use Cases
- Automated Financial Modeling: Build professional-grade financial models from scratch with standardized color coding, cross-sheet references, and automated recalculation logic.
- Data-to-Report Transformation: Convert raw data from pandas DataFrames into polished, formatted Excel reports with custom headers, currency symbols, and specific column widths.
- Spreadsheet Auditing and Cleaning: Programmatically scan existing Excel files to identify and fix formula errors such as #REF!, #DIV/0!, or data type mismatches.
- Batch Spreadsheet Modification: Efficiently update multiple existing workbooks by inserting rows, deleting columns, or adding new analysis sheets while preserving existing styles and formulas.
| name | working-with-spreadsheets |
|---|---|
| description | | |
Working with Spreadsheets
Quick Start
from openpyxl import Workbook
wb = Workbook()
sheet = wb.active
sheet['A1'] = 'Revenue'
sheet['B1'] = 1000
sheet['B2'] = '=B1*1.1' # Use formulas, not hardcoded values!
wb.save('output.xlsx')
Critical Rule: Use Formulas, Not Hardcoded Values
Always use Excel formulas instead of calculating in Python.
# WRONG - Hardcoding calculated values
total = df['Sales'].sum()
sheet['B10'] = total # Hardcodes 5000
# CORRECT - Using Excel formulas
sheet['B10'] = '=SUM(B2:B9)'
Financial Model Color Coding Standards
| Color | RGB | Usage |
|---|---|---|
| Blue text | 0,0,255 | Hardcoded inputs, scenario values |
| Black text | 0,0,0 | ALL formulas and calculations |
| Green text | 0,128,0 | Links from other worksheets |
| Red text | 255,0,0 | External links to other files |
| Yellow background | 255,255,0 | Key assumptions needing attention |
from openpyxl.styles import Font
# Input cell (user changeable)
sheet['B5'].font = Font(color='0000FF') # Blue
# Formula cell
sheet['C5'] = '=B5*1.1'
sheet['C5'].font = Font(color='000000') # Black
# Cross-sheet link
sheet['D5'] = "=Sheet2!A1"
sheet['D5'].font = Font(color='008000') # Green
Number Formatting Standards
# Currency with thousands separator
sheet['B5'].number_format = '$#,##0'
# Zeros display as dash
sheet['B5'].number_format = '$#,##0;($#,##0);-'
# Percentages with one decimal
sheet['C5'].number_format = '0.0%'
# Valuation multiples
sheet['D5'].number_format = '0.0x'
# Years as text (not 2,024)
sheet['A1'] = '2024' # String, not number
Library Selection
| Task | Library | Example |
|---|---|---|
| Data analysis | pandas | df = pd.read_excel('file.xlsx') |
| Formulas & formatting | openpyxl | sheet['A1'] = '=SUM(B:B)' |
| Large files (read) | openpyxl | load_workbook('file.xlsx', read_only=True) |
| Large files (write) | openpyxl | Workbook(write_only=True) |
Reading Excel Files
import pandas as pd
from openpyxl import load_workbook
# pandas - data analysis
df = pd.read_excel('file.xlsx')
all_sheets = pd.read_excel('file.xlsx', sheet_name=None) # Dict of DataFrames
# openpyxl - preserve formulas
wb = load_workbook('file.xlsx')
sheet = wb.active
print(sheet['A1'].value) # Returns formula string
# openpyxl - get calculated values (WARNING: loses formulas on save!)
wb = load_workbook('file.xlsx', data_only=True)
Creating Excel Files
from openpyxl import Workbook
from openpyxl.styles import Font, PatternFill, Alignment
wb = Workbook()
sheet = wb.active
sheet.title = 'Model'
# Headers
sheet['A1'] = 'Metric'
sheet['B1'] = '2024'
sheet['A1'].font = Font(bold=True)
# Data with formulas
sheet['A2'] = 'Revenue'
sheet['B2'] = 1000000
sheet['B2'].font = Font(color='0000FF') # Blue = input
sheet['A3'] = 'Growth'
sheet['B3'] = '=B2*0.1'
sheet['B3'].font = Font(color='000000') # Black = formula
# Formatting
sheet['B2'].number_format = '$#,##0'
sheet.column_dimensions['A'].width = 20
wb.save('model.xlsx')
Editing Existing Files
from openpyxl import load_workbook
wb = load_workbook('existing.xlsx')
sheet = wb['Data'] # Or wb.active
# Modify cells
sheet['A1'] = 'Updated Value'
sheet.insert_rows(2)
sheet.delete_cols(3)
# Add new sheet
new_sheet = wb.create_sheet('Analysis')
new_sheet['A1'] = '=Data!B5' # Cross-sheet reference
wb.save('modified.xlsx')
Formula Recalculation
openpyxl writes formulas but doesn't calculate values. Use LibreOffice to recalculate:
# Recalculate and check for errors
python recalc.py output.xlsx
The script returns JSON:
{
"status": "success", // or "errors_found"
"total_errors": 0,
"total_formulas": 42,
"error_summary": {
"#REF!": {"count": 2, "locations": ["Sheet1!B5", "Sheet1!C10"]}
}
}
Formula Verification Checklist
Before Building
- Test 2-3 sample references first
- Confirm column mapping (column 64 = BL, not BK)
- Remember: DataFrame row 5 = Excel row 6 (1-indexed)
Common Pitfalls
- Check for NaN with
pd.notna()before using values - FY data often in columns 50+ (far right)
- Search ALL occurrences, not just first match
- Check denominators before division (#DIV/0!)
- Verify cross-sheet references use correct format (
Sheet1!A1)
After Building
- Run
recalc.pyand fix any errors - Verify #REF!, #DIV/0!, #VALUE!, #NAME? = 0
Common Errors
| Error | Cause | Fix |
|---|---|---|
| #REF! | Invalid cell reference | Check deleted rows/columns |
| #DIV/0! | Division by zero | Add IF check: =IF(B5=0,0,A5/B5) |
| #VALUE! | Wrong data type | Check cell contains expected type |
| #NAME? | Unknown function | Check spelling, quotes around text |
Verification
Run: python scripts/verify.py
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