Xlsx

This is your reference for working with Excel files programmatically, covering both Python libraries (openpyxl for formatting and cell manipulation, pandas for data operations) and JavaScript's xlsx package. You'll reach for this when reading spreadsheets, writing structured data, applying formulas, or converting between Excel and CSV formats. The examples are concise and cover the common patterns you actually need: iterating rows, styling cells, pivoting data, and merging multiple files. It's designed as a quick lookup rather than a tutorial, so you can grab the syntax and get back to work. The pandas examples are especially useful if you're doing any data transformation before writing output.

skills.sh installs: 599
GitHub stars: 79
last updated: Aug 21, 2026

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Install

$ npx -y skills add bobmatnyc/claude-mpm-skills --skill xlsx --agent claude-code

Installs into .claude/skills of the current project.

Files

Excel/XLSX Manipulation

Working with Excel files programmatically.

Python (openpyxl)

Reading Excel

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)

Writing Excel

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')

Formatting

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

Formulas

# Add formula
ws['C2'] = '=A2+B2'

# Sum column
ws['D10'] = '=SUM(D2:D9)'

Python (pandas)

Reading Excel

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)

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