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Warming up data-wrangling

Let's warm up your tidyverse data wrangling skills a bit and look at the number of cases reported by year for the American region ('AMR').

To do this, we will first filter the dataset to our desired region, then make a simple scatter plot of the year by cases.

In addition, set the opacity of the points to 50% (0.5) so we can get a sense of data overlap.

This exercise is part of the course

Visualization Best Practices in R

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Exercise instructions

  • Filter who_disease so we just only keep data from the 'AMR' region.
  • Modify the aesthetics in the data to map the year to the x-axis, and cases to the y-axis.
  • Lower the opacity (alpha) of the points to 0.5 to get a sense of overlap in geom_point()

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# filter data to AMR region. 
amr_region <- who_disease %>%
    ___(___)

# map x to year and y to cases. 
ggplot(amr_region, aes(___)) + 
	# lower alpha to 0.5 to see overlap.   
  	geom_point(___)
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