grammar of graphics – Learning | Assessment

Data Visualization in R Using ggplot2 - Module 2

library(ggplot2)
data(PlantGrowth) 
data(airquality)

ggplot(data = PlantGrowth,                  # data              
       aes(y = weight)) +                         # aesthetics
  geom_boxplot() +                               # geometry
  facet_wrap(~ group) +                       # facets
  stat_summary(aes(x = 0),                  # statistics
               fun = mean,
               geom = "point",
               color = "red",
               size = 3) +
  coord_flip() +                                      # coordinates
  theme_bw()                                        # theme

Exercises

Below are the exercises for this module.

Install and load the ggplot2 package.
Load the airquality data set using the data() function.
Draw an empty plot using the ggplot() function, only specifying the data argument with the airquality data set.
Specify the aes() function within the ggplot() function so that y = Temp, and add a geom_boxplot() layer to draw a boxplot.
Create a facet boxplot for the Temp column, grouped by the Month column using the facet_wrap() function. How does the temperature distribution vary by month?
Apply the theme_light() to the facet boxplot you created in the previous exercise.

library(ggplot2)
ggplot(data = airquality,
  aes(y = Temp)) +
  geom_boxplot() +
  facet_wrap(~ Month) +
  theme_light()