R Data Structures

 

R provides several data structures that are used to store and manipulate data.

Ø   The most commonly used data structures in R:

a.         Vectors: A vector is a basic data structure in R that stores a sequence of values of the same data type. You can create a vector using the c() function.

For example, x <- c(1, 2, 3)

creates a vector x with values 1, 2, and 3.

b.         Matrices: A matrix is a two-dimensional data structure in R that contains rows and columns of values of the same data type. You can create a matrix using the matrix() function.

For example, m <- matrix(c(1, 2, 3, 4), nrow = 2, ncol = 2)

creates a 2x2 matrix m with values 1, 2, 3, and 4.

c.         Arrays: An array is a multi-dimensional data structure in R that can contain values of the same data type. You can create an array using the array() function.

For example, a <- array(c(1, 2, 3, 4), dim = c(2, 2, 1))

creates a 2x2x1 array a with values 1, 2, 3, and 4.

d.         Lists: A list is a collection of objects of different data types that can be of varying lengths. You can create a list using the list() function.

For example, l <- list(1, "two", TRUE)

creates a list l with a numeric value, a character value, and a logical value.

e.         Data Frames: A data frame is a two-dimensional data structure in R that is similar to a matrix but allows for columns of different data types. You can create a data frame using the data.frame() function.

For example, df <- data.frame(x = c(1, 2, 3), y = c("a", "b", "c"))

creates a data frame df with two columns, one numeric and one character.

Understanding and working with these data structures is crucial for performing data analysis tasks in R, as they allow you to store, manipulate, and analyze data efficiently.