Why interactive R custom visuals?
Let’s start with a graph you’ve already implemented in R. For example, consider the raincloud plot of Fare
versus Pclass
variables introduced in Chapter 19, Exploratory Data Analysis (this time not grouped by Sex
):
Figure 22.1: Raincloud plot for Fare (transformed) and Pclass variables
Focus for a moment just on the boxplots you see in Figure 22.1. Although the Fare
variable is already transformed according to Yeo-Johnson to try to reduce skewness, there are still some extreme outliers for each of the passenger classes described by the categorical variable Pclass
. For example, if you wanted to know the values of the transformed variable Fare
that correspond to the whiskers (fences) of the boxplot on the left so that you could then identify the outliers that are beyond these whiskers, it would be convenient to have these values appear when you hover the mouse near this boxplot. It would be even more interesting to know the...