R is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues. R can be considered as a different implementation of S. There are some important differences, but much code written for S runs unaltered under R. - The R Project website.

R is Freeware, and is DOD Complient on a number of platforms.

R has packages developed for just about everything imaginable, including creating your own xkcd-style graphics.

There are many ways to create visualizations in R, and we will not cover all of them here. This brief will discuss the following techniques:

1. Plot Functions in Base R
2. Grammar of Graphics - ggplot2
3. 3-d web based graphics, including plot_ly

We will also consider the following enablers:

1. Interactive Environments - Markdown and Shiny
2. Power Tools - magrittr and dplyr

Example dataset that comes standard with base R about the Michaelson-Morely Experiment.

data(morley); library(knitr);library(magrittr)
morley[1:3,] %>% kable()

library(dplyr); data(morley)
boxplot(Speed~Run, data = morley, xlab = "Run",
        ylab = "Speed", main = "R Base Plot Example")

library(ggplot2); library(magrittr)
mp = morley[morley$Expt %in% 1:4,] %>% ggplot( aes(x = Speed, y = Run)) +
geom_smooth() 
mp + facet_wrap(~Expt, ncol = 2)

library(plotly); library(reshape2)
PD = acast(morley, Run ~Expt, value.var = "Speed") 
plot_ly(z = PD, type = 'surface')

library(ggplot2);library(xkcd);library(extrafont)
p = ggplot() + xkcdrect(mapping, data) + 
  xkcdaxis(xrange, yrange) + xlab("Run") + ylab("Speed")
p

\(\LaTeX\) is built in

\[ F(\omega) = \int_{-\infty}^{\infty} f(t) e^{- j \omega t} dt \] This audience might prefer: \[ \hat{\beta} = (X'X)^{-1}X'Y \]

FY 17 Budget

-dplyr: Advanced summarization / data extraction tools for R

-reshape2: Allows the user to 'flatten' and 'recast' tabular dat

-magrittr: introduces the 'pipe' %>% operator, greatly streamlining code

-ggplot2 (covered previously): Advanced Graphics

-Rpubs: Publish to your own (free) website. Examples are here

-Shinyapps.io: Publish applications built in R/Shiny to the web. Fee structure depends on how much you want to host. A simple example is here, a more complicated example is here

• Three choices for Markdown Documents, in order of output quality:
  • HTML
  • PDF via \(\LaTeX\)
  • MS Word
• Three Choices for Markdown Presentations, in order of Quality
  • HTML via IOslides (This Presentation)
  • HTML via Slidy (not bad)
  • Beamer via \(\LaTeX\). I used to be a huge Beamer fan, but IOSlides and Slidy blow it away

• Books:
• R in a Nutshell
• Advanced R Programming
• The R Cookbook
• Web:
• Stack Overflow
• HipsteR
• rBloggers
• rProject.org