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    <p>Is this what you want?</p> <pre><code>library(ggplot2) library(plyr) library(gridExtra) # create data that links colour per 'cat' with 'fishery' # the 'cat' colours will be used as manually set fill colours. # get 'cat' colours # alt. 1: grab 'cat' colours from plot object # create a plot with fill = fishery *and* colour = cat g1 &lt;- ggplot(df, aes(x = year, y = TOTALshark, fill = fishery, colour = cat)) + geom_bar(width = 0.5, stat = "identity", position = "dodge") + facet_wrap(~ div) g1 # grab 'cat' colours for each 'fishery' from plot object # to be used in manual fill cat_cols &lt;- unique(ggplot_build(g1)[["data"]][[1]]$colour) # unique 'cat' cat &lt;- unique(df$cat) # create data frame with one colour per 'cat' df2 &lt;- data.frame(cat = cat, cat_cols) df2 # alt 2: create your own 'cat' colours # number of unique 'cat' n &lt;- length(cats) # select one colour per 'cat', from e.g. brewer_pal or other palette tools cat_cols &lt;- brewer_pal(type = "qual")(n) # cat_cols &lt;- rainbow(n) # create data frame with one colour per 'cat' df2 &lt;- data.frame(cat, cat_cols) df2 # select unique 'fishery' and 'cat' combinations # in the order they show up in the legend, i.e. ordered ('arranged') by fishery df3 &lt;- unique(arrange(df[, c("fishery", "cat")], fishery)) df3 # add 'cat' colours to 'fishery' # use 'join' to keep order df3 &lt;- join(df3, df2) df3 # plot with fill by 'fishery' creates a fill scale by fishery, # but colours are set manually using scale_fill_manual and the 'cat' colours from above g2 &lt;- ggplot(df, aes(x = year, y = TOTALshark, fill = fishery)) + geom_bar(width = 0.5, stat = "identity", position = "dodge") + facet_wrap(~ div, nrow = 5) + scale_fill_manual(values = as.character(df3$cat_cols)) g2 </code></pre> <p><img src="https://i.stack.imgur.com/n3nkc.png" alt="enter image description here"></p> <pre><code># create plot with both 'fishery' and 'cat' legend. # extract 'fisheries' legend tmp &lt;- ggplot_gtable(ggplot_build(g2)) leg &lt;- which(sapply(tmp$grobs, function(x) x$name) == "guide-box") legend_fish &lt;- tmp$grobs[[leg]] # create a non-sense plot just to get a 'fill = cat' legend g3 &lt;- ggplot(df, aes(x = year, y = TOTALshark, fill = cat)) + geom_bar(stat = "identity") + scale_fill_manual(values = as.character(df3$cat_cols)) # extract 'cat' legend tmp &lt;- ggplot_gtable(ggplot_build(g3)) leg &lt;- which(sapply(tmp$grobs, function(x) x$name) == "guide-box") legend_cat &lt;- tmp$grobs[[leg]] # arrange plot and legends library(gridExtra) # quick and dirty with grid.arrange # in the first column, put the plot (g2) without legend (removed using the 'theme' code) # put the two legends in the second column grid.arrange(g2 + theme(legend.position = "none"), arrangeGrob(legend_fish, legend_cat), ncol = 2) # arrange with viewports # define plotting regions (viewports) grid.newpage() vp_plot &lt;- viewport(x = 0.25, y = 0.5, width = 0.5, height = 1) vp_legend &lt;- viewport(x = 0.75, y = 0.7, width = 0.5, height = 0.5) vp_sublegend &lt;- viewport(x = 0.7, y = 0.25, width = 0.5, height = 0.3) print(g2 + theme(legend.position = "none"), vp = vp_plot) upViewport(0) pushViewport(vp_legend) grid.draw(legend_fish) upViewport(0) pushViewport(vp_sublegend) grid.draw(legend_cat) </code></pre> <p><img src="https://i.stack.imgur.com/IBQmG.png" alt="enter image description here"></p> <p>See also @mnel's answer <a href="https://stackoverflow.com/questions/19018568/possible-to-combine-position-jitter-with-position-dodge/19019810#comment28113777_19019810">here</a> for replacing values in the plot object. It might be worth trying here as well. You may also check <code>gtable</code> methods for arranging grobs. </p>
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    1. COMany thanks @Henrik for this answer & links. This is what I was looking for!
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    2. COGlad to hear that it worked!
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    3. COAs you can see in the viewport code for the last plot, the (almost-)alignment of the two legends along x axis is hard-coded. I think I have seen examples on SO where the position of different grobs is calculated based on their width. But that is another story...Good luck!
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