Excel Automation Skill

Overview

This skill enables advanced Excel automation using xlwings - a library that can interact with live Excel instances. Unlike openpyxl (file-only), xlwings can control Excel in real-time, execute VBA, update dashboards, and automate complex workflows.

How to Use

1. Describe the Excel automation task you need
2. Specify if you need live Excel interaction or file processing
3. I'll generate xlwings code and execute it

Example prompts:

• "Update this live Excel dashboard with new data"
• "Run this VBA macro and get the results"
• "Create an Excel add-in for data validation"
• "Automate monthly report generation with live charts"

Domain Knowledge

xlwings vs openpyxl

xlwings Fundamentals

import xlwings as xw

# Connect to active Excel workbook
wb = xw.Book.caller()  # From Excel add-in
wb = xw.books.active   # Active workbook

# Open specific file
wb = xw.Book('path/to/file.xlsx')

# Create new workbook
wb = xw.Book()

# Get sheet
sheet = wb.sheets['Sheet1']
sheet = wb.sheets[0]

Working with Ranges

Reading and Writing

# Single cell
sheet['A1'].value = 'Hello'
value = sheet['A1'].value

# Range
sheet['A1:C3'].value = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
data = sheet['A1:C3'].value  # Returns list of lists

# Named range
sheet['MyRange'].value = 'Named data'

# Expand range (detect data boundaries)
sheet['A1'].expand().value  # All connected data
sheet['A1'].expand('table').value  # Table format

Dynamic Ranges

# Current region (like Ctrl+Shift+End)
data = sheet['A1'].current_region.value

# Used range
used = sheet.used_range.value

# Last row with data
last_row = sheet['A1'].end('down').row

# Resize range
rng = sheet['A1'].resize(10, 5)  # 10 rows, 5 columns

Formatting

# Font
sheet['A1'].font.bold = True
sheet['A1'].font.size = 14
sheet['A1'].font.color = (255, 0, 0)  # RGB red

# Fill
sheet['A1'].color = (255, 255, 0)  # Yellow background

# Number format
sheet['B1'].number_format = '$#,##0.00'

# Column width
sheet['A:A'].column_width = 20

# Row height
sheet['1:1'].row_height = 30

# Autofit
sheet['A:D'].autofit()

Excel Features

Charts

# Add chart
chart = sheet.charts.add(left=100, top=100, width=400, height=250)
chart.set_source_data(sheet['A1:B10'])
chart.chart_type = 'column_clustered'
chart.name = 'Sales Chart'

# Modify existing chart
chart = sheet.charts['Sales Chart']
chart.chart_type = 'line'

Tables

# Create Excel Table
rng = sheet['A1'].expand()
table = sheet.tables.add(source=rng, name='SalesTable')

# Refresh table
table.refresh()

# Access table data
table_data = table.data_body_range.value

Pictures

# Add picture
sheet.pictures.add('logo.png', left=10, top=10, width=100, height=50)

# Update picture from matplotlib
import matplotlib.pyplot as plt
fig, ax = plt.subplots()
ax.plot([1, 2, 3], [1, 4, 9])
sheet.pictures.add(fig, name='MyPlot', update=True)

VBA Integration

# Run VBA macro
wb.macro('MacroName')()

# With arguments
wb.macro('MyMacro')('arg1', 'arg2')

# Get return value
result = wb.macro('CalculateTotal')(100, 200)

# Access VBA module
vb_code = wb.api.VBProject.VBComponents('Module1').CodeModule.Lines(1, 10)

User Defined Functions (UDFs)

# Define a UDF (in Python file)
import xlwings as xw

@xw.func
def my_sum(x, y):
    """Add two numbers"""
    return x + y

@xw.func
@xw.arg('data', ndim=2)
def my_array_func(data):
    """Process array data"""
    import numpy as np
    return np.sum(data)

# These become Excel functions: =my_sum(A1, B1)

Application Control

# Excel application settings