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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()`.