Exploratory analysis

Data visualization, Part 1. Code for Quiz 7.

1. Load the R package we will use.

library(tidyverse)

2. Quiz questions

• Replace all the ???s. These are answers on your moodle quiz.
• Run all the individual code chunks to make sure the answers in this file correspond with your quiz answers
• After you check all your code chunks run then you can knit it. It won’t knit until the ??? are replaced
• The quiz assumes that you have watched the videos, downloaded (to your examples folder) and worked through the exercises in exercises_slides-1-49.Rmd
• Pick one of your plots to save as your preview plot. Use the ggsave command at the end of the chunk of the plot that you want to preview.

Question: modify slide 34

• Create a plot with the faithful dataset
• add points with geom_point
  • assign the variable eruptions to the x-axis
  • assign the variable waiting to the y-axis
  • colour the points according to whether waiting is smaller or greater than 81

ggplot(faithful) + 
   geom_point(aes(x = eruptions, y = waiting, 
                  colour = waiting > 81))   

ggsave(filename = "preview.png", 
       path = here::here("_posts", "2022-03-14-exploratory-analysis"))

---

Modify intro-slide 35

• Create a plot with the faithful dataset
• add points with geom_point
  • assign the variable eruptions to the x-axis
  • assign the variable waiting to the y-axis
  • assign the colour blue to all the points

ggplot(faithful) + 
   geom_point(aes(x = eruptions, y = waiting),
              colour = "blue") 

---

Question: modify intro-slide 36

• Create a plot with the faithful dataset
• use geom_histogram() to plot the distribution of waiting time
  • assign the variable waiting to the x-axis

ggplot(faithful) +
  geom_histogram(aes(x = waiting))

---

Question: modify geom-ex-1

• See how shapes and sizes of points can be specified here
• Create a plot with the faithful dataset
• add points with geom_point
  • assign the variable eruptions to the x-axis
  • assign the variable waiting to the y-axis
  • set the shape of the points to asterisk
  • set the point size to 8
  • set the point transparency 0.7

ggplot(faithful) + 
   geom_point(aes(x = eruptions, y = waiting), 
   shape = "asterisk", size = 8, alpha = 0.7)   

---

Question: modify geom-ex-2

• Create a plot with the faithful dataset
• use geom_histogram() to plot the distribution of the eruptions (time)
• fill in the histogram based on whether eruptions are greater than or less than 3.2 minutes

ggplot(faithful) + 
   geom_histogram(aes(x = eruptions, fill = eruptions > 3.2))

---

Question: modify stat-slide-40

• Create a plot with the mpg dataset
• add geom_bar() to create a bar chart of the variable manufacturer

ggplot(mpg) +
  geom_bar(aes(x = manufacturer))

---

Question: modify stat-slide-41

• change code to count and to plot the variable manufacturer instead of class

mpg_counted <- mpg %>% 
  count(manufacturer, name = 'count')
ggplot(mpg_counted) + 
  geom_bar(aes(x = manufacturer, y = count), stat = 'identity')

---

Question: modify stat-slide-43

• change code to plot bar chart of each manufacturer as a percent of total
• change class to manufacturer

ggplot(mpg) + 
  geom_bar(aes(x = manufacturer, y = after_stat(100 * count / sum(count))))

---

Question: modify answer to stat-ex-2

• For reference see examples.
• Use stat_summary() to add a dot at the median of each group
• color the dot purple
• make the shape of the dot plus
• make the dot size 3

ggplot(mpg) + 
  geom_jitter(aes(x = class, y = hwy), width = 0.2) +
  stat_summary(aes(x = class, y = hwy), geom = "point", 
  fun = "median", color = "purple", 
  shape = "plus", size = 3)