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This Month's Bestsellers
Automate Excel with Python
From Manual Grind to One-Click Workflow
by John Wengler
May 2026, 272 pp.
ISBN-13:<br>9781718504646
Print Book and FREE Ebook, $49.99
Ebook (PDF, Mobi, and ePub), $39.99
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Contents
Download Chapter 3: Creating and Manipulating Dataframes and Lists
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.
Author Bio<br>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.
Table of contents<br>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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