Reshape2

After my presentation yesterday to a group of grad students on R resources, I did a presentation today on intro to R data manipulation, visualizations, and analyses/visualizations of biparite networks and community level analyses (diversity, rarefaction, ordination, etc.). As I said yesterday I’ve been playing with two ways to make reproducible presentations in R: RStudio’s presentations built in to RStudio IDE, and Slidify. Yesterday I went with RStudio’s product - today I used Slidify....

Excel pivot tables have been how I have reorganized data…up until now. These are just a couple of examples why R is superior to Excel for reorganizing data: UPDATE: I fixed the code to use ‘dcast’ instead of ‘cast’. And library(ggplot2) instead of library(plyr) [plyr is called along with ggplot2]. Thanks Bob! Also, see another post on this topic here. library(reshape2) library(ggplot2) dataset <- data.frame(var1 = rep(c("a","b","c","d","e","f"), each = 4), var2 = rep(c("level1","level1","level2","level2"), 6), var3 = rep(c("h","m"), 12), meas = rep(1:12)) Created by Pretty R at inside-R....