Exploratory analysis

Data Visualization, part 1. Code for quiz 7.

1. Load the R package that we will use.

library(tidyverse)

Question: Modify Slide 34

• Create a plot with 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 60.

ggplot(faithful) + 
  geom_point(aes(x = eruptions, y = waiting, colour = eruptions < 60))

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Question: Modify Slide 35

• Create a plot with 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 color dodgerblue to all points

ggplot(faithful) + 
  geom_point(aes(x = eruptions, y = waiting),
             colour = 'dodgerblue')

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Question: Modify Slide 36

• Create a plot with 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))

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Question: Modify geom-ex-1

• 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)

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Question: Modify geom-ex-2

• Create a plot with faithful dataset

• Use geom_histogram() to plot distribution of the eruptions (time)

• Fill in the histogram based on whether eruptions are greater than or less than 3.2

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

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Question: Modify stat-slide-40

• Create plot with mpg dataset

• Add geom_bar() to create a bar chart of the variable manufacturer

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

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Question: Modify stat-slide-41

• Change code count and 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')

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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))))

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Question: Modify stat-ex-2

• Use stat_summary() to add a dot at the median of each group

• Color the dot dodgerblue

• Make the shape of the dot plus

• Make the dot size 2

ggplot(mpg) + 
  geom_jitter(aes(x = class, y = hwy), width = 0.2) +
  stat_summary(aes(x = class, y = hwy), geom = "point",
               fun = "median", color = "dodgerblue", shape = "plus", size = 2)

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ggsave(filename = "preview.png",
       path = here::here("_posts", "2022-03-11-exploratory-analysis"))