title: How plot results from a pairwise.wilcox.test?
body: <p>I would like to plot a bubble/circle plot of p.values generated from pairwise comparisons. The goal is to be able to visually identify which comparisons are significant p &lt; .05</p>
  
  <p>For example like the one generated from corrplot.  The issue I think its because the table that it generates is not complete in that it lacks the full.  For example for a comparison for May-Sept the table looks like this.  Here is is my attempt to plot this with corrplot?</p>
  
  <pre><code> library ( corrplot)
      attach(airquality)
      Month &lt;- factor(Month, labels = month.abb[5:9])
      ## These give warnings because of ties :
  
      test = pairwise.wilcox.test(Ozone, Month, p.adj = "bonf")
      detach()
  
      corrplot(as.matrix (test$p.value), 
  p.mat = as.matrix (test$p.value) ,  is.corr = FALSE, method = "circle", mar = c(1, 1, 2, 0) )
  </code></pre>
  
  <p>The table the pairwise generate looks like this. </p>
  
  <pre><code>&gt; test$p.value
              May       Jun         Jul        Aug
  Jun 1.000000000        NA          NA         NA
  Jul 0.000299639 0.1413625          NA         NA
  Aug 0.001208078 0.2590776 1.000000000         NA
  Sep 1.000000000 1.0000000 0.007442604 0.03247955
  </code></pre>
  
  <p>is there a way to plot this similar to corrplot? Or any other way to show only significant comparison would be great. </p>
  
  <p>thanks! </p>