Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/bobmatnyc/claude-mpm-skills --skill xlsx명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
SKILL.md 표시 중
| name | xlsx |
| description | Working with Excel files programmatically. |
| user-invocable | false |
| disable-model-invocation | true |
| updated_at | "2025-10-30T17:00:00.000Z" |
| tags | ["excel","xlsx","spreadsheet","data"] |
| progressive_disclosure | {"entry_point":{"summary":"Working with Excel files programmatically.","when_to_use":"When working with xlsx or related functionality.","quick_start":"1. Review the core concepts below. 2. Apply patterns to your use case. 3. Follow best practices for implementation."}} |
Working with Excel files programmatically.
from openpyxl import load_workbook
wb = load_workbook('data.xlsx')
ws = wb.active # Get active sheet
# Read cell
value = ws['A1'].value
# Iterate rows
for row in ws.iter_rows(min_row=2, values_only=True):
print(row)
from openpyxl import Workbook
wb = Workbook()
ws = wb.active
ws.title = "Data"
# Write data
ws['A1'] = 'Name'
ws['B1'] = 'Age'
ws.append(['John', 30])
ws.append(['Jane', 25])
wb.save('output.xlsx')
from openpyxl.styles import Font, PatternFill
# Bold header
ws['A1'].font = Font(bold=True)
# Background color
ws['A1'].fill = PatternFill(start_color="FFFF00", fill_type="solid")
# Number format
ws['B2'].number_format = '0.00' # Two decimals
# Add formula
ws['C2'] = '=A2+B2'
# Sum column
ws['D10'] = '=SUM(D2:D9)'
import pandas as pd
# Read sheet
df = pd.read_excel('data.xlsx', sheet_name='Sheet1')
# Read multiple sheets
dfs = pd.read_excel('data.xlsx', sheet_name=None)
# Write DataFrame
df.to_excel('output.xlsx', index=False)
# Multiple sheets
with pd.ExcelWriter('output.xlsx') as writer:
df1.to_excel(writer, sheet_name='Sheet1')
df2.to_excel(writer, sheet_name='Sheet2')
# Filter
filtered = df[df['Age'] > 25]
# Group by
grouped = df.groupby('Department')['Salary'].mean()
# Pivot
pivot = df.pivot_table(values='Sales', index='Region', columns='Product')
import XLSX from 'xlsx';
// Read file
const workbook = XLSX.readFile('data.xlsx');
const sheetName = workbook.SheetNames[0];
const worksheet = workbook.Sheets[sheetName];
// Convert to JSON
const data = XLSX.utils.sheet_to_json(worksheet);
// Write file
const newWorksheet = XLSX.utils.json_to_sheet(data);
const newWorkbook = XLSX.utils.book_new();
XLSX.utils.book_append_sheet(newWorkbook, newWorksheet, 'Data');
XLSX.writeFile(newWorkbook, 'output.xlsx');
import pandas as pd
df = pd.read_csv('data.csv')
df.to_excel('data.xlsx', index=False)
df = pd.read_excel('data.xlsx')
df.to_csv('data.csv', index=False)
dfs = []
for file in ['file1.xlsx', 'file2.xlsx', 'file3.xlsx']:
df = pd.read_excel(file)
dfs.append(df)
combined = pd.concat(dfs, ignore_index=True)
combined.to_excel('merged.xlsx', index=False)
LinkedIn automation via the Linked API CLI - fetch profiles, search people and companies, send messages, manage connections, create posts, react, comment, and run Sales Navigator and custom workflows. Use when the user wants to interact with LinkedIn.
Xquik X data automation API - Use REST or MCP for tweet search, user lookup, follower exports, media downloads, monitors, webhooks, giveaway draws, and confirmation-gated X actions.
MCP (Model Context Protocol) - Build AI-native servers with tools, resources, and prompts. TypeScript/Python SDKs for Claude Desktop integration.
SOC 직업 분류 기준