I’ve been trying to carve out the time to write a post about the GooleVis package and, more specifically, how AWESOME motion charts are within GoogleVis, but in the mean-time, I’ve been spending a lot of time thinking about data visualizations. I think that the act of putting together an entry for Naomi Robbin’s Forbes Graph Challenge had this kind of an impact on my consciousness. Anyhow, a few early responders to Naomi’s post were discussing slope graphs (http://www.edwardtufte.com/bboard/q-and-a-fetch-msg?msg_id=0003nk) and it inspired me to seek out ways to incorporate these into some of my data presentations. I found a most excellent post here about producing them in R (http://www.jameskeirstead.ca/r/slopegraphs-in-r/). I will look for ways to incorporate these where they make sense in any future reporting.
Also, my issue of the week involved putting together a report that did an analysis of 300+ therapeutic groupings, where for each grouping I had to work out a way to get both an informative plot AND multiple pieces of data (2 data frames) to export to a single image. I resolved my issue with some help from gplots textplot() function.
testMat <- matrix(1:20, ncol = 5)## create data testMatDF <- as.data.frame(testMat) names(testMatDF) <- c("Hey there", "Column 2", "Some * Symbols", "And ^ More", "Final Column") rownames(testMatDF) <- paste("Group", 1:4) library(gplots) ## gplots needed for textplot() layout(matrix(c(1, 1, 2, 3, 3, 3), 2, 3, byrow = TRUE)) curve(dnorm, -3, 4) textplot(testMat) textplot(testMatDF) ## produces what I want within R png(file='plot1.png') layout(matrix(c(1, 1, 2, 3, 3, 3), 2, 3, byrow = TRUE)) curve(dnorm, -3, 4) textplot(testMat) textplot(testMatDF) dev.off() ## how to export the same