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The ggvis package is used to make interactive data visualizations. The fact that it combines shiny’s reactive programming model and dplyr’s grammar of data transformation make it a useful tool for data scientists.

This package may allows us to implement features like interactivity, but on the other hand every interactive ggvis plot must be connected to a running R session.

Look at the examples given and try to understand the logic behind them. Then try to solve the exercises below using R and without looking at the answers. Then check the solutions.

Exercise 1

Create a list which will include the variables “Horsepower” and “MPG.city” of the “Cars93” data set and make a scatterplot. HINT: Use ggvis() and layer_points().

Exercise 2

Add a slider to the scatterplot of Exercise 1 that sets the point size from 10 to 100. HINT: Use input_slider().

Learn more about using ggvis in the online course R: Complete Data Visualization Solutions. In this course you will learn how to:

• Work extensively with the ggvis package and its functionality
• Learn what visualizations exist for your specific use case
• And much more

Exercise 3

Add a slider to the scatterplot of Exercise 1 that sets the point opacity from 0 to 1. HINT: Use input_slider().

Exercise 4

Create a histogram of the variable “Horsepower” of the “Cars93” data set. HINT: Use layer_histograms().

Exercise 5

Set the width and the center of the histogram bins you just created to 10.

Exercise 6

Add 2 sliders to the histogram you just created, one for width and the other for center with values from 0 to 10 and set the step to 1. HINT: Use input_slider().

Exercise 7

Add the labels “Width” and “Center” to the two sliders respectively. HINT: Use label.

Exercise 8

Create a scatterplot of the variables “Horsepower” and “MPG.city” of the “Cars93” dataset with size = 10 and opacity = 0.5.

Exercise 9

Add to the scatterplot you just created a function which will set the size with the left and right keyboard controls. HINT: Use left_right().

Exercise 10

Add interactivity to the scatterplot you just created using a function that shows the value of the “Horsepower” when you “mouseover” a certain point. HINT: Use add_tooltip().