index.Rmd

---
title: "Intro to R"
output:
  dcTemplate::dc_lesson_template:
    fig_width: 6
    fig_height: 6
    highlight: pygments
---


```{r knitr_init, echo = FALSE, cache = FALSE}
library(knitr)

## Global options
options(max.print = "75")
opts_chunk$set(cache = TRUE,
               prompt = FALSE,
               tidy = TRUE,
               comment = "> #",
               message = FALSE,
               warning = FALSE)
opts_knit$set(width = 75)
```

**Instructors:** Tim Dennis & Reid Otsuji  
**Dates:** 10/20 & 11/4  
**Time:** 10-noon  
**Location:** BLB Classroom 4  
**Sponsoring Library Programs:** Research & Reference Advisory – Data Services & Research Data Curation   

This is an introduction to R designed for participants with no programming experience.  They start with some basic information about R syntax, the RStudio interface, and move through how to import CSV files, the structure of data.frame, how to deal with factors, how to add/remove rows and columns, and finish with how to calculate summary statistics for each level and a very brief introduction to plotting.


**NOTE: This course is largely adapted from the Data Carpentry's R for Ecology lessons <http://www.datacarpentry.org/>.**

## Lessons: 

* Intro to R
* Creating functions
* Working with data

<!--
* [Lesson 00 Before We Start] #(00-before-we-start.html) - 15 min
* [Lesson 01 Introduction to R](01-intro-to-R.html) - 45min
* [Lesson 01a Creating functions](http://swcarpentry.github.io/r-novice-inflammation/02-func-R.html)
* [Lesson 02 Starting with Data](02-working-with-data.html) -30min
* [Lesson 04 Introducing `data.frame`](03-data-frames.html) - 30min
-->

## Supplemental lessons

* [Analyzing multiple data sets](http://swcarpentry.github.io/r-novice-inflammation/03-loops-R.html)
* [Making Choices](http://swcarpentry.github.io/r-novice-inflammation/04-cond.html)


## Resources 

* [RStudio Keyboard Shortcuts](https://support.rstudio.com/hc/en-us/articles/200711853-Keyboard-Shortcuts)
	- Insert assignment operator: windows (Alt+-); mac(Option+-)
	- Insert pipe operator: win(Ctrl+Shift+M); mac(Alt+Shift+M)
<!-- * [Instructor's Notes](instr_notes.html) -->

# Setup

## R

[R](http://www.r-project.org) is a programming language that is especially powerful for data exploration, visualization, and statistical analysis. To interact with R, we use [RStudio](http://www.rstudio.com/).

## Windows {#r-windows}

Install R by downloading and running [this .exe file](http://cran.r-project.org/bin/windows/base/release.htm) from [CRAN](http://cran.r-project.org/index.html). Also, please install the [RStudio IDE](http://www.rstudio.com/ide/download/desktop).

## Mac OS X {#r-macosx}

Install R by downloading and running [this .pkg file](http://cran.r-project.org/bin/macosx/R-latest.pkg) from
[CRAN](http://cran.r-project.org/index.html). Also, please install the [RStudio IDE](http://www.rstudio.com/ide/download/desktop).


## Linux {#r-linux}

You can download the binary files for your distribution from [CRAN](http://cran.r-project.org/index.html). Or you can use your package manager (e.g. for Debian/Ubuntu run `sudo apt-get install r-base` and for Fedora run `sudo yum install R`).Also, please install the [RStudio IDE](http://www.rstudio.com/ide/download/desktop).