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Automate Excel with Python: A Practical Guide for Nonprogrammers [Pehme köide]

  • Formaat: Paperback / softback, 272 pages, kõrgus x laius: 234x177 mm, kaal: 369 g
  • Ilmumisaeg: 19-May-2026
  • Kirjastus: No Starch Press,US
  • ISBN-10: 1718504640
  • ISBN-13: 9781718504646
Teised raamatud teemal:
  • Pehme köide
  • Hind: 63,74 €
  • See raamat ei ole veel ilmunud. Raamatu kohalejõudmiseks kulub orienteeruvalt 3-4 nädalat peale raamatu väljaandmist.
  • Kogus:
  • Lisa ostukorvi
  • Tasuta tarne
  • Tellimisaeg 2-4 nädalat
  • Lisa soovinimekirja
  • Formaat: Paperback / softback, 272 pages, kõrgus x laius: 234x177 mm, kaal: 369 g
  • Ilmumisaeg: 19-May-2026
  • Kirjastus: No Starch Press,US
  • ISBN-10: 1718504640
  • ISBN-13: 9781718504646
Teised raamatud teemal:
This practical guide will help spreadsheet pros save time and boost productivity using beginner Python tools – without having to become a programmer.

Automate Excel with Python bridges the gap between Excel expertise and Python programming without forcing you to start from scratch. Unlike other programming guides, it’s specifically designed for Excel users who need more power and automation, not for professional programmers.

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.
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 ExcelPythonExcel 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
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.