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Key benefits

This is the first book on pandas 1.x

Practical, easy to implement recipes for quick solutions to common problems in data using pandas

Master the fundamentals of pandas to quickly begin exploring any dataset

Description

The pandas library is massive, and it's common for frequent users to be unaware of many of its more impressive features. The official pandas documentation, while thorough, does not contain many useful examples of how to piece together multiple commands as one would do during an actual analysis. This book guides you, as if you were looking over the shoulder of an expert, through situations that you are highly likely to encounter. This new updated and revised edition provides you with unique, idiomatic, and fun recipes for both fundamental and advanced data manipulation tasks with pandas. Some recipes focus on achieving a deeper understanding of basic principles, or comparing and contrasting two similar operations. Other recipes will dive deep into a particular dataset, uncovering new and unexpected insights along the way. Many advanced recipes combine several different features across the pandas library to generate results.

Who is this book for?

This book is for Python developers, data scientists, engineers, and analysts. Pandas is the ideal tool for manipulating structured data with Python and this book provides ample instruction and examples. Not only does it cover the basics required to be proficient, but it goes into the details of idiomatic pandas.

What you will learn

Master data exploration in pandas through dozens of practice problems

Group, aggregate, transform, reshape, and filter data

Merge data from different sources through pandas SQL-like operations

Create visualizations via pandas hooks to matplotlib and seaborn

Use pandas, time series functionality to perform powerful analyses

Import, clean, and prepare real-world datasets for machine learning

Create workflows for processing big data that doesn't fit in memory

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Ivan and Zorro Mar 28, 2020

This book is great for both beginners and someone already familiar with pandas. And if you are that someone then you know this library is so big that you never quite feel like you know everything. For instance, how many people use the pandas testing module? What’s that you say , you didn’t know pandas had a testing module? Another highlight is the EDA chapter which also includes some nice coverage of Seaborn, in addition to the chapter devoted entirely to visualization libraries. This will quickly become your goto reference for pandas and working with data.If you are looking for new and interesting ways to leverage pandas and make your work flow more efficient this book will help. It does start at the beginning, but I would be surprised if you didn’t pick up a nugget right in the first chapter. It says pandas but actually the authors spend a lot of time with NumPy although they don’t always distinguish between the two – which does make sense since pandas is for the most part a wrapper around many libraries, NumPy being chief among them.Personally I would have used fewer pages by showing less output, but that is one of the few complaints I have. I just don’t think we really need to see 10 lines of output for every step. Also I nice clear link to github for cloning the data would have been nice.

Amazon Verified review

Nathan Weston Apr 01, 2020

This is a huge book that's packed with details on both basic and advanced usage of Pandas. Each recipe is mostly self-contained, so you can jump straight to any topic you need to know more about without hunting around the book for all the pieces. This does mean there's some amount of repetition if you're reading start to finish, but I think it's a worthwhile trade-off. The accompanying Jupyter Notebook examples are also a nice addition.

Prayson Daniel Mar 16, 2020

I thought I knew Pandas until I read the first edition three years ago. There are so many new techniques I learnt and relearned by going through this revised version. Upgrading recipes to Python 3.6+ syntax has refined the simplicity and readability of the codes.Two things that stands out and makes me love this book are: (1) the accompanying codes in form of Jupyter Notebooks: Programming is learnt by doing and not just by reading,—having codes for each recipe in a clear and interactive is priceless, (2) the scope: this book goes beyond Pandas syntax. The application and visualisation are thoroughly covered.The only challenge, for beginners, I believe, will be a smooth setting up correct environment to experiment with these recipes. Perhaps creating a Dockerfile/docker-compose file which will build the entire step-up, Python version, libraries, spinning up Jupyter, and attach volumes with a single command, as part of accompanying codes, would make the whole experience divine. In this way, the only requirement needed to enjoy this book is the installation of Docker.

Tripp Parker Apr 10, 2020

The book is well thought out, provides an excellent framework for Pandas. If you've read other books that are by Matt Harrison, then you'll appreciate the quality and context of this book.

Bookworm_Live Sep 17, 2021

A really wonderful no-nonsense book. The author gives insight into how Pandas can be used in real world with all practical scenarios and usages. Highly Recommend.

Pandas 1.x Cookbook: Practical recipes for scientific computing, time series analysis, and exploratory data analysis using Python , Second Edition

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