This practical guide will help spreadsheet pros save time and boost productivity using beginner Python tools – without having to become a programmer. This book focuses on enhancing your existing Excel skills rather than replacing them. You’ll learn how Python’s dataframes work like virtual spreadsheets, extending what you already know while automating repetitive tasks. You’ll be able to import and export data seamlessly between Excel and Python to integrate coding into your current workflow. Concise, practical examples throughout will get you up and running quickly. Each topic addresses real problems Excel users face, with solutions you can implement immediately. The structure is deliberately flexible. Chapters progress logically but stand independently, so you can jump to exactly what you need without reading everything that came before. This makes it perfect for solving urgent problems or learning at your own pace. You’ll apply the techniques you learn to automate reports, clean messy data, perform complex calculations, and handle large datasets that would overwhelm Excel alone--all while leveraging your existing spreadsheet knowledge.

Autorentext

John Wengler taught himself Python to automate a spreadsheet process and solve a “million-dollar problem” at work. He is the author of Managing Energy Risk and has taught at the Illinois Institute of Technology and Tulane University.

Klappentext

AI can write the code. You still need to know what it does.

You’re already good at Excel. But you’re tired of the copy/paste, the helper columns, and the brittle formulas that break when someone adds a row. You want automation, and whether you write the code yourself or let AI generate it, you need to understand what’s actually running your business processes.

Automate Excel with Python teaches you to build real workflows, step-by-step. You’ll read messy workbooks into pandas dataframes, filter and reshape data without helper columns, merge sources without silent VLOOKUP failures, and export polished results with formatting intact. A capstone chapter ties it together: import a multi-tab workbook, generate exception reports, and email the results—all from one script you run with a single click.

You’ll learn how to:

• Read existing Excel files you already use into Python, even the messy ones
• Replace daily copy/paste routines with reusable scripts
• Merge and match data across sources with auditable results
• Handle dates, times, and the edge cases that break formulas
• Export from Python to Excel with column widths, number formats, and frozen panes intact
• Build workflows that run daily without babysitting
  AI can write the code. This book makes sure you’re the one in control of it.

Inhalt

Introduction

Part I: From Spreadsheets to Dataframes
Chapter 1: Getting Started with Python
Chapter 2: Displaying Data and Understanding Data Types
Chapter 3: Creating and Manipulating Dataframes and Lists
Chapter 4: Adding, Modifying, and Calculating Column Data
Chapter 5: Accessing and Transforming Individual Cell Values
Chapter 6: Filtering and Displaying Dataframes

Part II: Tools to Replicate Excel Functionality
Chapter 7: Counting and Summing Values
Chapter 8: Combining Dataframes
Chapter 9: Formatting and Calculating Dates and Times

Part III: Workflow Techniques
Chapter 10: Reading Excel Files into Dataframes
Chapter 11: Saving Dataframes to Excel
Chapter 12: There and Back Again: An Excel–Python–Excel Workflow

Appendix A: Working with Folders, Files, and Pathnames
Appendix B: Cleaning Up a Messy Spreadsheet
Appendix C: The Ducks Module
Python Quick Reference
Index**
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