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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.
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.
- 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:
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