Learning R Data Types

Understanding the various data types in R

Atomic Data Types

R has several atomic data types including numeric, character, logical, integer, and complex.

Numeric: Used for numeric values.
x <- 10.5

Logical: Used for boolean values (TRUE/FALSE).
z <- TRUE

Integer: Used for integer values.
age <- 25L

Complex: Used for complex numbers.
cplx <- 3 + 4i

R also has composite data types such as vectors, lists, data frames, matrices, and arrays.

Vector: A collection of elements of the same type.
vec <- c(1, 2, 3, 4, 5)

List: A collection of elements of different types.
lst <- list(name="John", age=30, isStudent=TRUE)

Data Frame: A table-like structure with rows and columns.
df <- data.frame(name=c("John", "Alice", "Bob"), age=c(30, 25, 28))

Matrix: A 2-dimensional array with elements of the same type.
mat <- matrix(c(1, 2, 3, 4), nrow=2, ncol=2)

Array: A multi-dimensional generalization of vectors and matrices.
arr <- array(1:24, dim=c(2, 3, 4))

Now that you've learned about R data types, it's time to practice. Try the following exercises to test your understanding:

Create a numeric vector called ages and assign ages of 5 people to it.
Define a list called person containing the name, age, and gender of a person.
Create a data frame called students with columns name, age, and grade containing information about students.
Make a matrix my_matrix with 3 rows and 2 columns filled with numeric values.