R for Data Science 2nd Edition Wickham, Cetinkaya-Rundel, & Grolemund Like New

The product is the second edition of “R for Data Science” by Hadley Wickham, Mine Cetinkaya-Rundel, and Garrett Grolemund. Published by O’Reilly Media, this textbook focuses on data modeling, design, visualization, processing, and mining. With a publication year of 2023, this trade paperback book offers 576 pages of content in English. It aims to guide readers through the process of importing, tidying, transforming, visualizing, and modeling data using R programming language. The book is a comprehensive resource for individuals looking to enhance their skills in data science and analysis.

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electricity for the trades

Master the fundamentals of electrical systems with “Electricity for the Trades,” a comprehensive textbook by Frank D. Petruzella. Published by McGraw-Hill Higher Education in 2006, this trade paperback is an essential resource for students and professionals alike, focusing on the practical applications of electricity in the technology and engineering sectors. The book delves into various electrical subjects, offering in-depth coverage that enhances understanding of the material. Written in clear, accessible English, it’s designed to support learners in developing a strong grasp of electrical principles and their real-world applications. Whether you’re pursuing a degree or seeking to expand your professional knowledge, this textbook is an invaluable addition to your educational library.

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Python for Data Analysis Data Wrangling with Pandas NumPy and Jupyter FS

“Python for Data Analysis: Data Wrangling with Pandas, NumPy, and Jupyter” by Wes McKinney is a comprehensive textbook published by O’Reilly Media. This book covers essential topics in data analysis, including data visualization, processing, and mining, all using the popular programming language Python. With a strong focus on practical applications, this text is designed for students and professionals looking to deepen their understanding of data analysis techniques. The book’s 579 pages provide detailed insights and guidance on working with data using various tools and techniques in the Python ecosystem.

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