xlsx

name	xlsx
description	Create, read, and modify Excel (.xlsx) spreadsheets using Python libraries openpyxl and pandas.
license	Apache 2.0

XLSX Skill

This skill provides capabilities to work with Excel spreadsheets (.xlsx) using Python.

Core Capabilities

1. Create New Spreadsheets: Generate .xlsx files programmatically.
2. Read Data: Extract data from sheets into structured formats.
3. Modify Existing Sheets: Update cells, add rows, or change formatting.
4. Data Analysis: Load data into pandas DataFrames for analysis.

Dependencies

This skill relies on openpyxl and pandas.

pip install openpyxl pandas

Workflows

1. Creating a New Workbook

Use openpyxl to create a new workbook.

from openpyxl import Workbook

wb = Workbook()
ws = wb.active
ws.title = "My Sheet"

# Add data
ws['A1'] = "Name"
ws['B1'] = "Value"
ws.append(["Alice", 100])
ws.append(["Bob", 200])

wb.save("output.xlsx")

2. Reading with Pandas

To easily read an Excel file into a DataFrame:

import pandas as pd

df = pd.read_excel("data.xlsx", sheet_name="Sheet1")
print(df.head())

3. Modifying an Existing Workbook

To edit an existing file:

from openpyxl import load_workbook

wb = load_workbook("existing.xlsx")
ws = wb.active

# Update a cell
ws['B2'] = 999

# save
wb.save("updated.xlsx")

Best Practices

• Library Choice: Use pandas for heavy data reading/analysis. Use openpyxl for formatting, styles, and precise cell manipulation.
• File Safety: Close files properly or use context managers if available (though openpyxl handles save/close explicitly).
• Large Files: For very large files, consider using openpyxl's read_only=True mode or processing in chunks with pandas.

Resources

• openpyxl Documentation
• pandas read_excel Documentation