If you’re comfortable in Excel, but you’ve hit a wall - slow files, broken formulas, hours spent on repetitive tasks - Python for Excel Users offers a way forward. The book 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.
Author Bio
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.
Table of contents
Introduction
PART I: FROM SPREADSHEETS TO CODE Chapter 1: Python Setup Essentials to Get You Started Chapter 2: Python Concepts Explained Through Excel Chapter 3: Creating Automations with Python Scripts Chapter 4: Keeping Track of Code with Version Control
PART II: DATA ANALYSIS DONE RIGHT Chapter 5: Interactive Coding for Data Analysis Chapter 6: Data Manipulation Made Easy Chapter 7: Storing and Accessing Data with a Database Chapter 8: Retrieving External Data with APIs Chapter 9: Visualizing Data with Charts Chapter 10: Sharing Data with Interactive Reports
PART III: CRAFTING GOOD CODE Chapter 11: Writing Simple, Scalable Code with Classes Chapter 12: Debugging and Testing Your Code Chapter 13: Three Habits for Effective Coding
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