ABSTRACT
This chapter explores a few alternatives for making more sophisticated-and in particular, dynamic-data graphics. As Web browsers became more complex, the desire to have interactive data visualizations in the browser grew. Thus far, all of the data visualization techniques that we have discussed are based on static images. However, newer tools have made it considerably easier to create interactive data graphics. Plot.ly specializes in online dynamic data visualizations and, in particular, the ability to translate code to generate data graphics between R, Python, and other data software tools. The dygraphs package generates interactive time series plots with the ability to brush over time intervals and zoom in and out. The flexdashboard package provides a straightforward way to create and publish data visualizations as a dashboard.
