Fiddling with a violin plot

The supplied code makes a simple violin plot of the same comparison we've been looking at.

Much like with geom_density(), ggplot has given us an unfilled (or at least white) shape. To make this more aesthetically pleasing, set the fill to 'steelblue'. Set the kernel SD to an intuitively reasonable value and make sure to state this kernel width in the subtitle of the plot.

In addition, let's attempt to replicate the rain-cloud plots from the density lesson and add (non-jittered) points back to the plot over the violins to attempt to see where interpolation is happening. Do this by simply adding a geom_point() geometry and setting the color to 'white', the alpha to 0.3 to show overlap, and the size to 0.5 to keep the points as unobtrusive as possible.

This exercise is part of the course

Visualization Best Practices in R

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Exercise instructions

Swap geom_beeswarm() with geom_violin().
Set the kernel width (bw) of the violin plot to 2.5.
Add individual points underneath with geom_point().
Style individual points with alpha = 0.3, size = 0.5.

Hands-on interactive exercise

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

md_speeding %>% 
    filter(vehicle_color == 'RED') %>%
    ggplot(aes(x = gender, y = speed)) + 
    # Replace beeswarm geometry with a violin geometry with kernel width of 2.5
    geom_beeswarm(cex = 0.5, alpha = 0.7) +
    # add individual points on top of violins
    ___

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