MATH 208 Final Exam Question 3 [50 points]

The goal of this question is to write functions to help to simplify our exploratory data analyses. The data for this question will come from the palmerpenguins library that we have used before in quizzes and assignments.

library(palmerpenguins) # make sure it is installed first


data(penguins)

head(penguins)

    • A tibble: 6 x 8

species island bill_length_mm bill_depth_mm flipper_length_~ body_mass_g sex

<fct>
<fct>
<dbl>
<dbl>
<int>
<int>
<fct>
1
Adelie
Torge~
39.1
18.7
181
3750
male
2
Adelie
Torge~
39.5
17.4
186
3800
fema~
3
Adelie
Torge~
40.3
18
195
3250
fema~
4
Adelie
Torge~
NA
NA
NA
NA
NA
5
Adelie
Torge~
36.7
19.3
193
3450
fema~
6
Adelie
Torge~
39.3
20.6
190
3650
male
# ... with 1 more variable: year <int>

To save reading space and time, you can refresh your memory for this data by entering help(penguins) in the console.

For this question, we will assume that someone ultimately wants to write a set of functions that will allow them to create scatterplots of all possible combinations of two quantitative variables with a single line of code. The different parts below will allow to create some useful functions to build up to that goal with some different ways to implement them. Please be sure to read carefully to understand each part.

    (a) [20 pts] The core function that we need to create is a function that takes in one argument which is a tibble object and two character string arguments (i.e. two single element character vectors) which indicate which variables from the tibble should be plotted against each other and returns a ggplot object. If either of the two character string arguments do not match names of columns of the tibble, your function should return an error message.

For example, if the tibble argument is penguins and the two character string arguments are x_var="bill_length_mm"

and y_var="body_mass_g", then calling the function would yield:

one_plot_fun(input_data=as_tibble(penguins),x_var="bill_length_mm",y_var="body_mass_g")









body_mass_g



6000




5000




4000




3000



40    50    60

bill_length_mm

But if we give it foot_length_mm, then it should return:

one_plot_fun(input_data=as_tibble(penguins),x_var="foot_length_mm",y_var="body_mass_g")





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MATH 208 Final Exam    December 18th – 21st, 2021



[1] "At least one variable not contained in input_data"

Hint: You will need to use aes_string instead of aes to set the aesthetics for your scatterplot. Recall the %in% operator allows you to check to see if elements of one vector are contained in another. For example,

a<-LETTERS[1:10]


b<-c("Z","C")

b %in% a

[1] FALSE    TRUE



























































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MATH 208 Final Exam    December 18th – 21st, 2021



    (b) [30 pts] Now using your function from part (a), write a function that takes two arguments, the input data tibble and a character string vector that contains variable names from the tibble that you want to be plotted against each other, and returns a list containing scatterplots of all possible combinations of variables, excluding plots where both the x and y axis variables are the same. Your function should use a for() loop (or multiple for loops) to generate plots for all possible combinations of variables in the character string vector. If either of the pairs of values from the character vector do not correspond to columns in the tibble, the element of the list should just contain the error message from part (a). Here is an example of running your function for the penguins data:

my_obj<-many_plots_fun(penguins,c("bill_length_mm","body_mass_g","flipper_length_mm"))


str(my_obj,max.level=1)

List of 6

$ :List of 9

..- attr(*,

    • :List of 9

..- attr(*,

    • :List of 9

..- attr(*,

$ :List of 9 ..- attr(*,

    • :List of 9

..- attr(*,

    • :List of 9

..- attr(*,



"class")= chr [1:2] "gg" "ggplot"

"class")= chr [1:2] "gg" "ggplot"

"class")= chr [1:2] "gg" "ggplot"

"class")= chr [1:2] "gg" "ggplot"

"class")= chr [1:2] "gg" "ggplot"

"class")= chr [1:2] "gg" "ggplot"

gridExtra::marrangeGrob(my_obj,nrow=3,ncol=2)



body_mass_g




page 1 of 1



6000


mm
230



4000


length
220







190



5000



210






flipper
200



40
50
60

3000
4000
5000
6000
3000



180







170













bill_length_mm

body_mass_g
flipper_length_mm

230

220

210

200

190

180

170

40

bill_length_mm

50    60

60


50


40


170    180    190    200    210    220    230

bill_length_mm

flipper_length_mm

bill_length_mm

60


50


40


3000    4000

body_mass_g

5000    6000

6000


5000


4000


3000


170    180    190    200    210    220    230

body_mass_g    flipper_length_mm

END OF QUESTION 3




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