Excel 2019 Bible

Author: Michael Alexander, Richard Kusleika and John Walkenbach
Publisher: Wiley
Pages: 1120
ISBN: 9781119514787
Print:1119514789
Kindle: B07J1ZSLDT
Audience: Excel users
Rating: 4
Reviewer: Kay Ewbank

This is a big book that attempts to cover everything you could ever want to know about Excel 2019. The difficulty lies in having one book for everything from 'this is a worksheet' to 'creating custom add-ins'.

This is the latest edition of a popular book that until this edition was written by John Walkenbach. It has now been updated by two other authors, but this is not a total rewrite - where Excel hasn't changed, much of the previous material remains untouched or lightly edited.

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There are six section in this the book and the first is the obligatory scene setting of getting started with Excel, with chapters introducing it, showing how to enter end edit workbook data, performing worksheet operations such as changing the name of a worksheet or inserting a row or column. There's a chapter on working with ranges and tables, another on formatting worksheets, and one on understanding files and templates. This part of the book finishes with chapters on printing your work and customizing the Excel user interface.

 

Part II moves on to the heart of Excel for most users, working with formulas and functions. Individual chapters cover mathematical, text, and date and time functions before the authors move on to conditional analysis, then lookups. Financial and statistical analysis functions are covered next, followed by using tables and conditional formatting to highlight cells that meet particular criteria. This part of the book closes with good chapters on understanding and using array formulas, and how to make your formulas error free.

The next part of the book is on creating charts and graphics. After the basics, there's a chapter described as advanced charting techniques that covers working with titles and legends, and hiding a data series. More interesting is a chapter on sparkline graphics, and another on using custom number formats and shapes.

Data management and analysis is next on the agenda. The authors begin with importing and cleaning data, then look at data validation. There's an interesting chapter on creating and using worksheet outlines to show data in more of a summary view, after which this part of the book moves on more to the analysis side with chapters on pivot tables and what-if analysis. Chapters on goal seeking and solver, and the analysis toolpak are both good.

Power Pivot and Power Query get a section devoted just to themselves, with useful chapters on working directly with the internal data model and adding formulas to Power Pivot. There are four chapters on Power Query, covering topics including transforming data with Power Query, making queries work together, and enhancing Power Query productivity.

The remaining 100 pages of the book are in Part VI Automating Excel. The section starts with a look at recording macros before moving on to more general VBA. There's a chapter on creating custom worksheet functions that could have usefully been much longer, followed by two chapters on userforms and userform controls. Excel events are tackled next, and the book ends with a chapter of example VBA projects and a brief look at creating custom Excel add-ins.

Conclusion

What you think of the book depends on what you know already. If someone hasn't ever seen a spreadsheet, the early chapters give useful information. For most of our audience, there's a lot of the book dedicated to information you'll know already. The more advanced topics are written accurately, but space is tight - even in a book of over 1000 pages - when you have to assume the reader knows nothing. There are useful sections on some of the more recent additions to Excel, but personally, I'd suggest you'd be better with a book on the specifics you're interested in rather than a general one-size-fits-all.

 

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Foundational Python For Data Science

Author: Kennedy Behrman
Publisher: Pearson
Pages:256
ISBN: 978-0136624356
Print: 0136624359
Kindle: B095Y6G2QV
Audience: Data scientists
Rating: 4.5
Reviewer: Kay Ewbank

This book sets out to be a simple introduction to Python, specifically how to use it to work with data.



Learn to Code by Solving Problems

Author: Dr. Daniel Zingaro
Publisher: No Starch Press
Date: June 2021
Pages: 335
ISBN: 978-1718501324
Print: 1718501323
Kindle: B08FH92YL8
Audience: People wanting to learn Python
Rating: 4
Reviewer: Mike James
Solving problems - sounds good?


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