Making a stacked area plot using ggplot2

问题:

I'm using the following data structure to try and make a stacked area chart:

df <- data.frame(PopDen = c( 0.002279892, 0.002885407, 0.004291351, 0.002457731, 0.006631572, 0.007578882, 0.004465446, 0.007436628, 0.009001456, 0.006951703, 0.003602076, 0.005695585, 0.005819783, 0.007412274, 0.004931548, 0.006257411, 0.008635908, 0.005438558, 0.002251421,0.006438558), DomArea = c( 253500, 135270, 197180, 131590, 142210, 166920, 125640, 184600, 139940, 126280, 127760, 190940, 133440, 143510, 117260, 69340, 143620, 127480, 181970,164180), PR_Cat = c( "High", "High", "Low", "Low", "Low", "Low", "Low", "Low", "High", "High", "Medium", "Medium", "Medium", "Low", "Low", "Medium", "Medium", "Low", "Low","Low") )  p <- ggplot(df, aes(PopDen, order(DomArea), colour = PR_Cat))   p + geom_area(aes(colour = PR_Cat, fill= PR_Cat), position = 'stack')

However, I don't understand how to stack the areas on top of each other; at the moment they are overlapping. I assume that I need a position = 'stack' argument here, but the plot looks the same whether it is included or not.

Also, is it possible to order DomArea by one of the categories in PR_Cator would I need to reorganize my data?

回答1:

I'm not sure what you are plotting here, but don't you want to be plotting PopDen along the y axis rather than the x axis? You can order the DomArea by each PR_Cat category using ddply from the plyr package, and then the stacking works as follows: EDIT I realized you probably want the plot to be stacked in the order Low, Medium High, so we need to first force this ordering on the PR_Cat factor by doing:

df$PR_Cat <- ordered( df$PR_Cat, levels = c('Low', 'Medium', 'High'))

And now create the DomAreaByCat column using ddply:

df <- ddply(df, .(PR_Cat), transform, DomAreaByCat = order(DomArea))

Your df will look like this:

> df         PopDen DomArea PR_Cat DomAreaByCat 1  0.004291351  197180    Low            8 2  0.002457731  131590    Low            5 3  0.006631572  142210    Low            9 4  0.007578882  166920    Low            2 5  0.004465446  125640    Low            3 6  0.007436628  184600    Low            7 7  0.007412274  143510    Low           11 8  0.004931548  117260    Low            4 9  0.005438558  127480    Low           10 10 0.002251421  181970    Low            6 11 0.006438558  164180    Low            1 12 0.003602076  127760 Medium            4 13 0.005695585  190940