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working-with-spreadsheets

working-with-spreadsheets

github.com/mjunaidcaDocuments28154 installsUpdated 11w ago
Repository

About working-with-spreadsheets

working-with-spreadsheets is a skill for handling Excel workbooks with Python libraries, for people creating, analyzing, or maintaining spreadsheets. It emphasizes formula-based calculations, financial-model formatting, and formula error checks.

Key features

  1. 01Analyze Excel data with pandas
  2. 02Create and edit workbooks with openpyxl
  3. 03Apply financial model colors and number formats
  4. 04Recalculate and check formula errors
  5. 05Troubleshoot common formula issues

Use cases

  1. 01Build financial models with formulas
  2. 02Analyze data across workbook sheets
  3. 03Edit existing workbooks while preserving formulas
  4. 04Check formula references and calculation errors

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/mjunaidca/mjs-agent-skills --skill working-with-spreadsheets

After installing, type/working-with-spreadsheetsin Claude Code to confirm it loaded.

Bundled filesscripts/verify.py

Details

From the project README

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

ColorRGBUsage
Blue text0,0,255Hardcoded inputs, scenario values
Black text0,0,0ALL formulas and calculations
Green text0,128,0Links from other worksheets
Red text255,0,0External links to other files
Yellow background255,255,0Key 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

TaskLibraryExample
Data analysispandasdf = pd.read_excel('file.xlsx')
Formulas & formattingopenpyxlsheet['A1'] = '=SUM(B:B)'
Large files (read)openpyxlload_workbook('file.xlsx', read_only=True)
Large files (write)openpyxlWorkbook(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.py and fix any errors
  • Verify #REF!, #DIV/0!, #VALUE!, #NAME? = 0

Common Errors

ErrorCauseFix
#REF!Invalid cell referenceCheck deleted rows/columns
#DIV/0!Division by zeroAdd IF check: =IF(B5=0,0,A5/B5)
#VALUE!Wrong data typeCheck cell contains expected type
#NAME?Unknown functionCheck spelling, quotes around text

Verification

Run: python scripts/verify.py

Related Skills

  • building-nextjs-apps - Frontend for spreadsheet uploads
  • scaffolding-fastapi-dapr - API for spreadsheet processing

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