Interactive Session 3B

Linear algebra basics: scalars, vectors & matrices

1. Set up

A new workflow! GitHub repo FIRST, then R project.

  1. Go to https://github.com (you should already be logged in)
  2. To create a new GitHub repository, either (a) click on the “+” button in the top right corner of your profile landing page > New repository, or (b) navigate to the Repositories page > click on the green “New” button
  3. Name it eds212-day3b
  4. Initialize it with a README file, then click Create repository
  5. Click on the green Code button and copy https URL
  6. Go back to RStudio
  7. Click on New Project > Version Control > Git > paste your URL, then click the tab key to auto fill the Project Directory name > click Create Project (use the Browse button to save your project to your EDS-212/).
  8. Tada! Now you have a project set up to go with version control & already connected to a GitHub repo

In your new project:

  1. Create a new Quarto document
  2. Save as r-vectors.qmd

2. Vectors

Vectors in R

Complete the following in your Quarto doc, r-vectors.qmd:

Create vectors in R using c().

Note that all elements in a vector must be a single class (e.g. all strings or all numeric values) - if strings and numbers are combined, the whole thing will be of class character.

For example:

# Create and store the vector ----
marmots <- c("blue", "green", 4, "yellow")

# Return it ----
marmots
[1] "blue"   "green"  "4"      "yellow"
# Check the class ----
class(marmots)
[1] "character"

If all values are numeric, however, it will be stored as a number:

# Create and store the vector ----
pika <- c(12.4, 6.8, 2.9, 8.8, 5)

# Return it ----
pika
[1] 12.4  6.8  2.9  8.8  5.0
# Check the class ----
class(pika)
[1] "numeric"

Notice in the vector above, these are class numeric. If values should be integers (often the case with count data), you can add an L after the value.

# Create the integer vector ----
bear <- c(20L, 3L, 5L, 18L, 23L)

# Look at it ----
bear
[1] 20  3  5 18 23
# Check the class ----
class(bear) 
[1] "integer"

We learn something important here: even numbers can be stored in R in different ways: floats are numbers that have decimals (these show up as class numeric) and integers, numbers without decimals (these show up as class integer).

You’ll learn about data representation and other classes of data in EDS 221.

Vector addition and subtraction, scalar multiplier, and dot product

You can add or subtract numeric vectors of equal length using basic operations. For example, let’s make two new vectors of length 4, then try adding & subtracting them:

# Create two vectors -----
ringtail <- c(4.3, 8.9, 2.6, 7.1)
fox <- c(9.0, 12.5, 5.4, 10.9)

# Addition ----
ringtail + fox
[1] 13.3 21.4  8.0 18.0
# Subtraction ----
fox - ringtail
[1] 4.7 3.6 2.8 3.8
# Scalar multiplier ----
100 * ringtail
[1] 430 890 260 710
# Dot product ----
ringtail %*% fox
       [,1]
[1,] 241.38

3. Stage, commit, push your files to GitHub using RStudio’s Terminal

Rather than using the Git tab and GUI buttons, let’s perform the same steps using git commands in the Terminal:

  • Switch from the Console to the Terminal (if you don’t see a Terminal tab, open one up by clicking Tools > Terminal > New Terminal)
  • Run git status to see any newly added or modified files (they should be red) – notice that these match the files in the Git pane
  • Run git add . to add (aka stage) all three files at once (analogous to checking the boxes in the Git pane)
  • Run git status again to verify that they have been added (they should now be green)
    • Note: If you refresh your Git pane, you should also see check marks appear beside each of these newly staged files.
  • Run git commit -m "your commit message here" to commit them (analogous to typing your commit message into the popup window and clicking the Commit button)
  • Run git status again to verify that your changes have been committed
    • Note: If you refresh your Git pane again, you should see that those staged files have disappeared, and a message that indicates that “Your branch is ahead of ‘origin/main’ by 1 commit” (meaning that you have committed changes locally that GitHub doesn’t know about yet)
  • Run git push (analogous to clicking the Push button)
  • Run git status again to verify that your local branch is up to date with ‘origin/main’ (meaning that both your local repo and your remote repo on GitHub now have the same exact commit history)
    • Note: If you refresh your Git pane (yet again), the previous message should disappear
Important takeaway: git commands underlie the actions performed by RStudio’s Git tab / buttons

Whenever you stage / commit / push files using RStudio’s super helpful buttons, RStudio is simply running these git commands in the background.

Why is it worthwhile to get used to running these git commands? As you begin learning new languages and working in different IDEs, you may or may not have GUI buttons for adding / committing / pushing files to GitHub. You can, however, always use the command line to navigate to a git directory, then use these git commands to do so.


End interactive session 3B