Pandas In Action

Pandas is a popular data analysis library in Python that provides efficient sorting, analyzing, filtering, and munging of data. "Pandas in Action" is a comprehensive guide that teaches users how to master this versatile tool and advance their data science career. The book offers a friendly and example-rich introduction, covering operations on millions of rows, integration with other Python libraries, and user productivity. It begins with real-world datasets and teaches how to clean and format them for proper analysis. The author, Boris Paskhaver, is a software engineer, Agile consultant, and educator with extensive experience in Python and data analysis.

Format: Paperback / softback
Length: 525 pages
Publication date: 13 October 2021
Publisher: Manning Publications

Pandas, a popular data analysis library in Python, has gained widespread popularity for its efficient data manipulation capabilities. In Pandas in Action, author Boris Paskhaver provides a friendly and comprehensive guide to mastering this versatile tool and advancing your data science career.

Pandas' familiarity for users of spreadsheet software is a significant advantage. While its column-based grids may evoke memories of Excel or Google Sheets, Pandas offers far greater flexibility and power. It can efficiently handle operations on millions of rows, making it suitable for large-scale data analysis. Moreover, Pandas seamlessly integrates with other Python libraries such as statistics, machine learning, and more, expanding its applications.

One of the key strengths of Pandas is its user-friendly interface. It is clean, intuitive, and fast, allowing users to perform complex data analysis tasks without the need for extensive code. This accessibility makes Pandas suitable for both novice and experienced data scientists, enabling them to streamline their workflow and extract valuable insights from data efficiently.

Pandas in Action offers a comprehensive introduction to Python-based data analysis. The book begins by covering the basics of Pandas, including its data structures, indexing, and operations. It then delves into practical techniques for automating repetitive spreadsheet functionality, sorting columns, filtering data subsets, and creating multi-leveled indices. Each chapter serves as a self-contained tutorial, allowing readers to dip in whenever they encounter challenging problems.

One of the unique features of Pandas in Action is its emphasis on real-world datasets. Instead of relying on sterile or randomly created data, the book starts with a variety of datasets that are representative of real-world scenarios. These datasets are diverse, ranging from big and complex to small and incomplete. By working with these datasets, readers learn how to clean and format them for proper analysis, addressing common issues such as missing values, inconsistent data formats, and data anomalies.

Throughout the book, Paskhaver employs practical examples and hands-on exercises to reinforce the concepts presented. These examples are drawn from various domains, including finance, healthcare, and social sciences, allowing readers to apply their knowledge to real-world problems. The exercises are designed to challenge readers' understanding and help them develop their data analysis skills.

In addition to its comprehensive coverage of Pandas, Pandas in Action provides valuable insights into the field of data science. The book discusses the importance of data cleaning, data visualization, and statistical analysis in data science projects. It also touches upon the ethical considerations and best practices associated with data analysis, ensuring that readers approach their work with integrity and responsibility.

Whether you are a beginner looking to foray into the world of data analysis or an experienced data scientist seeking to enhance your skills, Pandas in Action is an invaluable resource. With its friendly and example-rich approach, the book makes it easy to dive into Python-based data analysis and unlock the full potential of Pandas. By mastering this versatile tool and applying its principles, you can efficiently sort, analyze, filter, and munge almost any type of data, paving the way for your data science career.

Weight: 808g
Dimension: 187 x 235 x 39 (mm)
ISBN-13: 9781617297434