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copied!<p>If you use the excellent <code>FactoMineR</code> package for pca, you might find this useful for making plots with <code>ggplot2</code></p> <pre><code># Plotting the output of FactoMineR's PCA using ggplot2 # # load libraries library(FactoMineR) library(ggplot2) library(scales) library(grid) library(plyr) library(gridExtra) # # start with a clean slate rm(list=ls(all=TRUE)) # # load example data from the FactoMineR package data(decathlon) # # compute PCA res.pca <- PCA(decathlon, quanti.sup = 11:12, quali.sup=13, graph = FALSE) # # extract some parts for plotting PC1 <- res.pca$ind$coord[,1] PC2 <- res.pca$ind$coord[,2] labs <- rownames(res.pca$ind$coord) PCs <- data.frame(cbind(PC1,PC2)) rownames(PCs) <- labs # # Just showing the individual samples... ggplot(PCs, aes(PC1,PC2, label=rownames(PCs))) + geom_text() # # Now get supplementary categorical variables cPC1 <- res.pca$quali.sup$coor[,1] cPC2 <- res.pca$quali.sup$coor[,2] clabs <- rownames(res.pca$quali.sup$coor) cPCs <- data.frame(cbind(cPC1,cPC2)) rownames(cPCs) <- clabs colnames(cPCs) <- colnames(PCs) # # Put samples and categorical variables (ie. grouping # of samples) all together p <- ggplot() + opts(aspect.ratio=1) + theme_bw(base_size = 20) # no data so there's nothing to plot... # add on data p <- p + geom_text(data=PCs, aes(x=PC1,y=PC2,label=rownames(PCs)), size=4) p <- p + geom_text(data=cPCs, aes(x=cPC1,y=cPC2,label=rownames(cPCs)),size=10) p # show plot with both layers # # clear the plot dev.off() # # Now extract variables # vPC1 <- res.pca$var$coord[,1] vPC2 <- res.pca$var$coord[,2] vlabs <- rownames(res.pca$var$coord) vPCs <- data.frame(cbind(vPC1,vPC2)) rownames(vPCs) <- vlabs colnames(vPCs) <- colnames(PCs) # # and plot them # pv <- ggplot() + opts(aspect.ratio=1) + theme_bw(base_size = 20) # no data so there's nothing to plot # put a faint circle there, as is customary angle <- seq(-pi, pi, length = 50) df <- data.frame(x = sin(angle), y = cos(angle)) pv <- pv + geom_path(aes(x, y), data = df, colour="grey70") # # add on arrows and variable labels pv <- pv + geom_text(data=vPCs, aes(x=vPC1,y=vPC2,label=rownames(vPCs)), size=4) + xlab("PC1") + ylab("PC2") pv <- pv + geom_segment(data=vPCs, aes(x = 0, y = 0, xend = vPC1*0.9, yend = vPC2*0.9), arrow = arrow(length = unit(1/2, 'picas')), color = "grey30") pv # show plot # # clear the plot dev.off() # # Now put them side by side # library(gridExtra) grid.arrange(p,pv,nrow=1) # # Now they can be saved or exported... # # tidy up by deleting the plots # dev.off() </code></pre> <p>And here's what the final plots looks like, perhaps the text size on the left plot could be a little smaller:</p> <p><img src="https://i.stack.imgur.com/M5ASm.png" alt="enter image description here"></p>

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