Exploratory analysis

Data visualization, part 1. Code for Quiz 7.

1. Load the R packages 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_slides-1-49(1).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
  • color the points according to whether waiting is smaller or greater than 77

ggplot(faithful) +
  geom_point(aes(x = eruptions, y = waiting,
          colour = waiting > 77))

Question: Modify intro-slide 35

• Create a plot with the faithful dataset
• Add point with `geom_point
  • assign the variable eruptions to the x-axis
  • assign the variable waiting to the y-axis
  • assign the colour darkorange to all the points

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

Question: Modify intro-slide 36

• Create a plot with the faithful dataset
• Use geom_histogram() to plot the distribution 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: https://ggplot2.tidyverse.org/articles/ggplot2-specs.html#sec:shape-spec
• 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 square
  • set the point size to 5
  • set the point transparency 0.5

ggplot(faithful) +
  geom_point(aes(x = eruptions, y = waiting),
             shape = "square", size = 5, alpha = 0.5)

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 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 https://ggplot2.tidyverse.org/reference/stat_summary.html?q=stat%20_%20summary#examples
• Use stat_summary() to add a dot at the median of each group
• Color the dot purple3
• Make the shape of the dot square
• Make the dot size 8

ggplot(mpg) +
  geom_jitter(aes(x = class, y = hwy), width = 0.2) +
  stat_summary(aes(x = class, y = hwy), geom = "point",
               fun = "median", color = "purple3",
               shape = "square", size = 8 )

ggsave(filename = "preview.png",
       path = here::here("_posts", "2022-03-18-exploratory-analysis"))