R Data Science Quick Reference

In this handy, practical book you will cover each concept concisely, with many illustrative examples. You'll be introduced to several R data science packages, with examples of how to use each of them. 
In this book, you'll learn about the following APIs and packages that deal specifically with data science applications:  readr, tibble, forcates, lubridate, stringr, tidyr, magnittr, dplyr, purrr, ggplot2, modelr, broom, knitr, shiny, and more.
After using this handy quick reference guide, you'll have the code, APIs, and insights to write data science-based applications in the R programming language.  You'll also be able to carry out data analysis.  

You will:Get started with RMarkdown and notebooks
Import data with readr
Work with categories using forcats, time and dates with lubridate, and strings with stringr
Format data using tidyr and then transform that data using magrittr and dplyr
Write functions with R for data science, data mining, and analytics-based applications
Visualize data with ggplot 2 and data fit for models using modelr and broom
Report results with markdown, knitr, shiny, and more