Felix Zumstein - Python for Excel
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- Book:Python for Excel
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What can Python do for Excel? If youve ever dealt with unexpected workbook crashes, broken calculations, and tedious manual processes, youll want to find out. Python for Excel is a comprehensive and succinct overview to getting started with Python as a spreadsheet user, and building powerful data products using both. Dont let the fear of learning to code keep you away: Felix provides an exceptional foundation for learning Python that even experienced programmers could benefit from. Moreover, he frames this information in a way that is quickly accessible and applicable to you as an Excel user. You can quickly tell reading this book that it was written by someone with years of experience teaching and working with clients on how to use Excel to its fullest extent with the help of Python programming. Felix is uniquely suited to show you the possibilities of learning Python for Excel; I hope you enjoy the master class as much as I did.
George Mount, Founder, Stringfest Analytics
Python is the natural progression from Excel and its tempting to simply discard Excel all together. Tempting, but hardly realistic. Excel is here, and here to stay, both in the corporate world and as a useful desktop tool at home and in the office. This book provides the much needed bridge between these two worlds. It explains how you can integrate Python into Excel and free yourself from the inevitable disaster of huge workbooks, thousands of formulas, and ugly VBA hacks. Python for Excel is probably the single most useful book on Excel that I have read and an absolute must-read for any advanced Excel user. A highly recommended book!
Andreas F. Clenow, CIO Acies Asset Management and author of international best-sellers Following the Trend, Stocks on the Move,
and Trading Evolved
Excel remains a cornerstone tool of the financial world, but a vast amount of these Excel applications are an irresponsible mess. This book does an excellent job of showing you how to build better, more robust applications with the help of xlwings.
Werner Brnnimann, Derivatives and DeFi practitioner and cofounder, Ubinetic AG
Excel and Python are two of the most important tools in the Business Analytics toolbox, and together they are far greater than the sum of their parts. In this book, Felix Zumstein lays out his unparalleled mastery of the many ways to connect Python and Excel using open source, cross-platform solutions. It will be an invaluable tool for business analysts and data scientists alike, and any Python user looking to harness the power of Excel in their code.
Daniel Guetta, Associate Professor of Professional Practice and Director of the Business Analytics Initiative at Columbia
Business School and coauthor of Python for MBAs
by Felix Zumstein
Copyright 2021 Zoomer Analytics LLC. All rights reserved.
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- March 2021: First Edition
- 2021-03-04: First Release
See http://oreilly.com/catalog/errata.csp?isbn=9781492081005 for release details.
The OReilly logo is a registered trademark of OReilly Media, Inc. Python for Excel, the cover image, and related trade dress are trademarks of OReilly Media, Inc.
The views expressed in this work are those of the author, and do not represent the publishers views. While the publisher and the author have used good faith efforts to ensure that the information and instructions contained in this work are accurate, the publisher and the author disclaim all responsibility for errors or omissions, including without limitation responsibility for damages resulting from the use of or reliance on this work. Use of the information and instructions contained in this work is at your own risk. If any code samples or other technology this work contains or describes is subject to open source licenses or the intellectual property rights of others, it is your responsibility to ensure that your use thereof complies with such licenses and/or rights.
978-1-492-08100-5
[LSI]
Microsoft is running a feedback forum for Excel on UserVoice where everybody can submit a new idea for others to vote on. The top voted feature request is Python as an Excel scripting language, and it has roughly twice as many votes as the second most voted feature request. Though nothing really happened since the idea was added in 2015, Excel users were fueled with new hope at the end of 2020 when Guido van Rossum, the creator of Python, tweeted that his retirement was boring and he would join Microsoft. If his move has any influence on the integration of Excel and Python, I dont know. I do know, however, what makes this combination so compelling and how you can start using Excel and Python togethertoday. And this is, in a nutshell, what this book is about.
The main driving force behind the Python for Excel story is the fact that we are living in a world of data. Nowadays, huge datasets are available to everybody and about everything. Often, these datasets are so big that they dont fit into a spreadsheet anymore. A few years ago, this may have been referred to ).
Python, on the other hand, is a general-purpose programming language that has become one of the most popular choices amongst analysts and data scientists. If you use Python with Excel, you are able to use a programming language that is good at all aspects of the story, whether thats automating Excel, accessing and preparing datasets, or performing data analysis and visualization tasks. Most importantly, you can reuse your Python skills outside of Excel: if you need to scale up your computing power, you could easily move your quantitative model, simulation, or machine learning application to the cloud, where practically unconstrained computing resources are waiting for you.
Through my work on xlwings, the Excel automation package that we will meet in or at a physical event like a meetup or a conference.
On a regular basis, I am asked to recommend resources to get started with Python. While there is certainly no shortage of Python introductions, they are often either too general (nothing about data analysis) or too specific (full scientific introductions). However, Excel users tend to be somewhere in the middle: they certainly work with data, but a full scientific introduction may be too technical. They also often have specific requirements and questions that arent answered in any of the existing material. Some of these questions are:
Which Python-Excel package do I need for which task?
How do I move my Power Query database connection over to Python?
Whats the equivalent of Excels AutoFilter or pivot table in Python?
I wrote this book to get you from zero Python knowledge to be able to automate your Excel-centric tasks and leverage Pythons data analysis and scientific computing tools in Excel without any detours.
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