R for Data Science: Import, Tidy, Transform, Visualize, and Model Data 2nd Edition
by Hadley Wickham(Author), Mine Çetinkaya-Rundel(Author), Garrett Grolemund(Author)
Publisher finelybook 出版社: O’Reilly Media; 2nd edition (July 18, 2023)
Language 语言: English
Print Length 页数: 576 pages
ISBN-10: 1492097403
ISBN-13: 9781492097402
Book Description
By finelybook
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 tidyverseâ??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
Intro duction.
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
16. Factors
15. Regular Expressions
17. Dates and Times
18. Missing Values
19. Joins IV. Import
20. Spre adsheets
21. Databases
22. Arrow
23. Hierarchical Data
24. Web Scraping V. Program
25. Functions
26. Iteration VI. Communicate
29. Quarto Formats
27. A Field Guide to Base R
28. Quarto
Index
About the Authors
