Plotting

Learning outcomes

• Comfortable with the first chapter of R for Data Science
• Can use ggplot2 for simple plots
• Can create simple ggplots from tidy data
• Can use some ggplot aesthetics
• Can use some ggplot geometrical objects

For teachers

Teaching goals are:

• Learners have read part of the first chapter of R for Data Science
• Learners have created simple plots in ggplot2
• Learners can create simple ggplots from tidy data
• Learners can set the aesthetics x, y and color
• Learners can use geom_scatter, geom_boxplot and geom_smooth for simple aesthetics

Prior question:

• What is the most used use R package for plotting?
• What is gg in ggplot2?
• What is tidy data?
• There is a philosophy that 'missing values should never silently go missing'. What does that mean?

Feedback questions:

• What is gg in ggplot2?
• What is tidy data?
• What is an aesthetic?
• What is a geom?
• The philosophy that 'missing values should never silently go missing'. What does this mean?

Why ggplot2 is important

ggplot2 allows you to create publication-quality graphs for your paper, using a unified (and extensible) grammar, which allows you to express your unique plotting needs.

Exercises

Exercise 1

• Read R for data science, chapter 1 until the exercises of 1.2.5
• Do these exercises

Answers

See the answers here

Note that the answers use chapter 2.2.5.

(optional) Exercise 2

• Read R for data science, chapter 1 until the exercises of 1.4.3.
• Do these exercises

Answers

See the answers here

Note that the answers use chapter 2.4.3.

(optional) Exercise 3

• Read R for data science, chapter 1 until the exercises of 1.5.5
• Do these exercises

Answers

See the answers here

Note that the answers use chapter 2.5.5.

(optional) Exercise 4

• Read R for data science, chapter 1 until the exercises of 1.6.1
• Do these exercises

Answers

See the answers here

Note that the answers use chapter 2.6.1.