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R for Data Science Coordinate Systems Exercises

Nov 13, 2023

From R for Data Science

Coordinate Systems

1-Turn a stacked bar chart into a pie chart using coord_polar().

bar_mpg <- ggplot(mpg) +
  geom_bar(aes(x = class, fill = class)) 

bar_mpg + coord_polar()

2-What’s the difference between coord_quickmap() and coord_map()?

coord_map() projects a portion of the earth, which is approximately spherical, onto a flat 2D plane using any projection defined by the mapproj package. Map projections do not, in general, preserve straight lines, so this requires considerable computation. coord_quickmap() is a quick approximation that does preserve straight lines. It works best for smaller areas closer to the equator.

3-What does the following plot tell you about the relationship between city and highway mpg? Why is coord_fixed() important? What does geom_abline() do?

ggplot(data = mpg, mapping = aes(x = cty, y = hwy)) +
  geom_point() + 
  geom_abline() +
  coord_fixed()

coord_fixed() is a fixed scale coordinate system that forces a specified ration between the physical representation of data units on the axes. It is important because it ensures that one unit on the x-axis is teh same lenght as one unit on the y-axis, and makes ratios higher than one longer on the y axis than units on the x-axis and vice versa also.

geom_abline() adds a reference line that is diagonal (specified by slope and intercept). It is useful for annotating plots.