Title
R for Data Science: Import, Tidy, Transform, Visualize, and Model Data,Used
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Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible.Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, bigpicture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way.You'll learn how to: Wrangle??transform your datasets into a form convenient for analysis Program??learn powerful R tools for solving data problems with greater clarity and ease Explore??examine your data, generate hypotheses, and quickly test them Model??provide a lowdimensional summary that captures true 'signals' in your dataset Communicate??learn R Markdown for integrating prose, code, and results
⚠️ WARNING (California Proposition 65):
This product may contain chemicals known to the State of California to cause cancer, birth defects, or other reproductive harm.
For more information, please visit www.P65Warnings.ca.gov.
- Q: How many pages are in 'R for Data Science'? A: This book contains five hundred eighteen pages. It covers a wide range of topics related to data science using R.
- Q: What is the binding type of this book? A: The binding type is paperback. This makes it lightweight and easy to carry around for study or reference.
- Q: What are the dimensions of 'R for Data Science'? A: The book measures five point nine one inches in length, one point one eight inches in width, and nine point eight four inches in height. These dimensions make it convenient for shelf storage.
- Q: What programming skills do I need to read this book? A: No previous programming experience is required. The book is designed for beginners to help them grasp data science concepts quickly.
- Q: How can I apply the concepts learned in this book? A: You can use the book to wrangle, explore, model, and communicate data insights effectively. It includes exercises for practical application.
- Q: Is this book suitable for self-study? A: Yes, this book is ideal for self-study. It provides a comprehensive introduction to data science along with practical exercises.
- Q: How do I keep this book in good condition? A: To maintain the book's condition, store it in a cool, dry place and avoid exposure to direct sunlight. Handle it gently to prevent wear and tear.
- Q: Is this book safe for children? A: Yes, the book is suitable for older children and young adults interested in learning about data science. However, younger children may need adult supervision.
- Q: What if I receive a damaged copy of the book? A: If you receive a damaged copy, you should contact the seller for return or exchange options. Ensure to check their return policy.
- Q: Can I use this book for a classroom setting? A: Yes, this book is excellent for classroom settings. It provides structured learning with exercises that can be used for group discussions.
- Q: What kind of exercises does this book include? A: The book includes practical exercises at the end of each section. These exercises help reinforce the concepts learned throughout the chapters.
- Q: Does this book cover advanced topics in data science? A: No, this book focuses primarily on introductory topics. It is designed for beginners to build foundational skills in data science.
- Q: What are the main topics covered in this book? A: Main topics include data importing, tidying, transforming, visualizing, and modeling data using R and the tidyverse.
- Q: Is there a digital version available for this book? A: Yes, there is often a digital version available. You should check with your preferred retailer for eBook options.
- Q: Who are the authors of 'R for Data Science'? A: The authors are Hadley Wickham and Garrett Grolemund. They are well-known figures in the R programming community.