1. An Introduction to RIts Bigger on the Inside

2. You could say Ive been usingfor a whileJohnny Appleseed 3. But then I decided to grow upand learn somethinguseful 4. For Statisticians By StatisticiansThis is a good thingand a bad thingR grew out of an appreciation for the S programming language(fathered by John Chambers at Bell Labs)Ross Ihaka and Robert Gentleman set out to make a better statisticslab at U. of Aukland; R was the result 5. A Little ContextR, like S, is pretty Scheme-yBut its also OO, except when its notAnd mostly people stitch packages togetheruntil something works 6. The Packages You'll NeedFor the budding data scientist,bare minimum starter set caret ggplot2 (ggvis) data.table dplyr RODBC lattice RCurl Hmisc/rms zoo reshape2 7. The Places You'll GoThe non-definitive list of resources http://www.r-bloggers.com/ http://stackoverflow.com/questions/tagged/r http://www.statmethods.net/ (Quick R) http://onepager.togaware.com/ (One page R) http://www.rdocumentation.org/ 8. The HadleyverseHadley Wickam gets +3 charisma for just showing up ggplot2 lubridate reshape2 stringr dplyr ggvis 9. Lasciate ogne speranza, voi ch'entrateOh, by the way R has a perverse love for floating point numbers Repeat after memap, dont loop; map, dont loop R is terseuse tiny functions and lots of them Expect inconsistency, skepticism is your friend 10. Now, We Code