Variables and Vectors

R is a programming language and software environment specialized in statistical data analysis, data visualization, and machine learning.

Unlike other general-purpose languages, R was designed by statisticians for statisticians, making vector and matrix manipulation and aggregation operations extremely intuitive.

Variables and Assignment

In R, the standard convention for assigning a value to a variable is to use the left arrow operator <-, composed of the less-than character < followed by a hyphen -.

Although the = operator is valid in most contexts, the R community prefers <- to clearly distinguish variable assignment from passing arguments inside functions.

# Assign the value 42 to the variable age
age <- 42

# We can print the value using the print() function
print(age)

Vectors

The fundamental data structure in R is the vector. A vector is an ordered collection of elements of the same type. In R, even a single number (a scalar) is technically treated as a vector of length 1.

To create a vector with multiple elements, use the concatenation function c():

# Create a vector with the first four even numbers
even_numbers <- c(2, 4, 6, 8)
print(even_numbers)

Vectorized Operations

R supports vectorized operations. When you apply an arithmetic operator to a vector, R applies the operation to each element of the vector individually (element-by-element):

prices <- c(10, 20, 30)

# Multiply each price by 2
doubled_prices <- prices * 2
# The result will be c(20, 40, 60)

If we operate on two vectors of the same length, the operation is executed element-by-element:

v1 <- c(1, 2, 3)
v2 <- c(10, 20, 30)
v3 <- v1 + v2
# The result will be c(11, 22, 33)

Sequences and Vector Names

R provides powerful tools for generating sequences of numbers. In addition to the : operator (e.g., 1:10), we can use the seq() function to define a custom increment:

# Generates numbers from 1 to 5 with an increment of 0.5
custom_seq <- seq(from = 1, to = 5, by = 0.5)

Furthermore, elements of a vector can have associated names that make them easier to identify, which can be set using the names() function:

temperatures <- c(22, 24)
names(temperatures) <- c("Mon", "Tue")

Try it yourself