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.
Diese Übung ist Teil des Kurses
Visualization Best Practices in R
Anleitung zur Übung
- 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, andcases
to the y-axis. - Lower the opacity (
alpha
) of the points to0.5
to get a sense of overlap ingeom_point()
Interaktive Übung
Vervollständige den Beispielcode, um diese Übung erfolgreich abzuschließen.
# 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(___)