---

name: xlsx description: "Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas"

XLSX Spreadsheet Processing

Requirements for Outputs

All Excel Files

• Zero Formula Errors: Every file must have ZERO formula errors (#REF!, #DIV/0!, etc.)
• Preserve Existing Templates: Match existing format when modifying files

Financial Models

Color Coding:

• Blue text: Hardcoded inputs
• Black text: Formulas and calculations
• Green text: Links from other worksheets
• Red text: External file links
• Yellow background: Key assumptions

Number Formatting:

• Years: Text strings ("2024" not "2,024")
• Currency: $#,##0 with units in headers
• Zeros: Format as "-"
• Percentages: 0.0% format
• Negatives: Use parentheses (123)

Reading and Analyzing

Copyimport pandas as pd

# Read Excel
df = pd.read_excel('file.xlsx')
all_sheets = pd.read_excel('file.xlsx', sheet_name=None)

# Analyze
df.head()
df.info()
df.describe()

Creating/Editing with openpyxl

Copyfrom openpyxl import Workbook, load_workbook

# Create new
wb = Workbook()
sheet = wb.active
sheet['A1'] = 'Hello'
sheet['B2'] = '=SUM(A1:A10)'  # Use formulas!
wb.save('output.xlsx')

# Edit existing
wb = load_workbook('existing.xlsx')
sheet = wb.active
sheet['A1'] = 'New Value'
wb.save('modified.xlsx')

CRITICAL: Use Formulas

Wrong: Calculate in Python, hardcode result

Copytotal = df['Sales'].sum()
sheet['B10'] = total  # BAD!

Correct: Use Excel formulas

Copysheet['B10'] = '=SUM(B2:B9)'  # GOOD!

Recalculating Formulas

Copypython recalc.py <excel_file> [timeout_seconds]

The script:

• Sets up LibreOffice macro on first run
• Recalculates all formulas
• Scans for errors
• Returns JSON with error details

Library Selection

• pandas: Data analysis, bulk operations, simple export
• openpyxl: Complex formatting, formulas, Excel features