Thinking in Pandas: How to Use the Python Data Analysis Library the Right Way


Thinking in Pandas: How to Use the Python Data Analysis Library the Right Way
By 作者:Hannah Stepanek
pages 页数: 186 pages
Publisher Finelybook 出版社: Apress; 1st ed. edition (6 Jun. 2020)
Language 语言: English
ISBN-10 书号:148425838X
ISBN-13 书号:9781484258385
Book Description to Finelybook sorting
Understand and implement big data analysis solutions in pandas with an emphasis on performance. This book strengthens your intuition for working with pandas, the Python data analysis library, By 作者:exploring its underlying implementation and data structures.
Thinking in Pandas introduces the topic of big data and demonstrates concepts By 作者:looking at exciting and impactful projects that pandas helped to solve. From there, you will learn to assess your own projects By 作者:size and type to see if pandas is the appropriate library for your needs. Author Hannah Stepanek explains how to load and normalize data in pandas efficiently, and reviews some of the most commonly used loaders and several of their most powerful options. You will then learn how to access and transform data efficiently, what methods to avoid, and when to employ more advanced performance techniques. You will also go over basic data access and munging in pandas and the intuitive dictionary syntax. Choosing the right DataFrame format, working with multi-level DataFrames, and how pandas might be improved upon in the future are also covered.
By the end of the book, you will have a solid understanding of how the pandas library works under the hood. Get ready to make confident decisions in your own projects By 作者:utilizing pandas―the right way.
What You Will Learn

Understand the underlying data structure of pandas and why it performs the way it does under certain circumstances
Discover how to use pandas to extract, transform, and load data correctly with an emphasis on performance
Choose the right DataFrame so that the data analysis is simple and efficient.
Improve performance of pandas operations with other Python libraries

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