This is a quick introduction to the bar mekko function* in the mekko package.
Its main value is to add quantitative context to a bar graph, via bar width.
knitr::opts_chunk$set( fig.width = 7, fig.height = 4 )
You can also install the development version with
devtools::install_github('ryninho/mekko', build_vignettes = TRUE).
View examples with:
First we'll load ggplot and mekko and create some example data.
profits <- data.frame( product = c('widgets', 'sprockets', 'cogs', 'whosits', 'whatsits'), profit_margin = c(3.2, -1.4, 0.1, -5.5, 11.9), revenue = c(850, 1600, 900, 675, 250) )
Now let's take a look at profit margin by product using ggplot2.
ggplot(profits, aes(x = product, y = profit_margin)) + geom_bar(stat = "identity")
Well that's insightful, but I don't know how worried I should be about the margin on whosits or cogs, nor do I know how happy I should be about whatsits knocking it out of the park. Maybe I can add revenue as the bar width so I know what's important here?
ggplot(profits, aes(x = product, y = profit_margin, width = revenue)) + geom_bar(stat = "identity") + labs(title = "Variable bar width fail :(")
Well shucks, that looks like some kind of Atari graphics airplane. Let's use the mekko package to put our margins in context.
bmx <- barmekko(profits, product, profit_margin, revenue) bmx
Alright, so actually the weak profit margins on sprockets may be worth nearly as much focus as the problem with whosits. Also, no high-fives for margins on the whatsits until we triple sales of them.
Those labels are a little close together- this is a ggplot object so let's use the usual method of rotating the axes.
bmx + theme(axis.text.x = element_text(angle = 90, hjust = 1))
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