New Book: R for Data Science; Visualize, Model, Transform, Tidy and Import Data

Recommended introductory text. It discusses some packages I was not really familiar with (like tibble).

Contents

Part I. Explore

1. Data Visualization with ggplot2
2. Workflow: Basics
3. Data Transformation with dplyr
4. Workflow: Scripts
5. Exploratory Data Analysis
6. Workflow: Projects

Part II. Wrangle

7. Tibbles with tibble
8. Data Import with readr
9. Tidy with tidyr
10. Relational Data with dplyr
11. Strings with stringr
12. Factors with forcats
13. Dates and Times with lubridate

Part III. Program

14. Pipes with magrittr
15. Functions
16. Vectors
17. Iteration with purrr

Part IV. Model

18. Model Basics with modelr
19. Model Building
20. Many Models with purrr and broom

Part V. Communicate

21. R Markdown
22. Graphics for Communication with ggplot2
23. R Markdown Formats
24. R Markdown Workflow

References

1. Hadley Wickham, Garrett Grolemund, R for Data Science: Import, Tidy, Transform, Visualize, and Model Data, O'Reilly Media; 1 edition (January 5, 2017), 522 pages, price: about $0.08 per page (glossy, with many color pictures) 
2. Website: http://r4ds.had.co.nz/