**R-exercises**, and kindly contributed to R-bloggers)

**INTRODUCTION**

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.

Before proceeding, please follow our short tutorial.

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.

to check your answers.

**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()`

.

### Related exercise sets:

**leave a comment**for the author, please follow the link and comment on their blog:

**R-exercises**.

R-bloggers.com offers

**daily e-mail updates**about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more…

Source:: R News