Featuring the lovely “spectral” palette from Colorbrewer. This really just serves as a reminder of how to do four things I frequently want to do: Make a heatmap of some kind of matrix, often a square correlation matrix Reorder a factor vari...

I wrote before about heatmap tables as a better way of producing frequency or other tables, with a solution which works nicely in latex. It is possible to do them much more easily in ggplot2, like this library(Hmisc) library(ggplot2) library(reshape) data(HairEyeColor) P=t(HairEyeColor) Pm=melt(P) ggfluctuation(Pm,type="heatmap")+geom_text(aes(label=Pm$value),colour="white")+ opts(axis.text.x=theme_text(size = 15),axis.text.y=theme_text(size = 15)) Note that ggfluctuation will also take

I wrote before about heatmap tables as a better way of producing frequency or other tables, with a solution which works nicely in latex. It is possible to do them much more easily in ggplot2, like this library(Hmisc) library(ggplot2) library(reshape) data(HairEyeColor) P=t(HairEyeColor) Pm=melt(P) ggfluctuation(Pm,type="heatmap")+geom_text(aes(label=Pm$value),colour="white")+ opts(axis.text.x=theme_text(size = 15),axis.text.y=theme_text(size = 15)) Note that ggfluctuation will also take … Continue reading...

In this article, Hans Gilde exposes the clever use of a heatmap hidden in the Bioconductor library. In his example, he describes a way to show different ‘observations’ on subjects, with the concept of time. Financial indices, like the S&P 500 or the Dow Jones indices, are mathematically some kind of measure of overall market

If you want more info about clustering, I have another post about "Clustering analysis and its implementation in R". Here is the link: http://onetipperday.blogspot.com/2012/04/clustering-analysis-2.html------------Several R functions in this...

I wrote before about using heatmap tables to combine the strengths of tables and graphics for nominal data. Here is a neat approach using Sweave and latex to produce an effect like in the picture. This latex code is self-contained. Just save it as myfile.Rnw, run Sweave(myfile.Rnw) from inside R and then pdflatex myfile.tex