Ignore outliers in ggplot2 boxplot + faceting + "free" options
boxplot, facet, ggplot2, outliers, r
Solution
It obviously depends on what you consider an outlier. If it's possible for you to calculate it, you can set your `ylim` at this value an let those points out of the chart.
For example, if you assume that the upper and lower limits are Q3 + 1.5 IQR and Q1 - 1.5 IQR, and this is the way boxplots usually have its outliers limit calculated, you would have:
upper.fence <- quantile(x)[4] + 1.5*IQR(x)
lower.fence <- quantile(x)[2] - 1.5*IQR(x)
Then you can use these limits as the `y` range of values:
my.ggplot + coord_cartesian(ylim=c(lower.fence, upper.fence))
The procedure you use to get your upper and lower limits can change, but the use of the limits is the same.
Problem
How can I adjust my Y axis in order to ignore outliers, like in this post, but in a more challenging case where I have 4 boxplots and a "free faceting" layout? p <- ggplot(molten.DF,aes(x=class,y=SOC,fill=class)) + geom_boxplot() + facet_grid(layer~.,scales="free",space="free") As you can see on my figure, considering outliers in the Y axis range make the boxes more difficult to read. No importance if some outliers are still visible in the result, but I would like to really focus on the boxes!