• May include: A book cover titled Python in Excel Step-by-Step by David Langer. The cover features a dark gray background with white and light blue text. A horizontal band across the middle displays a colorful graphic of a creature with sharp teeth.
  • May include: A book contents page titled CONTENTS, listing sections including ACKNOWLEDGMENTS, ABOUT THE AUTHOR, ABOUT THE TECHNICAL EDITORS, INTRODUCTION, CHAPTER 1: INTRODUCING PYTHON IN EXCEL, and CHAPTER 2: DATA TYPES with corresponding page numbers.
  • May include: A black and white table of contents page from a technical book. The text lists Chapter 3: Data Structures and Chapter 4: Control Flow and Loops, with sub-sections including Lists, Dictionaries, Tuples, Sets, Slicing Data, and if/else statements.
  • May include: A black and white table of contents page from a technical book, listing chapters and sub-sections including for Loops, while Loops, Comprehensions, Functions, Lambdas, and Data Table Fundamentals with corresponding page numbers.
  • May include: A page from a book contents section titled Chapter 7: Working with Columns, listing technical subheadings and page numbers ranging from 109 to 148. The text is black on a white background, organized in a structured list format.
  • May include: A page from a book contents section titled Chapter 8 Working with Data Tables and Chapter 9 Data Visualization. It lists numbered sections and subsections including Datetime Columns, Changing Dataframes, Filtering Dataframes, Combining Dataframes, Pivoting Dataframes, and Introducing Plotnine with corresponding page numbers.
  • May include: A page from a book contents section titled CONTENTS, listing chapters and sub-sections including 9.2.2 Bar Charts on page 206 through 10.4 Continue Your Learning on page 249, ending with an INDEX on page 251, all in black text on white.
  • May include: A book cover titled Python in Excel Step-by-Step by David Langer. The cover features a dark gray background with white and light blue text. A horizontal band across the middle displays a colorful graphic of a creature with sharp teeth.
  • May include: A book contents page titled CONTENTS, listing sections including ACKNOWLEDGMENTS, ABOUT THE AUTHOR, ABOUT THE TECHNICAL EDITORS, INTRODUCTION, CHAPTER 1: INTRODUCING PYTHON IN EXCEL, and CHAPTER 2: DATA TYPES with corresponding page numbers.
  • May include: A black and white table of contents page from a technical book. The text lists Chapter 3: Data Structures and Chapter 4: Control Flow and Loops, with sub-sections including Lists, Dictionaries, Tuples, Sets, Slicing Data, and if/else statements.
  • May include: A black and white table of contents page from a technical book, listing chapters and sub-sections including for Loops, while Loops, Comprehensions, Functions, Lambdas, and Data Table Fundamentals with corresponding page numbers.
  • May include: A page from a book contents section titled Chapter 7: Working with Columns, listing technical subheadings and page numbers ranging from 109 to 148. The text is black on a white background, organized in a structured list format.
  • May include: A page from a book contents section titled Chapter 8 Working with Data Tables and Chapter 9 Data Visualization. It lists numbered sections and subsections including Datetime Columns, Changing Dataframes, Filtering Dataframes, Combining Dataframes, Pivoting Dataframes, and Introducing Plotnine with corresponding page numbers.
  • May include: A page from a book contents section titled CONTENTS, listing chapters and sub-sections including 9.2.2 Bar Charts on page 206 through 10.4 Continue Your Learning on page 249, ending with an INDEX on page 251, all in black text on white.
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Python in Excel Step-by-Step

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Python in Excel Step-by-Step is a practical, hands-on guide that empowers Excel users to unlock the full power of Python without abandoning the spreadsheet environment they already know. Designed for analysts, accountants, financial professionals, business users, data scientists, and Excel power users, this book provides a structured learning path from the fundamentals of Python in Excel to advanced data analysis, automation, and intelligent reporting. Whether you're replacing complex formulas, streamlining repetitive tasks, or working with datasets that exceed the limits of traditional spreadsheets, you'll discover how Python transforms Excel into a modern analytics platform.

Through step-by-step tutorials and real-world business scenarios, readers learn how to use Python alongside Excel to clean and transform data, perform statistical analysis, create compelling visualizations, automate reports, and build reproducible workflows. The book explores powerful Python libraries including Pandas, NumPy, Matplotlib, SciPy, and scikit-learn, demonstrating how they integrate seamlessly with Excel to enable advanced calculations, predictive analytics, financial modeling, data validation, and machine learning. Readers also learn how to connect Excel to databases, REST APIs, cloud services, and external data sources while leveraging Python to process millions of records efficiently and accurately.

Beyond data analysis, Python in Excel Step-by-Step introduces modern productivity techniques such as AI-assisted coding, workflow automation, reusable Python functions, and best practices for building maintainable analytical solutions. The book emphasizes performance optimization, error handling, debugging, and collaborative development, helping readers create scalable, transparent, and repeatable processes that reduce manual effort and improve decision-making across finance, operations, marketing, supply chain, and business intelligence.

Whether you're preparing executive dashboards, automating financial reports, analyzing customer behavior, forecasting business performance, or beginning your journey into data science, Python in Excel Step-by-Step provides the technical foundation and practical confidence to bridge the gap between spreadsheets and modern programming. Turn familiar Excel skills into powerful automation capabilities, transform data into actionable insights, and discover how Python can redefine the way you work with spreadsheets in the age of intelligent analytics.

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Listed on Jul 31, 2026
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