Python for Excel Users

Python for Excel Users

Know Excel? You Can Learn Python
by Tracy Stephens
August 2025, 344 pp.
ISBN-13: 
9781718503984
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Download Chapter 8: Retrieving External Data with APIs

Look Inside!

Python for Excel Users pages 102-103Python for Excel Users pages 142-143Python for Excel Users pages 196-197

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.

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

Afterword

The chapters in red are included in this Early Access PDF.