R
superheat 0.1.0 is now available on CRAN. Superheat makes it easy to create extendable, cutomizable, and most importantly, beautiful heatmaps. It has increased flexibility and user-friendliness when compared to alternatives such as heatmap() and pheatmap().
For usage options see the vignette and for examples see the accompanying paper by Barter and Yu (2017).
You can install the latest version with:
install.packages("superheat") Stay tuned for new versions with added features and minor usability tweaks.
Making beautiful and customizable heatmaps just got way easier… Introducing the superheat R package!
Using superheat, it is now extremely easy to produce plots like the example below describing 10 randomly selected cars from the famous mtcars dataset.
library(superheat) set.seed(1347983) selected.rows <- sample(1:nrow(mtcars), 10) X.col <- matrix("black", ncol = ncol(mtcars), nrow = 10) X.col[scale(mtcars[selected.rows, ]) < 0] <- "white" superheat(mtcars[selected.rows,], # add text X.text = round(as.matrix(mtcars[selected.rows, ])), X.text.col = X.col, # scale columns scale = T, # label aesthetics left.
Pie charts are terrible Pie charts are notoriously terrible for data visualization. Humans are genuinely bad at comparing angles. Thus, the only reason one should ever use a pie chart is to make beautiful pie-chart-art.
par(mar = c(0, 1, 0, 1)) pie( c(280, 60, 20), c('Sky', 'Sunny side of pyramid', 'Shady side of pyramid'), col = c('#0292D8', '#F7EA39', '#C4B632'), init.angle = -50, border = NA ) Figure 1: Pyramid pie chart art.
