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. In this book, you'll learn about the following APIs and packages that deal specifically with data science applications: reader, Tibble, forces, lubridate, stringr, tidy, magnetite, dplyr, purrr, ggplot2, model, 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 forecast, time and dates with lubridate, and strings with string Format data using tidy 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 two and data fit for models using the model and broom Report results with markdown, knitr, shiny, and more