Syntax Operators

Materials adapted from Adrien Osakwe, Larisa M. Soto and Xiaoqi Xie.

Syntax operators are the specialized symbols and keywords that define how R interprets your code. They handle essential tasks like naming objects, writing notes to yourself, and digging into complex datasets.

It includes comment line, assignation, access content, and equal.

1. Comments (#): Writing Notes to Your Future Self

Comments are used to explain why you wrote a specific line of code. This is vital for reproducibility and collaboration. Anything written after the # symbol is ignored by R during execution.

  • Manual: Type # before your note.
  • Shortcut (Mac): Cmd + Shift + C
  • Shortcut (Windows): Ctrl + Shift + C
# This is a comment. R will not execute this.
# "hello world"
Note

The shortcut is “smart.” If you highlight ten lines of code and hit the shortcut, it will comment out all ten lines at once. Hit it again to “uncomment” them.

Note

It doesn’t matter how many # symbols you use.

R simply looks for the first one on a line and ignores everything to the right of it. You are free to use multiple hashtags to create visual hierarchy in your script:

#-----------------------------------------------------------
## MAIN SECTION: DATA CLEANING
#-----------------------------------------------------------

### Step 1: Remove outliers
# The following line filters out p-values above 0.05
Tip

Best Practices for Commenting

  1. Don’t explain “What”: R (and yourself) knows what the code is doing.

    • Bad: # Adding 1 to x

  2. Explain “Why”: Explain the scientific logic.

    • Good: # Adjusting for batch effect

  3. Use them as “Bookmarks”: Use long lines of hashtags to separate your “Loading Data” section from your “Plotting” section.

2. Assignment: Creating Objects

Assignment is the process of storing a value (data) inside a named container (an object).

2.1 The Left-Hand Assignment (<-)

The standard way to assign values in R is using the <- operator. Think of it as an arrow pointing from the data to the label.

# The convention is to use left hand assignation 
var1 <- "hello world"
var1
[1] "hello world"
Note

Shortcut for <-

Instead of typing two characters, use these shortcuts to insert the assignment arrow:

  • Mac: Option + - (minus key)

  • Windows: Alt + - (minus key)

Note

A Note on Coding Style: To Space or Not to Space?

While var1<-“hello world” works, it is a little bit “dirty” and hard to read.

Following the Tidyverse Style Guide, you should always put a space before and after the assignment operator: var1 <- "hello world"

2.2 Other Assignment Methods

2.2.1 The Equals Sign (=):

While = works for assignment, R users generally avoid it. In R, = is typically reserved for defining arguments inside a function. Using it for general assignment is considered poor style.

# It is also possible to use the '=' sign, but is NOT a good practice
var1 = "hello world"
var1
[1] "hello world"

2.2.2 Right-Hand Assignment (->):

You can technically point the arrow the other way: "data" -> var1.

This is rarely used but can be helpful at the end of a long pipe (|>) if you decide to save the final result into a new variable.

"hello world" -> var1
var1
[1] "hello world"

2.3 Printing Variables

Once you have stored data in a variable, there are several ways to “call” it back to the console:

2.3.1 Direct Call

Simply type the name. This is the most common method during interactive analysis.

"hello world!"
[1] "hello world!"

2.3.2 Using Function print() and cat()

print(): Explicitly prints the object. This is often used inside “loops” or complex functions where R might not automatically show the output.

cat(): Short for “concatenate.” It prints the raw text without the [1] index marker or quotes. It is great for creating clean, human-readable messages.

var1 <- "McGill"
print(var1)
[1] "McGill"
var1 <- "McGill"
cat(var1)
McGill

3. Access Content ($)

The $ operator is one of the most powerful symbols in R. It allows you to “reach inside” a complex object (like a Data Frame or a List) and extract a specific column or element by its name.

Example: The iris Dataset

The iris dataset is a built-in collection of measurements for 150 flowers. It includes variables like Sepal.Length, Petal.Length, and Species. To look at only the species column, we use the $ operator.

# Show the first 6 rows of the dataset
head(iris)
  Sepal.Length Sepal.Width Petal.Length Petal.Width Species
1          5.1         3.5          1.4         0.2  setosa
2          4.9         3.0          1.4         0.2  setosa
3          4.7         3.2          1.3         0.2  setosa
4          4.6         3.1          1.5         0.2  setosa
5          5.0         3.6          1.4         0.2  setosa
6          5.4         3.9          1.7         0.4  setosa
# Extract only the "Species" column
iris$Species
  [1] setosa     setosa     setosa     setosa     setosa     setosa    
  [7] setosa     setosa     setosa     setosa     setosa     setosa    
 [13] setosa     setosa     setosa     setosa     setosa     setosa    
 [19] setosa     setosa     setosa     setosa     setosa     setosa    
 [25] setosa     setosa     setosa     setosa     setosa     setosa    
 [31] setosa     setosa     setosa     setosa     setosa     setosa    
 [37] setosa     setosa     setosa     setosa     setosa     setosa    
 [43] setosa     setosa     setosa     setosa     setosa     setosa    
 [49] setosa     setosa     versicolor versicolor versicolor versicolor
 [55] versicolor versicolor versicolor versicolor versicolor versicolor
 [61] versicolor versicolor versicolor versicolor versicolor versicolor
 [67] versicolor versicolor versicolor versicolor versicolor versicolor
 [73] versicolor versicolor versicolor versicolor versicolor versicolor
 [79] versicolor versicolor versicolor versicolor versicolor versicolor
 [85] versicolor versicolor versicolor versicolor versicolor versicolor
 [91] versicolor versicolor versicolor versicolor versicolor versicolor
 [97] versicolor versicolor versicolor versicolor virginica  virginica 
[103] virginica  virginica  virginica  virginica  virginica  virginica 
[109] virginica  virginica  virginica  virginica  virginica  virginica 
[115] virginica  virginica  virginica  virginica  virginica  virginica 
[121] virginica  virginica  virginica  virginica  virginica  virginica 
[127] virginica  virginica  virginica  virginica  virginica  virginica 
[133] virginica  virginica  virginica  virginica  virginica  virginica 
[139] virginica  virginica  virginica  virginica  virginica  virginica 
[145] virginica  virginica  virginica  virginica  virginica  virginica 
Levels: setosa versicolor virginica
Note

The head() Function

The head() function is a “quick look” tool. It returns the first few rows of a dataset (default is 6) so you can inspect your data without flooding your console with thousands of lines.

Conversely, tail() shows you the last few rows.

Remember, you can always type ?head in your Console to see the full documentation.

4. The Equal Operator (=)

In R, the single equals sign (=) has two primary roles, but they are not created equal.