Effective Pandas: Patterns for Data Manipulation (Treading on Python)

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I think that is because we are pretty early on with the library and crossovers from science to programming. I highly recommend this book for anyone who wish to learn a little bit about pandas and use it to clean data set.

Seller shipped immediately but the book took over half a month to arrive, due to the carrier used on the first leg, to get the package to USPS. Would you say that this book is a reference book or does it require thorough reading to get the best out of it? Matt Harrison is the Pandas guru, which in my opinion is equivalent to being Canelo Alvarez of boxers or the Esther Perel of therapists; he’s mastered the fundamentals and knows more than most anyone about the Pandas package.I have taught to other co-workers using this book: this book is well organized in chapters with an brief intro, then the functions and at the end some exercises that help the Pandas learner to apply the knowledge. Bonus: At the end of each chapter, you will find exercises that make you practice right away the concepts you’ve just read.

In this article, we will explore 5 advanced functions in Pandas to help you improve your efficiency when working with Pandas library. This week on the show, Matt Harrison talks about his new book, “Effective Pandas: Patterns for Data Manipulation. It has been said to invest a good deal of time into marketing, and I believe that has been the case with this book.Even if you are ultimately going to be working with terabytes of data, you’ll start out doing exploratory data analysis. Beyond just explaining functionality, Matt draws from practical experience to compare methods, highlight nuances, and explain common pitfalls.

The book is full of useful information and practical knowledge for the daily use of pandas, and also contains interesting focus on some external features such as Cython, CatBoost or sparklines. It is also a legit hands-on material, and even the session on debugging chains that starts with commenting commands before applying more robust debugging methods mimics what data scientists are really doing in the wild.

There are so many Python-based libraries out there which can be used for a variety of data science tasks. We will demonstrate how to do this in Pandas as well as show some of the situations you might want to look out for. I am using pandas for quite a while but never knew i was doing it in dumb way until i started reading this book.