What you’ll need:

This lesson assumes you have current versions of the following software installed on your computer:

  1. the R software itself, and
  2. RStudio Desktop
  3. the R package tidyverse (a package is a set of software tools that you use in R)

Both programmes and all R packages are free. RStudio runs the R software within it, so first download R package and install it on your computer. Then download and install RStudio. For detailed instructions for Macs or PCs, see https://datacarpentry.org/r-socialsci/setup.html

If you have never used R or RStudio before, I recommend going through this tutorial, it takes about 30 minutes. At the end of it you will download the package tidyverse

If you are familiar with RStudio install tidyverse by entering the command into your console:

install.packages("tidyverse")

What we’ll do:

On Monday we will be going through the tutorial “Manipulating, analyzing and exporting data with tidyverse”

This tutorial uses an example dataset we’ll call surveys. To import this dataset run the following code:

library(readr)
surveys <- read_csv("https://ndownloader.figshare.com/files/2292169")

This will create your first R object, a dataset called “surveys”. All exercises will be run on this dataset.

Useful stuff

There are tons of free resources for learning how to use R. For online resources I recommend:

Cheatsheets

The cheat sheets make it easy to learn about and use some of our favorite packages. They are published in their respective PDF versions here: https://www.rstudio.com/resources/cheatsheets/, some are also available in RStudio under Help-Cheatsheets.

Two suggested cheatsheets for Monday’s tutorial:

Data transformation with dplyr

RStudio guide

Textbook

R for Data Science by Hadley Wickham, the Buddah of the Tidyverse

Curriculum

I base tutorials around the Data/Software Carpentries: https://datacarpentry.org/lessons/ http://swcarpentry.github.io/r-novice-inflammation/