The #spiffy @dseverski gave me this posit the other day:
— David F. Severski (@dseverski) October 25, 2013
and, I obliged shortly thereafter, but figured I’d toss a post up on the blog before heading to Strata.
To rephrase the tweet a bit, Mr. Severski asked me what alternate encoding I’d use for this grouped bar chart (larger version at the link in David’s tweet):
I have almost as much disdain for grouped bar charts as I do for pie or donut charts, so appreciated the opportunity to try a makeover. However, I ran into an immediate problem: the usually #spiffy 451 Group folks did not include raw data. So, I reverse engineered the graph with WebPlotDigitizer, cleaned up the result and made a CSV from it. Then, I headed to RStudio with a plan in mind.
The old chart and data screamed faceted dot plot. The only trick necessary was to manually order the factor levels.
library(ggplot) # read in the CSV file nosql.df <- read.csv("nosql.csv", header=TRUE) # manually order facets nosql.df$Database <- factor(nosql.df$Database, levels=c("MongoDB","Cassandra","Redis","HBase","CouchDB", "Neo4j","Riak","MarkLogic","Couchbase","DynamoDB")) # start the plot gg <- ggplot(data=nosql.df, aes(x=Quarter, y=Index)) # use points, colored by Quarter gg <- gg + geom_point(aes(color=Quarter), size=3) # make strips by nosql db factor gg <- gg + facet_grid(Database~.) # rotate the plot gg <- gg + coord_flip() # get rid of most of the junk gg <- gg + theme_bw() # add a title gg <- gg + labs(x="", title="NoSQL LinkedIn Skills Index\nSeptember 2013") # get rid of the legend gg <- gg + theme(legend.position = "none") # ensure the strip is gone gg <- gg + theme(strip.text.x = element_blank()) gg
The result is below in SVG form (install a proper browser if you can’t see it, or run the R code :-) I think it conveys the data in a much more informative way. How would you encode the data to make it more informative and accessible?
Full source & data over at github.