Lab 2: Data visualization

Not graded, just practice

Practice your new ggplot skills with these practice exam questions! Best to open a fresh Google Colab notebook and test things out! Refer to the study guide to find answers as well.

Tip

More than one answer may be correct!

Materials from lab

• Brittany’s materials
• Wesley’s materials

1 Setup

We will continue working with the ratings dataset from the visualization lecture (part of the languageR package).

library(ggplot2)
library(languageR)

It contains the following variables:

str(ratings)

'data.frame':   81 obs. of  14 variables:
 $ Word            : Factor w/ 81 levels "almond","ant",..: 1 2 3 4 5 6 7 8 9 10 ...
 $ Frequency       : num  4.2 5.35 6.3 3.83 3.66 ...
 $ FamilySize      : num  0 1.39 1.1 0 0 ...
 $ SynsetCount     : num  1.1 1.1 1.1 1.39 1.1 ...
 $ Length          : int  6 3 5 7 9 7 6 6 3 6 ...
 $ Class           : Factor w/ 2 levels "animal","plant": 2 1 2 2 2 2 1 2 1 1 ...
 $ FreqSingular    : int  24 69 315 26 19 24 53 74 155 37 ...
 $ FreqPlural      : int  42 140 231 19 19 6 78 77 103 14 ...
 $ DerivEntropy    : num  0 0.562 0.496 0 0 ...
 $ Complex         : Factor w/ 2 levels "complex","simplex": 2 2 2 2 2 2 2 2 2 2 ...
 $ rInfl           : num  -0.542 -0.7 0.309 0.3 0 ...
 $ meanWeightRating: num  1.49 3.35 2.19 1.32 1.44 ...
 $ meanSizeRating  : num  1.89 3.63 2.47 1.76 1.87 ...
 $ meanFamiliarity : num  3.72 3.6 5.84 4.4 3.68 4.12 2.12 5.68 3.2 2.2 ...

2 Data viz day 1

1. Fill in the blanks below with one of the following words: data, aesthetics, geom.

   The basic ggplot involves: (1) using your , (2) defining how variables are mapped to visual properties (), and (3) determining the geometrical object that a plot uses to represent data ()

2. When ggplot2 maps a categorical variable to an aesthetic, it automatically assigns a unique value of the aesthetic to each level of the variable. What is this process called?

   level assignment variable aestheticization autofill scaling

3. The code below generated which of the following figures?

   ggplot(
       data = ratings,
       mapping = aes(x = Frequency, y = meanFamiliarity)
   ) + 
       geom_point(mapping = aes(color = Class)) +
       geom_smooth(method = "lm") +
       theme_classic(base_size=20)

   

   A B C

4. Suppose we want to map the variable Complex to the color aesthetic in a scatterplot. Which of the following arguments could we pass to geom_point()?

   color = Complex mapping=aes(color = Complex) color = mapping(Complex) aes(color=Complex)

5. To adjust the size of the font to 20pt in the complete theme theme_minimal(), what argument should we include?

   base_size=20 size=20 font_family_size=20 None of the above

6. Which geoms are depicted in the following figure?

   

   geom_histogram() geom_density() geom_bar() geom_smooth() geom_point()

7. Which geoms are depicted in the following figure?

   

   geom_histogram() geom_density() geom_bar() geom_smooth() geom_point()

3 Data viz day 2

3.1 Plot 1

Given code blocks a, b, and c; and the plot below:

# CODE BLOCK a ---------------------------#
ggplot(
    data = ratings, 
    mapping = aes(x = Frequency, y = meanFamiliarity)
    ) +
    geom_point(color = "blue")

# CODE BLOCK b ---------------------------#
ggplot(
    data = ratings, 
    mapping = aes(x = Frequency, y = meanFamiliarity, color = "blue")
    ) 

# CODE BLOCK c ---------------------------#
ggplot(
    data = ratings, 
    mapping = aes(x = Frequency, y = meanFamiliarity)
    ) +
    geom_point()

1. Which of the code blocks above generate the plot ?

   a b c

2. In the plot above, is the color aesthetic mapped, set, or both?

   mapped set both

3. In the plot above, which of the following aesthetics should we set to make the points more transparent?

   color fill alpha shape

4. In plot A above, which of the following would change the x axis label to “FQ”?

   add a labs() layer with x="FQ" argument add a labs() layer with y="FQ" argument change the mapping argument from x="Frequency" to x="FQ"

3.2 Plot 2

Given the following plot:

1. In the plot above, which geom(s) are used to represent the data?

   geom_histogram() geom_density() geom_bar() geom_point() geom_smooth()

2. True or false, the blue line in the plot above is mapped to the Class aesthetic?

   True False

3. In the plot above, which of the following variables is mapped to the x aesthetic?

   Frequency meanFamiliarity FreqSingular FreqPlural

4. True or false, in the plot above, the default statistical transformation in the geom responsible for the red dots is “identity”.

   True False

3.3 Code block 1

Suppose we run the following code.

ggplot(
    data = ratings, 
    mapping = aes(x = Frequency, y = meanFamiliarity, color = Class)
    ) +
    geom_point() +
    geom_smooth(method = "lm", color = "red") 

1. Which of the following plots will be returned?

   A B

2. Which aesthetic is mapped and which is set?

   Class is set to color and the smoothing line is mapped to red Class is mapped to color and the smoothing line is set to red Both are mapped Both are set

3. Which aesthetic is global and which is local?

   Color is mapped to the class variable globally, and set to red locally Color is mapped to the class variable locally, and set to red globally Both are global Both are local

3.4 Code block 2

Suppose we run the following code block

ggplot(
    data = ratings, 
    mapping = aes(x = Class, fill = Complex)
    ) +
    geom_bar() 

1. Which plot will be returned?

   A B C D

2. What would happen if we added the layer scale_fill_manual(values = c("green", "orange")) to the following plot?

   error: no fill aesthetic specified complex would turn green and simplex would turn orange simplex would turn green and complex would turn orange No change

3. What argument could we add to geom_bar() to add a black border around the bars?

   fill = black border_color = 'black' linetype = 'black' color = 'black'

3.5 Plot 3

Consider the following plot

1. To generate the facets in the plot above, which of the following lines of code must be included?

   facet_grid(Complex ~ Class) facet_grid(Class ~ Complex) facet_grid(.~ Complex) facet_wrap(Class~Complex, ncol = 2)

2. Which of the following geoms are added to the plot above?

   geom_histogram() geom_density() geom_bar() geom_smooth() geom_point()

3. Which built-in theme is applied to the following plot?

   theme_grey() theme_classic() theme_void() theme_bw()