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See ?stat_summary. <blockquote> fun.data : Complete summary function. Should take data frame as input and return data frame as output </blockquote> Your function <code>max.n.filt</code> uses an <code>if()</code> statement that tries to evaluate the condition <code>x > filter</code>. But when <code>length(x) > 1</code>, the <code>if()</code> statement only evaluates the condition for the first value of <code>x</code>. When used on a data frame, this will return a list cobbled together from the original input <code>x</code> and whatever label the <code>if()</code> statement returns. <pre><code>> max.n.filt(data.frame(x=c(10,15,400))) $y.x [1] 10 15 400 $label [1] "" </code></pre> Try a function that uses <code>ifelse()</code> instead: <pre><code>max.n.filt2 <- function(x){ filter = 300 # whatever threshold y = ifelse( x > filter, max(x) + 1, x[,1] ) label = ifelse( x > filter, round(max(x),2), NA ) return(data.frame(y=y[,1], label=label[,1])) } > max.n.filt2(data.frame(x=c(10,15,400))) y label 1 10 NA 2 15 NA 3 401 400 </code></pre> Alternatively, you might just find it easier to use <code>geom_text()</code>. I can't reproduce your example, but here's a simulated dataset: <pre><code>set.seed(101) sim_data <- expand.grid(m1=1:1440, variable=factor(c(0,0.25,0.5,0.75,1))) sim_data$sample_size <- sapply(1:1440, function(.) sample(1:25, 1, replace=T)) sim_data$value = t(sapply(1:1440, function(.) quantile(rgamma(sim_data$sample_size, 0.9, 0.5),c(0,0.25,0.5,0.75,1))))[1:(1440*5)] </code></pre> Just use the <code>subset</code> argument in <code>geom_text()</code> to select those points you wish to label: <pre><code>ggplot(sim_data, aes(x = m1/60, y = value, color = variable)) + geom_point(size = 4) + geom_text(aes(label=round(value)), subset = .(variable == 1 & value > 25), angle = 90, size = 4, colour = "red", hjust = -0.5) </code></pre> If you have a column of sample sizes, those can be incorporated into <code>label</code> with <code>paste()</code>: <pre><code>ggplot(sim_data, aes(x = m1/60, y = value, color = variable)) + geom_point(size = 4) + geom_text(aes(label=paste(round(value),", N=",sample_size)), subset = .(variable == 1 & value > 25), angle = 90, size = 4, colour = "red", hjust = -0.25) </code></pre> (or create a separate column in your data with whatever labels you want.) If you're asking about how to retrieve the sample sizes, you could modify your call to <code>ddply()</code> like this: <pre><code>... c2 <- ddply(C, .(h1), function (x) { cbind(summarise(x, y = quantile(x$gaps, cuts)), n=nrow(x)) } ) c2$cuts <- cuts c2 <- dcast(c2, h1 + n ~ cuts, value.var = "y") c2.h1.melt <- melt(c2, id.vars = c("h1","n")) ... </code></pre>
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