Based on suggestions by @Sven Hohenstein, @Roland and @lukeA I have solved the problem for displaying multiple boxplots in expanded form without outliers.
First plot the box plots without outliers by using outlier.colour=NA
in geom_boxplot()
plt_wool <- ggplot(subset(df_mlt, value > 0), aes(x=ID1,y=value)) +
geom_boxplot(aes(color=factor(ID1)),outlier.colour = NA) +
scale_y_log10(breaks = trans_breaks("log10", function(x) 10^x), labels = trans_format("log10", math_format(10^.x))) +
theme_bw() +
theme(legend.text=element_text(size=14), legend.title=element_text(size=14))+
theme(axis.text=element_text(size=20)) +
theme(axis.title=element_text(size=20,face="bold")) +
labs(x = "x", y = "y",colour="legend" ) +
annotation_logticks(sides = "rl") +
theme(panel.grid.minor = element_blank()) +
guides(title.hjust=0.5) +
theme(plot.margin=unit(c(0,1,0,0),"mm"))
Then compute the lower, upper whiskers using boxplot.stats()
as the code below. Since I only take into account positive values, I choose them using the condition in the subset()
.
yp <- subset(df, x>0) # Choosing only +ve values in col x
sts <- boxplot.stats(yp$x)$stats # Compute lower and upper whisker limits
Now to achieve full expanded view of the multiple boxplots, it is useful to modify the y-axis limit of the plot inside coord_cartesian()
function as below,
p1 = plt_wool + coord_cartesian(ylim = c(sts[2]/2,max(sts)*1.05))
Note: The limits of y should be adjusted according to the specific case. In this case I have chosen half of lower whisker limit for ymin.
The resulting plot is below,