Data Wrangling with R

Part I. Introduction

1. The Role of Data Wrangling
Bradley C. Boehmke

2. Introduction to R
Bradley C. Boehmke

3. The Basics
Bradley C. Boehmke

Part II. Working with Different Types of Data in R

4. Dealing with Numbers
Bradley C. Boehmke

5. Dealing with Character Strings
Bradley C. Boehmke

6. Dealing with Regular Expressions
Bradley C. Boehmke

7. Dealing with Factors
Bradley C. Boehmke

8. Dealing with Dates
Bradley C. Boehmke

Part III. Managing Data Structures in R

9. Data Structure Basics
Bradley C. Boehmke

10. Managing Vectors
Bradley C. Boehmke

11. Managing Lists
Bradley C. Boehmke

12. Managing Matrices
Bradley C. Boehmke

13. Managing Data Frames
Bradley C. Boehmke

14. Dealing with Missing Values
Bradley C. Boehmke

Part IV. Importing, Scraping, and Exporting Data with R

15. Importing Data
Bradley C. Boehmke

16. Scraping Data
Bradley C. Boehmke

17. Exporting Data
Bradley C. Boehmke

Part V. Creating Efficient and Readable Code in R

18. Functions
Bradley C. Boehmke

19. Loop Control Statements
Bradley C. Boehmke

20. Simplify Your Code with %>%
Bradley C. Boehmke

Part VI. Shaping and Transforming Your Data with R

21. Reshaping Your Data with tidyr

Bradley C. Boehmke

22. Transforming Your Data with dplyr

Bradley C. Boehmke

Keywords: Statistics, Statistics and Computing/Statistics Programs, Statistical Theory and Methods, Data Structures, Big Data/Analytics, Visualization, Computer Graphics