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 you have watched the videos had worked through exercises in exercises_slides-1-49.Rmd.

3. 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 preveiw.

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 58

ggplot(faithful)+
  geom_point(aes(x=eruptions,y=waiting,
        colour=waiting>58))

Question: modify intro slide 35

• Create a plot with the faithful dataset

• Add points with the geom_point

  • assign the variable eruptions to the x-axis

  • assign the variable waiting to the y-axis

  • assign the colour purple to all the points

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

Questions: modify into-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: 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 y-axis

  • set the shape of the points to cross

  • set the point size to 7

  • set the point transparency 0.6

ggplot(faithful) + 
   geom_point(aes(x = eruptions, y = waiting), 
   shape = "cross", size = 7, alpha =0.6)

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: modufy stat-slide-41

• change the 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 state-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 answers to stat-ex-2

• For reference see examples: https://ggplot2.tidyverse.org/reference/stat_summary.html?q=stat%20_%20summary#examples

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

• 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 )

• 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.

ggsave(filename = "preview.png", 
       path = here::here("_posts", "2021-03-29-exploratory-analysis"))