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
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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
license
Proprietary. LICENSE.txt has complete terms
Excel电子表格处理专家 Real Skill
一句话说明
专业的 Excel 处理工具，强制零公式错误标准，支持数据分析、报表生成和财务建模。
Excel Spreadsheet Mastery - Zero-error formula standard, data analysis, automated reporting, financial modeling with color coding.
使用场景
适用：
数据分析和统计报告
自动化生成 Excel 报表
财务预测模型（色彩编码）
批量处理多个 Excel 文件
数据清洗和格式转换
不适用：
实时协同编辑（用 Google Sheets / use Google Sheets for real-time collaboration）
Formula recalculation script (requires LibreOffice)
关键原则（AI 必读 / Critical Principles）
1. ⚠️ Zero Formula Errors (零公式错误原则 - MANDATORY)
Every Excel file MUST be delivered with ZERO formula errors:
No #REF! (invalid references)
No #DIV/0! (division by zero)
No #VALUE! (wrong data type)
No #N/A (lookup not found)
No #NAME? (unrecognized formula name)
Verification workflow:
python scripts/recalc.py output.xlsx
# Check JSON output: status should be "success"# If "errors_found", fix and recalculate
2. Use Formulas, Not Hardcoded Values (使用公式而非硬编码)
CRITICAL: Always use Excel formulas instead of calculating in Python.
❌ WRONG - Hardcoding:
total = df['Sales'].sum()
sheet['B10'] = total # Hardcodes 5000
✅ CORRECT - Using Formulas:
sheet['B10'] = '=SUM(B2:B9)'# Dynamic formula
Why: Spreadsheet remains dynamic and updateable when source data changes.
3. Financial Modeling Color Coding (财务建模色彩编码)
Industry-standard color conventions (unless user specifies otherwise):
from openpyxl.styles import Font
# Blue text (0000FF): User inputs and assumptions
ws['A1'].font = Font(color='0000FF')
# Black text (000000): ALL formulas and calculations
ws['B1'].font = Font(color='000000')
# Green text (008000): Links within same workbook
ws['C1'].font = Font(color='008000')
# Red text (FF0000): External file links
ws['D1'].font = Font(color='FF0000')
# Yellow background (FFFF00): Key assumptionsfrom openpyxl.styles import PatternFill
ws['E1'].fill = PatternFill(start_color='FFFF00', fill_type='solid')
4. Number Formatting Standards (数字格式标准)
from openpyxl.styles import numbers
# Years: Format as text strings "2024" (not numbers)
ws['A1'].number_format = '@'# Text format
ws['A1'] = "'2024"# Force text# Currency: $#,##0 + specify units in header
ws['B1'].number_format = '$#,##0'# Zeros: Format as "-"
ws['C1'].number_format = '$#,##0;($#,##0);"-"'# Percentages: 0.0% (one decimal)
ws['D1'].number_format = '0.0%'# Multiples: 0.0x for valuation multiples
ws['E1'].number_format = '0.0"x"'# Negative numbers: Use parentheses (123) not minus -123
ws['F1'].number_format = '#,##0;(#,##0)'
5. Preserve Existing Templates (保留现有模板)
When modifying existing files:
Study and EXACTLY match existing format, style, conventions
Never impose standardized formatting on files with established patterns
Existing template conventions ALWAYS override these guidelines
快速命令参考 (Quick Commands)
Data Analysis with Pandas (数据分析)
import pandas as pd
# Read Excel (single sheet or all)
df = pd.read_excel('file.xlsx') # 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
df.groupby('Category')['Sales'].sum() # Group by# Write Excel
df.to_excel('output.xlsx', index=False)
Create Excel with Formulas (创建带公式的 Excel)
from openpyxl import Workbook
from openpyxl.styles import Font
wb = Workbook()
ws = wb.active
# Data with formulas
ws['A1'] = 'Revenue'
ws['A2'] = 1000
ws['A3'] = 1200
ws['A4'] = 'Total'
ws['B4'] = '=SUM(A2:A3)'# Use formula, not hardcoded value# Color coding
ws['A2'].font = Font(color='0000FF') # Blue: User input
ws['B4'].font = Font(color='000000') # Black: Formula
wb.save('output.xlsx')
Recalculate Formulas (公式重算 - MANDATORY)
# After saving file with formulas
python scripts/recalc.py output.xlsx
# Output JSON shows:# - status: "success" or "errors_found"# - error_summary: Details of any errors# - total_errors: Count of formula errors
Financial Model with Color Coding (财务建模)
from openpyxl import Workbook
from openpyxl.styles import Font, PatternFill
wb = Workbook()
ws = wb.active
# Headers
ws['A1'] = 'Year'
ws['B1'] = 'Revenue ($mm)'
ws['C1'] = 'Growth %'# Data with color coding
ws['A2'] = "'2024"# Force text for year
ws['B2'] = 100
ws['B2'].font = Font(color='0000FF') # Blue: User input
ws['C2'] = 0.15# Growth assumption
ws['C2'].font = Font(color='0000FF')
ws['C2'].fill = PatternFill(start_color='FFFF00', fill_type='solid') # Yellow: Key assumption
ws['C2'].number_format = '0.0%'# Formulas
ws['B3'] = '=B2*(1+C2)'# Revenue calculation
ws['B3'].font = Font(color='000000') # Black: Formula
wb.save('financial_model.xlsx')
# MUST recalculateimport subprocess
subprocess.run(['python', 'scripts/recalc.py', 'financial_model.xlsx'])
Error Handling (错误处理)
import subprocess
import json
# Run recalc and check results
result = subprocess.run(
['python', 'scripts/recalc.py', 'output.xlsx'],
capture_output=True,
text=True
)
data = json.loads(result.stdout)
if data['status'] == 'errors_found':
print(f"Found {data['total_errors']} errors:")
for error_type, count in data['error_summary'].items():
print(f" {error_type}: {count}")
# Fix errors and recalculateelse:
print("✅ Zero formula errors - file ready!")
