Coursera Google Data Analytics Professional Data Analysis with R Programming (Week 4) Quiz Answer-More about visualizations, aesthetics, and annotations.

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4.More about visualizations, aesthetics, and annotations.

Question 1

Which of the following are benefits of using ggplot2? Select all that apply.

• Combine data manipulation and visualization
• Automatically clean data before creating a plot
• Easily add layers to your plot
• Customize the look and feel of your plot

The benefits of using ggplot2 include easily adding layers to your plot, customizing the look and feel of your plot, combining data manipulation and visualization.

 

Question 2

In ggplot2, what symbol do you use to add layers to your plot?

• The equal sign (=)
• The plus sign (+)
• The ampersand symbol (&)
• The pipe operator (%>%)

In ggplot2, you use the plus sign (+) to add layers to your plot.

 

Question 3

A data analyst creates a plot using the following code chunk:

ggplot(data = penguins) + 
    geom_point(mapping = aes(x = flipper_length_mm, y = body_mass_g))

Which of the following represents a variable in the code chunk? Select all that apply.

• body_mass_g
• flipper_length_mm
• x
• y

The two variables in the code are flipper_length_mm and body_mass_g. The two variables are part of the penguins dataset. The aesthetic x maps the variable flipper_length_mm to the x-axis of the plot. The aesthetic y maps the variable body_mass_g to the y-axis of the plot.

 

Question 4

A data analyst uses the aes() function to define the connection between their data and the plots in their visualization. What argument is used to refer to matching up a specific variable in your data set with a specific aesthetic?

• Faceting
• Jittering
• Mapping
• Annotating

Mapping is an argument that matches up a specific variable in your data set with a specific aesthetic. You use the aes() function to define the mapping between your data and your plot.

 

Question 5

A data analyst is working with the penguins data. The analyst creates a scatterplot with the following code:

ggplot(data = penguins) + 
    geom_point(mapping = aes(x = flipper_length_mm, y = body_mass_g,alpha = species))

What does the alpha aesthetic do to the appearance of the points on the plot?

• Makes the points on the plot smaller
• Makes the points on the plot larger
• Makes some points on the plot more transparent
• Makes the points on the plot more colorful

The alpha aesthetic makes some points on a plot more transparent, or see-through, than others.

 

Question 6

You are working with the penguins dataset. You create a scatterplot with the following code chunk:

ggplot(data = penguins) + 
    geom_point(mapping = aes(x = flipper_length_mm, y = body_mass_g))

How do you change the second line of code to map the aesthetic size to the variable species?

• geom_point(mapping = aes(x = flipper_length_mm, y = body_mass_g, size + species))
• geom_point(mapping = aes(x = flipper_length_mm, y = body_mass_g, species = size)
• geom_point(mapping = aes(x = flipper_length_mm, y = body_mass_g, size = species))
• geom_point(mapping = aes(x = flipper_length_mm, y = body_mass_g, species + size)

You change the second line of code to geom_point(mapping = aes(x = flipper_length_mm, y = body_mass_g, size = species)) to map the aesthetic size to the variable species. Inside the parentheses of the aes() function, add a comma after y = body_mass_g to add a new aesthetic attribute, then write size = species to map the aesthetic size to the variable species. The data points for each of the three penguin species will now appear in different sizes.

 

Question 7

Fill in the blank: The _____ creates a scatterplot and then adds a small amount of random noise to each point in the plot to make the points easier to find.

• geom_point() function
• geom_bar() function
• geom_jitter() function
• geom_smooth() function

The geom_jitter() function creates a scatterplot and then adds a small amount of random noise to each point in the plot to make the points easier to find.

 

Question 8

You have created a plot based on data in the diamonds dataset. What code chunk can be added to your existing plot to create wrap around facets based on the variable color?

• facet(~color)
• facet_wrap(color)
• facet_wrap(~color)
• facet_wrap(color~)

The code chunk is facet_wrap(~color). Inside the parentheses of the facet_wrap() function, type a tilde symbol (~) followed by the name of the variable you want to facet.

 

Question 9

A data analyst uses the annotate() function to create a text label for a plot. Which attributes of the text can the analyst change by adding code to the argument of the annotate() function? Select all that apply.

• Change the color of the text
• Change the text into a title for the plot
• Change the size of the text
• Change the font style of the text

By adding code to the argument of the annotate() function, the analyst can change the font style, color, and size of the text.

 

Question 10

You are working with the penguins dataset. You create a scatterplot with the following lines of code:

ggplot(data = penguins) + 
    geom_point(mapping = aes(x = flipper_length_mm, y = body_mass_g)) + 

What code chunk do you add to the third line to save your plot as a jpeg file with "penguins" as the file name?

• ggsave(penguins)
• ggsave("penguins.jpeg")
• ggsave(penguins.jpeg)
• ggsave("jpeg.penguins")

You add the code chunk ggsave("penguins.jpeg") to save your plot as a jpeg file with "penguins" as the file name. Inside the parentheses of the ggsave() function, type a quotation mark followed by the file name (penguins), then a period, then the type of file (jpeg), then a closing quotation mark.

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