Python in Excel for Data Analytics (Packt)

Where to pre-order

The book releases on January 8, 2027 and is available now for pre-order. Links to additional booksellers will be added here as they go live.

• Amazon: Print, Kindle
• Packt: Print, ebook
• Barnes & Noble: Paperback

This book is still in development, so I’ll keep this page updated as more details, sample content, and retailer links become available. Check back for the latest.

About the book

Excel is one of the most widely used tools for business analysis, but many analytical tasks quickly reach the limits of formulas and built-in features. Python in Excel for Data Analytics shows how Python, now built directly into Excel, can extend what you already do: transform data more efficiently, run advanced statistical analysis, create richer visualizations, and model uncertainty, all within the environment you already know.

Through step-by-step explanations, practical business examples, and downloadable Excel workbooks, you’ll learn how to fold Python into your everyday Excel workflow. Each chapter tackles a realistic analytical task, from data cleaning and exploratory analysis to visualization, forecasting, and simulation. The book’s core idea is that Excel and Python complement each other: you keep the flexibility of the spreadsheet grid and add the analytical power of Python.

What you’ll be able to do

By the end of the book, you’ll be able to use Python inside Excel to perform deeper analysis than traditional spreadsheet tools allow. You’ll know how to:

• Move data between the spreadsheet grid and Python DataFrames
• Clean, reshape, and summarize datasets with pandas
• Build clear visualizations with Seaborn and Matplotlib
• Run statistical tests, regression models, and time series forecasts
• Model risk and uncertainty with Monte Carlo simulation
• Combine Python results with Excel dashboards and reports for better decisions

Table of contents

The chapter list below is current as of the book’s development and may shift slightly before release.

Part I. Introducing Python in Excel

1. Getting Started with Python in Excel
2. Exploring and Analyzing Data with pandas
3. Visualizing Data with Seaborn
4. Performing Exploratory Data Analysis

Part II. Building Analytical Models

5. Running Statistical Tests
6. Building Regression Models
7. Forecasting Time Series Data

Part III. Extending Excel with Python

8. Running Simulations and Scenario Models
9. Extracting Insights from Text Data
10. Integrating Python with Native Excel Features
11. Accelerating Analysis with AI Assistance
12. Continuing Your Python in Excel Journey

About the author

George Mount is the founder of Stringfest Analytics, a training and consulting firm specializing in modern Excel and data analytics. A Microsoft Excel MVP and author of Advancing into Analytics and Modern Data Analytics in Excel (O’Reilly), George helps organizations integrate Python, AI, and automation into their Excel workflows. He has trained professionals worldwide through corporate programs, LinkedIn Learning, and global conferences, empowering analysts to bridge business insight with advanced analytics.