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Use R to turn data into insight, knowledge, and understanding. With this practical book, aspiring data scientists will learn how to do data science with R and RStudio, along with the tidyverse—a collection of R packages designed to work together to make data science fast, fluent, and fun. Even if you have no programming experience, this updated edition will have you doing data science quickly.

You'll learn how to import, transform, and visualize your data and communicate the results. And you'll get a complete, big-picture understanding of the data science cycle and the basic tools you need to manage the details. Updated for the latest tidyverse features and best practices, new chapters show you how to get data from spreadsheets, databases, and websites. Exercises help you practice what you've learned along the way.

You'll understand how to:

**Visualize:**Create plots for data exploration and communication of results**Transform:**Discover variable types and the tools to work with them**Import:**Get data into R and in a form convenient for analysis**Program:**Learn R tools for solving data problems with greater clarity and ease**Communicate:**Integrate prose, code, and results with Quarto

- Introduction
- I. Whole Game
- 1. Data Visualization
- 2. Workflow: Basics
- 3. Data Transformation
- 4. Workflow: Code Style
- 5. Data Tidying
- 6. Workflow: Scripts and Projects
- 7. Data Import
- 8. Workflow: Getting Help
- II. Visualize
- 9. Layers
- 10. Exploratory Data Analysis
- 11. Communication
- III. Transform
- 12. Logical Vectors
- 13. Numbers
- 14. Strings
- 15. Regular Expressions
- 16. Factors
- 17. Dates and Times
- 18. Missing Values
- 19. Joins
- IV. Import
- 20. Spreadsheets
- 21. Databases
- 22. Arrow
- 23. Hierarchical Data
- 24. Web Scraping
- V. Program
- 25. Functions
- 26. Iteration
- 27. A Field Guide to Base R
- VI. Communicate
- 28. Quarto
- 29. Quarto Formats
- Index
- About the Authors