Exploratory analysis

Data visualization, part 1. Code for Quiz 7.

  1. Load the R package we will use.
  1. Quiz questions
  1. 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 **64**
ggplot(faithful) + 
  geom_point(aes(x = eruptions, y = waiting, colour = eruptions < 64))


Question: modify intro-slide 35

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


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 diamond
set the point size to 5
set the point transparency 0.9
ggplot(faithful) + 
  geom_point(aes(x = eruptions, y = waiting))


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

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 )