Exporatory analysis

Data visualization, part 1. Code for Quiz 7.

  1. Load the R package we will use
  1. Quiz Questions

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

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


Question: modify intro-slide 35

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


Question: modify intro-slide 36

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


Question: modify modify geom-ex-1

-See how shapes and sizes of points can be specified here

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


Question: modify geom-ex-2

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


Question: modify stat-slide-40

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


Question: modify stat-slide-41

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

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 = "diamond", size = 4 )