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    <p>Using the <strong>grid</strong> package, we can have someting like this:</p> <p><img src="https://i.stack.imgur.com/HaAHg.png" alt="enter image description here"></p> <pre><code>mylabd &lt;- data.frame (company = rep(c("A", "B", "C"), each = 7), skillsDg = rep(c("Basic", "HighSc", "Undgd", "MAST", "PHD", "EXPD", "EXECT"), 3), number = c(200, 100, 40, 30, 10, 0, 0, 220, 110, 35, 10, 0, 4, 1, 140, 80, 120, 50, 52, 52, 3) ) ## to comapre we need o have the same scales for all organizations nskills &lt;- nlevels(mylabd$skillsDg) ncompany &lt;- nlevels(mylabd$company) barYscale &lt;- c(0, nskills) * 1.05 barXscale &lt;- c(0, max(mylabd$number) )* 1.05 ## the global scene vp &lt;- plotViewport(c(5, 4, 4, 1), yscale = barYscale, layout = grid.layout(nrow=1,ncol=nbars)) pushViewport(vp) grid.rect() grid.yaxis(at=c(1:nlevels(mylabd$skillsDg)),label=unique(mylabd$skillsDg)) grid.grill() ## split data by companya data.splitted &lt;- split(mylabd,f=mylabd$company) lapply(1:3,function(company){ x &lt;- data.splitted[[company]] vv &lt;- x$number companyName &lt;- unique(x$company) pushViewport(viewport(layout.pos.col=company, xscale = barXscale, yscale = barYscale)) grid.rect() # grid.xaxis(at= mean(x$number),label = companyName) grid.xaxis() grid.polygon(x = unit.c(unit(0.5,'npc')-unit(vv/2,'native'), unit(0.5,'npc')+unit(rev(vv)/2,'native')), y = unit.c(unit(1:nmeasures,'native'), unit(rev(1:nmeasures),'native')), gp=gpar(fill = rainbow(nmeasures)[company])) grid.polygon(x = unit.c(unit(0.5,'npc')-unit(vv/2,'native'), unit(0.5,'npc')+unit(rev(vv)/2,'native')), y = unit.c(unit(1:nmeasures,'native'), unit(rev(1:nmeasures),'native')), id = c(1:nmeasures,rev(1:nmeasures)), gp=gpar(fill = NA)) grid.text( x = unit(0.5,'npc'), y = unit(0.5,'native'), label = unique(x$company)) popViewport() }) popViewport() </code></pre>
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