1. Learn
    2. /
  2. Courses
    3. /
  3. Dealing With Missing Data in R

Exercise

Create histogram of imputed data

Now that we can recreate the first visualization of geom_miss_point(), let's explore how we can apply this to other exploratory tasks.

One useful task is to evaluate the number of missings in a given variable using a histogram. We can do this using the ocean_imp_track dataset we created in the last exercise, which is loaded into this session.

Instructions

100 XP

Using the imputed and tracked data, ocean_imp_track:

  • Explore the values of air_temp_c, visualizing the amount of missings with air_temp_c_NA.
  • Explore the missings in humidity using humidity_NA.
  • Explore the missings in air_temp_c according to year, using facet_wrap(~year).
  • explore the missings in humidity according to year, using facet_wrap(~year).