Paths

(optional) If Using RStudio Cloud

• So far in this course we’ve been using RStudio Cloud and placing data files where R knows to find them for you
• Working with data files on your own computer is a little more complicated
• But in this lesson we’ll learn how to do this effectively

Introduction to Paths

• To use data stored on a computer we need to tell R where it is
• This is done using paths
• This is a description of the directories where our files are stored
• Let’s go to the course website and download some data
• https://datacarpentry.org/semester-biology/materials/datasets
• This page contains all of the data we use in class
• Download Shrub Dimensions data
• If we click on this link it will download, but where did it download to
• Click on the arrow to ‘Show in Folder’
• The details will look different depending on the operating system

• But, generally, across the top you’ll see the folder that things are stored in

• Go back to RStudio
• If we try to load this data just using it’s filename it won’t work

data = read.csv("shrub-dimensions-labeled.csv")

• Returns the error “Cannot open file”, “No such file or directory”

• That’s because it can’t find the file where we’ve tried to load it from

• Paths can be either relative or absolute
• We’ll start with absolute, which always describes exactly where something is on the computer
• Data file is stored in the Downloads subdirectory of our Home directory
• Home directory varies by operating system
• On mac and Linux it is /home/username
• Within that is the Downloads directory

data = read.csv('/home/ethan/datacarp/shrub-dimensions-labeled.csv') # OSX/Linux

• This successfully loads the data because we’ve told it exactly where the file is
• On Windows change home to Users

data = read.csv('/Users/ethan/datacarp/shrub-dimensions-labeled.csv') # Windows

• Folders/Directories are separate by / with the file name at the end

• Include the file extension (the part after the .)

• Paths can also be relative

'datacarp/shrub-dimensions-labeled.csv'

• “From where I am the shrub-dimensions file is in the Desktop subdirectory”
• Absolute & relative paths are the same if R thinks it’s in /home/ethan/

Find out where you are

• To find out where R is use getwd()

getwd()

• “get working directory”
• The “working directory” is where the program starts from

Loading data

• For data in the working directory just use the file name

shrub_data <- read.csv('shrub-dimensions-labeled.csv')

• This is a relative path, because the file is in the working directory the only remaining piece is the name

• One way to ensure that a file is in the working directory is to download it using download.file()

• For data not in the working directory there are two options
  • tell R where it is
  • change the working directory to where it is
• Changing the working directory is common
  • Who here uses setwd regularly?
  • Does that ever cause any issues?
    • Working on a different computer?
    • Working with someone else’s files?
• In general, using setwd means that your code will only work on a single computer
• That’s bad, so we want to have the working directory automatically and use relative paths

Projects

• The simplest way to do this is using RStudio Projects

• (RStudio Cloud) In fact we’ve already been using them

• (RStudio Cloud) Every time you click on an assignment or click New Project this creates a new project

• Each project is a self-contained unit of work in a single folder/directory
• Treat all locations as relative to that single directory
• To do this in regular RStudio we use projects
• File -> New Project -> New Directory -> New Project -> datacarp
• Or use Existing Directory to choose an existing directory
• Creates .Rproj file
  • Isn’t project itself
  • Contains project info
  • Don’t change manually
• Can switch between projects using File -> Recent Projects or Open Project
• Keeps track the state of RStudio when you last worked with that project

Sharing code

• This idea of projects as folders is also important for how we share code
• Version control, which we’ll have the opportunity to learn about later, works with the projects as folder structure
• We can also zip a the project folder and send it to someone else and they can work with it