An interactive graphic invites the viewer to become an active partner in the analysis and allows for immediate feedback on how the data and results may change when inputs are modified. Interactive graphics can be extremely useful for exploratory data analysis, for teaching, and for reporting.
Because there are so many different kinds of interactive graphics, there has been an explosion in R packages that can produce them (e.g. animint, shiny, rCharts, rMaps, ggvis, htmlwidgets). A beginner with little knowledge of interactive graphics can thus be easily confused by (1) understanding what kinds of graphics are useful for what kinds of data, and (2) finding an R package that can produce the desired type of graphic. This tutorial solves these two problems by (1) introducing a vocabulary of keywords for understanding the different kinds of graphics, and (2) explaining what R packages can be used for each kind of graphic.
Attendees will gain hands-on experience with using R to create interactive graphics. We will discuss several example data sets and several R interactive graphics packages. Attendees will learn a vocabulary that helps to understand the strengths and weaknesses of the many different packages which are currently available.
For details, refer to tutorial description.
