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ggvis Exercises (Part-1)

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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. HINT: Use ggvis().

Exercise 2

Use the list you just created to make a scatterplot. HINT: Use layer_points().

Exercise 3

Use %>% to create the scatterplot of Exercise 2.

< aside class='stb-icon'>
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 4

Use the list you created in Exercise 1 to create a scatterplot and use “Cylinders” as stroke.

Exercise 5

Use the list you created in Exercise 1 to create a scatterplot and use “Cylinders” as fill.

Exercise 6

Use the list you created in Exercise 1 to create a scatterplot and use “EngineSize” as size.

Exercise 7

Use the list you created in Exercise 1 to create a scatterplot and use “Cylinders” as shape.

Exercise 8

Use the list you created in Exercise 1 to create a scatterplot with red color and black stroke.

Exercise 9

Use the list you created in Exercise 1 to create a scatterplot with size set to 300 and opacity to 0.5 .

Exercise 10

Use the list you created in Exercise 1 to create a scatterplot with cross as shape.

Related exercise sets:

  1. How to create interactive data visualizations with ggvis
  2. Data science for Doctors: Cluster Analysis Exercises
  3. iPlots exercises
  4. Explore all our (>1000) R exercises
  5. Find an R course using our R Course Finder directory

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