Tracy Stephens

Python for Excel Users

Know Excel? You Can Learn Python. Sprache: Englisch.
epub eBook , 344 Seiten
ISBN 1718503997
EAN 9781718503991
Veröffentlicht 23. September 2025
Verlag/Hersteller No Starch Press
Familienlizenz Family Sharing

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Beschreibung

When Excel isn't enough, it's time to learn Python.
If you're comfortable in Excel, but you've hit a wall-slow files, broken formulas, hours spent on repetitive tasks-this book offers a way forward. It shows you how to take the work you already do in spreadsheets and make it faster, smarter, and more powerful with Python.
You'll start by setting up your environment and getting comfortable with Python through short, Excel-inspired exercises. From there, you'll gradually move into writing scripts that automate manual work, structure your data, and generate consistent results-no prior programming knowledge required.
You'll use your preexisting Excel skills to learn how to:
- Translate spreadsheet logic into Python code- Use pandas to clean, reshape, and filter data- Automate reports you'd normally build by hand- Read and write Excel files directly from Python- Connect to databases and APIs- Create professional visualizations with Plotly and Dash- Organize code into sharable modules and write simple tests
Throughout the book, you'll find practical examples that show why and how to move your work out of spreadsheets and into scripts, and how to resolve issues along the way.
Author Tracy Stephens has extensive practical experience with both Excel and Python. Her approach is grounded in real workflows, and she introduces each concept through tasks you've likely handled in Excel.
This book won't ask you to replace everything you do in spreadsheets, but it will help you use Python to work faster, more reliably, and with greater flexibility than you ever could with Excel.

Portrait

Tracy Stephens is a quantitative developer based in New York City. Her experience includes building systematic trading strategies at some of the world's top financial institutions. A long-time Python evangelist, she focuses on designing quantitative infrastructure that's flexible, explainable, and efficient---when she can successfully keep her one-eyed tuxedo cat off her keyboard.

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