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RCourse.Rpres
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RCourse.Rpres
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Introduction to R
========================================================
author: Rodrigo R Amadeu
date: Sep 11th 2018
autosize: true
AGR5266 - Field Plot Techniques
========================================================
[Top 10 Programming Languages 2018](https://spectrum.ieee.org/ns/IEEE_TPL_2018/index/2018/1/1/1/1/1/50/1/50/1/50/1/30/1/30/1/30/1/20/1/20/1/5/1/5/1/20/1/100/)
Freely available language and environment for statistical computing and graphics which provides a wide variety of statistical and graphical techniques. It's GNU!
========================================================
**GNU Philosophy**
+ to run the program
+ to study and change the program in source code form
+ to redistribute exact copies
+ to distribute modified versions
R Overview
========================================================
+ Data Science/Statistics
+ Modeling
+ Graphics
+ Programming language
+ Free
+ Open Source
+ Extensible
+ Apps
+ Repeatability!
+ Widely used in Life Sciences
R Theory
========================================================
From Ihaca [Speech](https://www.stat.auckland.ac.nz/~ihaka/downloads/JSM-2010.pdf):
R provides An interactive, extensible, vectorised language with a large run-time environment
which provides a good deal of statistical functionality and good graphics capabilities.
It comes with the the freedom to inspect, modify and redistribute the source code.
Extensive “third-party solutions” are available through the CRAN websites. User support
is available through community mechanisms.
Open R
Interfaces: RStudio
========================================================
[Different interfaces](goo.gl/oqKLnE)
Open RStudio
Practice
========================================================
From here to where?
========================================================
* Report (Rmd) on RStudio
* https://rmarkdown.rstudio.com/gallery.html
From here to where?
========================================================
`pres.Rmd`
More about R? Tutorials
========================================================
* https://www.coursera.org/learn/r-programming
* https://www.datacamp.com/courses/free-introduction-to-r
* http://tryr.codeschool.com/
* http://swirlstats.com/
More about R? Tutorials
========================================================
**Old school**
* [Amazon Books](https://goo.gl/sTmyPe)
* https://cran.r-project.org/doc/contrib/Verzani-SimpleR.pdf
* https://cran.r-project.org/doc/manuals/R-intro.pdf
* [Dr. Peng Books](https://leanpub.com/u/rdpeng) (pay as much as you want and my personal preference)
Debugging Code
========================================================
* http://stackoverflow.com/
* http://rseek.org/
* [Google!](https://www.google.com.br/?gfe_rd=cr&ei=s-gYWKeZGNHV8wfOzZHwCA#q=R+Cran)
Motivational - From here to where?
========================================================
* Graphics
[Basic + ggplot2](http://www.r-graph-gallery.com/)
[Course](https://rramadeu.github.io/2016/07/07/Graphics-Course/)
[RCircos](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3765848/)
From here to where?
========================================================
* Apps
* https://plot.ly/r/3d-surface-plots/
* http://shinyapps.stat.ubc.ca/r-graph-catalog/
* http://rosetta.ahmedmoustafa.io/drift/
Advanced R
========================================================
* Dates? _lubridate_
* http://vita.had.co.nz/papers/tidy-data.pdf
* http://tidyverse.org/
* https://www.rstudio.com/resources/webinars/working-with-big-data-in-r/
* https://www.coursera.org/learn/advanced-r
Packages
========================================================
* 1x routine -> ok, just comment it
* 2x routine -> wrap it in a function
* 2+ routine -> wrap them in a package
* https://support.rstudio.com/hc/en-us/articles/200486488-Developing-Packages-with-RStudio
* http://kbroman.org/pkg_primer/