Part 1 Exercise 1 Solution: Mastering the geoms

Exercise 1.1: Scatterplot

ggplot(crampton.pig, aes(weight1, weight2, color = treatment, size = feed)) + 
  geom_point()

Exercise 1.2: Tile plot

ggplot(crampton.pig, aes(rep, treatment, fill = weight2 - weight1)) + 
  geom_tile(color = "black", size = 2)

Exercise 1.3: Density plot

ggplot(crampton.pig, aes(weight2 - weight1, fill = treatment)) + 
  geom_density(alpha = 0.7) 

Exercise 1.4: Grouped barplot

ggplot(crampton.pig, aes(treatment, feed, fill = rep)) + 
  geom_col(position = "dodge")

Exercise 1.5: Rose plot

ggplot(crampton.pig, aes(treatment, feed, fill = rep)) + 
  geom_col(position = "dodge") + coord_polar("x")

Exercise 1.6: Boxplot

ggplot(heart2, aes(heart_disease, obesity, fill = family_history)) + 
  geom_boxplot()

Exercise 1.7: Dotplot

ggplot(heart2, aes(heart_disease, obesity, fill = family_history)) + 
  geom_dotplot(binaxis = "y", stackdir = "center",
               position = "dodge")

## Bin width defaults to 1/30 of the range of the data. Pick better value with `binwidth`.

Exercise 1.8: Violin plot

ggplot(heart2, aes(heart_disease, obesity, fill = family_history)) + 
  geom_violin()

Exercise 1.9: 2D density plot

ggplot(heart2, aes(age, obesity)) + 
  geom_density_2d_filled()

Exercise 1.10: Hexagonal heatmap

ggplot(heart2, aes(age, obesity)) + 
  geom_hex()