What this book covers

Chapter 1, A Simple Guide to R, is a quick tutorial on getting started with R. You will learn how to install packages, access help on R, construct and edit matrices, create and manipulate data frames, and write and save plots.

Chapter 2, Basic and Interactive Plots, introduces some of the basic R plots, such as scatter, line, and bar charts. We will also discuss the basic elements of interactive plots using the googleVis package in R. This chapter is a great resource for understanding the basic R plotting techniques.

Chapter 3, Heat Maps and Dendrograms, starts with a simple introduction to dendrograms and further introduces the concept of clustering techniques. The second half of this chapter discusses heat maps and integrating heat maps with dendrograms to get a more complete picture.

Chapter 4, Maps, discusses the importance of spatial data and various techniques used to visualize geographic data in R. You will learn how to generate static as well as interactive maps in R. The chapter discusses the topic of shape files and how to use them to generate a cartogram.

Chapter 5, The Pie Chart and Its Alternatives, is a detailed discussion on how to generate pie charts in R. You will also learn about the various criticisms of pie charts and how the pie chart is transformed to overcome them. The chapter also provides you with various alternatives used by data scientists and visualization artists to overcome the limitation of a pie chart.

Chapter 6, Adding the Third Dimension, dives into constructing 3D plots. This chapter also introduces packages such as rgl and animation, which are used to create interactive 3D plots.

Chapter 7, Data in Higher Dimensions, demonstrates the use of visualizations that are used to display data in higher dimension. You will learn the techniques to generate sunflower plots, hexbin plots, Chernoff faces, and so on. This chapter also discusses the usefulness of network, radial, and coxcomb plots, which have been widely used in news.

Chapter 8, Visualizing Continuous Data, illustrates the use of visualizations to display time series data. The chapter also discusses some general concepts related to visualizing correlations, the shape of the distribution, and detection of outliers using box and whisker plots.

Chapter 9, Visualizing Text and XKCD-style Plots, illustrates the use of text in creating effective visualizations. This chapter focuses mainly on techniques to create word clouds, phase tree, and comparison clouds in R. You will also learn how to use the XKCD package to introduce humor in visualizations.

Chapter 10, Creating Applications in R, shows you the techniques to create presentations and R markdown documents for publishing on a blog or a website. The chapter further discusses the XML package used to extract and visualize data as well as using shiny package used to create interactive applications.