(This article was first published on rud.is » R, and kindly contributed to R-bloggers)
Naomi Robbins is running a graph makeover challenge over at her Forbes blog and this is my entry for the B2B/B2C Traffic Sources one (click for larger version):
And, here’s the R source for how to generate it:
library(ggplot2) df = read.csv("b2bb2c.csv") ggplot(data=df,aes(x=Site,y=Percentage,fill=Site)) + geom_bar(stat="identity") + facet_grid(Venue ~ .) + coord_flip() + opts(legend.position = "none", title="Social Traffic Sources for B2B & B2C Companies") + stat_bin(geom="text", aes(label=sprintf("%d%%",Percentage), vjust=0, hjust=-0.2, size = 10)) |
And, here’s the data:
Site Venue Percentage Facebook B2B 72 LinkedIn B2B 16 Twitter B2B 12 Facebook B2C 84 LinkedIn B2C 1 Twitter B2C 15
I chose to go with a latticed bar chart as I think it helps show the relative portions within each category (B2B/B2C) and also enables quick comparisons across categories for all three factors.
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