Lecture 6: Working with Vectors and Variables in R

Author

Dr. Logan Kelly

Published

September 4, 2024

Overview

  • In this lecture, we’ll explore:
    • How to create and work with vectors in R.
    • Storing different types of variables (numeric, character, logical).
    • Indexing vectors to access or modify specific elements.

1. Creating Vectors in R

  • What is a vector?
    • A vector is one of the most fundamental data structures in R.
    • A vector stores a collection of elements that are all of the same data type (e.g., all numbers or all characters).
  • How to create a vector:
    • You can create a vector using the c() function, which stands for “combine.”
  • Example: Creating a numeric vector:
numbers <- c(10, 20, 30, 40, 50)  # Create a vector of numbers
  • Example: Creating a character vector:
names <- c("Alice", "Bob", "Charlie", "David")  # Create a vector of names
  • Example: Creating a logical vector:
logical_vector <- c(TRUE, FALSE, TRUE, TRUE)  # Create a vector of logical values

2. Storing Different Types of Variables

  • What is a variable in R?
    • A variable is a storage location where you can keep a value (e.g., a number, a string of text, or a logical value).
  • Types of variables:
    • Numeric: Numbers (e.g., 10, 25.5).
    • Character: Text strings (e.g., "Alice", "Data").
    • Logical: Boolean values, TRUE or FALSE.
  • Example: Storing a number as a variable:
x <- 10  # Store the number 10 in the variable 'x'
  • Example: Storing text as a variable:
name <- "Alice"  # Store the name 'Alice' in the variable 'name'
  • Example: Storing a logical value:
is_active <- TRUE  # Store the value TRUE in the variable 'is_active'

3. Indexing Vectors in R

  • What is indexing?
    • Indexing allows you to access or modify specific elements in a vector.
    • In R, indexing starts at 1, unlike many programming languages where indexing starts at 0.
  • Accessing elements in a vector:
    • Use square brackets [] to access elements at specific positions in a vector.
  • Example: Accessing the first element of a vector:
numbers <- c(10, 20, 30, 40, 50)  # Create a numeric vector
numbers[1]  # Access the first element (10)
[1] 10
  • Example: Accessing multiple elements:
numbers[2:4]  # Access elements from the second to the fourth position (20, 30, 40)
[1] 20 30 40
  • Modifying elements in a vector:
    • You can replace elements in a vector by assigning new values to specific positions.
  • Example: Changing the third element:
numbers[3] <- 35  # Change the third element to 35

4. Performing Operations on Vectors

  • Element-wise operations:
    • R can perform operations on each element of a vector automatically.
  • Example: Adding 10 to each element of a vector:
numbers <- c(10, 20, 30, 40, 50)
numbers + 10  # Add 10 to each element in the vector
[1] 20 30 40 50 60
  • Vector arithmetic:
    • You can also perform arithmetic between two vectors of the same length.
  • Example: Adding two vectors:
numbers1 <- c(1, 2, 3)
numbers2 <- c(4, 5, 6)
result <- numbers1 + numbers2  # Add corresponding elements (1+4, 2+5, 3+6)

Key Takeaways

  • You’ve learned how to create vectors in R and store different types of variables.
  • Indexing allows you to access and modify specific elements within a vector.
  • R performs operations on vectors in an element-wise manner, making it easy to manipulate data.

Looking Forward

  • In the next lecture, we’ll explore data frames and lists, two more advanced data structures that allow you to work with larger and more complex datasets in R.