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R for Data Science: Import, Tidy, Transform, Visualize, and Model Data, (Paperback)
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Use R to turn data into insight, knowledge, and understanding.
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| Country of Origin | This item will be imported from US |
| What is in the box | R for Data Science:... For more details, please check description/product details |
Who Should Buy?
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Data Science Beginners
Ideal for beginners seeking an accessible introduction to data science concepts using the R programming language.
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Statisticians
Great for statisticians needing practical guidance on using R for data manipulation, visualization, and statistical modeling.
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Analysts Transitioning
Beneficial for analysts transitioning from other software to R, providing hands-on practical examples in data analysis.
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Advanced Users
Not suitable for advanced users who already possess extensive knowledge of R and data science methodologies.
Product Description
R for Data Science: Import, Tidy, Transform, Visualize, and Model Data, (Paperback)
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Hadley Wickham Ages 3-5 Kids' Books Editorial Review
R for Data Science: Import, Tidy, Transform, Visualize, and Model Data is a comprehensive paperback guide that dives deep into the fundamentals of data science. This non-fiction book, published by O'Reilly Media in July 2023, spans 576 pages and is ideal for college-level engineering students. The second edition by editor Garrett Grolemund focuses on practical applications, making it an excellent resource for learning how to manipulate and visualize data effectively. Readers appreciate its clear explanations and hands-on approach, which simplifies complex concepts in data science.
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Pros
- Comprehensive guide for data science beginners
- Practical applications with clear explanations
- Ideal for college-level engineering students
- Second edition offers updated content
- User-friendly format for easy understanding
Cons
- Reading level may seem basic for advanced users
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Features & Benefits
- Learn data science with R and RStudio
- Utilize the tidyverse packages for efficient data science
- Import, transform, and visualize data easily
- Understand the complete data science cycle and basic tools
- Practice exercises to reinforce learning
- Integrate prose, code, and results with Quarto
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