This is a killer book for the Python and data wrangling professional, making all other books look like elementary school treatments. I've read 7 Pandas books and 32 Python books that have Pandas sections. Stepanie Molin's is by far the strongest, most detailed, easiest to follow, best-exampled book, and easiest to understand of any of the 39 books read. All other books pale in comparison to this must-read book from Molin.
The datasets are intuitive. Not a boring texty book. Instead, lots of example code appears on every single page, illustrating the features. The story and example code flow together, not skipping around or showing disjointed points. The chapters follow your workflow, from data ingest and EDA to data cleaning, data wrangling, visualizataion, and finally to applications.
Thorough treatments are given to data cleaning, data wrangling, and data enrichment as separate topics, going into deep details on how to reshape and reindex data frames, how to do proper joins on data frames, left, right, inner, and outer, and how to do many other data cleaning and wrangling steps. For exaple, you'll learn how to set a new index, and why you should do that. And when inserting rows from different dataframes, you can leave yourself a new indicator column that shows you which table added the row. Pandas has many features like this that professionals should know, and Stephanie Molin shows the "how to".
Of course there's a GitHub link so you can download the example datasets. Honestly, I'm only up through data wrangling - have not even reached the financial analysis, machine learning, and advanced visualization code. I can hardly wait to work all the examples in person. (As you know, reading is good, but building the code is by far the most effective way to learn.)
Thanks Stephanie for devoting the time to making this a wonderful detailed and usable guide on how to use Pandas to solve my customer's problems. What a joy to read and use. This is the first and best book you should buy for Pandas.
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From the Publisher
What makes this second edition of Hands-On Data Analysis with Pandas stand out from other pandas titles?
Hands-On Data Analysis with Pandas is not your typical data science book. Say goodbye to the stereotypical datasets that most tutorials and books use and say hello to real-world data with real-world issues; after all, the data you will work with in real life won’t be perfect either.
This book shows you how to work with realistic datasets, so you can master the use of pandas for data analysis. Elements of software engineering are also included throughout the chapters, which will strengthen your programming skills—you’ll learn how to build scripts with command-line arguments, package analysis code in classes, and build Python packages for modular and reusable analysis code.
What's new in the second edition of Hands-On Data Analysis with Pandas?
In this edition, the code examples have been updated for newer versions of the libraries used. The book also features new and revised examples highlighting new features in pandas 1.2. In addition, there are significant changes to the content of some chapters, while others have new examples and/or datasets.
What are the key takeaways for the readers buying this book?
Working with data doesn’t preclude good programming skills. This book will instill confidence and teach the concepts needed to write quality data science code using pandas and other Python data science libraries. You'll be able to apply new data wrangling and visualization skills to a variety of real-world datasets and have the confidence to search for solutions to common problems in both the documentation and resources like Stack Overflow with a solid foundation in pandas.
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Top reviews from other countries
Vitor Ribeiro
That's a very useful book. I do recommend buying it.
Reviewed in Japan on August 26, 2021
