I'm a Python software developer with an interest in applied statistics. This is an excellent book on data analysis, but for review purposes, it's worth initially pointing out what this book is not.
It is not a comprehensive survey of open source tools that are available, and it does not contain many examples of working code to implement the techniques he talks about, though there are some. For this reason, I'd strike the "with Open Source Tools" from the title in evaluating whether you want to purchase the book.
The author greatly favors mathematical notation over code examples in describing the data analysis techniques he presents. While this is not a bad thing per se, you'll have to struggle to comprehend the content if you're a programmer without an academic familiarity with math, or if you've been away from mathematics for a long time.
As other reviewers have pointed out, the organization of the content is somewhat disjointed. Going from chapter to chapter, there is little in the way of causality, and the early chapters are pretty math-heavy. The reader is advised to consult appendices at the back of the book to refresh themselves on the basics, if required.
Wait! I didn't say you shouldn't buy it.
Despite a few shortcomings, this book does offer a good introduction and overview of several basic techniques. It's an excellent survey of the current data analysis landscape for anyone who's not familiar with it. If a topic seems irrelevant to you, it's pretty easy to skip that chapter and move forward.
On top of that, the author's writing style and ways of explaining relatively esoteric concepts is generally very good. As with many good books, you get the sense the author is a co-worker, trying to explain something to you in terms you can understand. It's very example-based, even if those examples don't always involve code.
All in all, to get the most out of this book, the best approach is careful and methodical study. The author covers many topics quickly, and not any one in depth, so if one chapter interests you, I'd plan on consulting other resources on particular topics. Luckily, the author does offer several "Further Reading" recommendations for each topic.
Most books containing information on these techniques are far harder to read, and they generally cost at least twice as much. Highly recommended. Thanks for this one, Philipp.
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Top reviews from other countries
- bkReviewed in Canada on July 28, 2018
The book provides very good math and stats foundation without diving into the code
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