In this chapter, we demonstrated the use of R Markdown to produce dynamic documents where tables, graphics, and interactive plots can be easily embedded. Then we saw a few simple examples of shiny apps which are basically web-based interactive apps with an R backend. With these powerful productivity tools, data analysis can be made more interesting and full of fun because the outcome can be demonstrated in a nice, interactive way, which is usually better for conveying more information, drawing more insights and making better decisions.
Now we have finished this book. We started learning R by getting familiar with the fundamental concepts, data structures and language constructs and features. We went through a wide range of examples to understand how these fit the needs of practical data analysis. To build a concrete and consistent understanding of the R programming language and the behavior of data structures, we discussed several advanced topics such as R's evaluation model, metaprogramming...
