R Tutorial
Fundamentals of R
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Arrays in R are a multi-dimensional data structure that can hold more than two dimensions. Essentially, if matrices are 2D (rows x columns), arrays can be 2D, 3D, 4D, and so on. They are useful for operations that need to be performed across several different dimensions of data.
Here's a tutorial on arrays in R:
You can create an array using the array() function:
# Create a 3x3x2 array arr <- array(1:18, dim = c(3, 3, 2)) print(arr)
In the above code, we're creating an array with the numbers 1 through 18 and specifying its dimensions to be 3x3x2.
Elements in an array can be accessed using the indices for each dimension:
# Access the element in the 1st row, 2nd column of the 2nd matrix arr[1, 2, 2]
Arrays support typical arithmetic operations:
arr1 <- array(1:6, dim = c(2, 3)) arr2 <- array(7:12, dim = c(2, 3)) # Array addition result <- arr1 + arr2 print(result)
The apply() function can be used to apply a function across margins of an array:
# Sum across the rows (1st margin) of each matrix in the array row_sums <- apply(arr, MARGIN = 1, FUN = sum) # Sum across the columns (2nd margin) of each matrix in the array col_sums <- apply(arr, MARGIN = 2, FUN = sum)
The abind() function from the abind package is helpful for combining arrays:
# Install and load abind package
install.packages("abind")
library(abind)
arr3 <- array(19:24, dim = c(2, 3))
combined <- abind(arr1, arr2, arr3, along = 3) # Stack along the third dimension
You can assign names to the dimensions of an array:
# Naming the dimensions
rownames <- c("R1", "R2", "R3")
colnames <- c("C1", "C2", "C3")
matnames <- c("M1", "M2")
arr <- array(1:18, dim = c(3, 3, 2), dimnames = list(rownames, colnames, matnames))
print(arr)
The is.array() function can be used to check if an object is an array:
is.array(arr1) # Returns TRUE or FALSE
Arrays in R offer a flexible and powerful way to handle multi-dimensional data. While they might seem more complex than vectors or matrices, they are essential when working with higher-dimensional data. Functions like apply() and packages like abind further augment the usability of arrays in various applications.
Creating and initializing arrays in R:
# Creating a vector vec <- c(1, 2, 3, 4) # Creating a matrix mat <- matrix(1:6, nrow = 2, ncol = 3) # Creating a 3D array arr <- array(1:24, dim = c(2, 3, 4))
Manipulating arrays with apply functions in R:
# Applying a function to each column of a matrix apply(mat, 2, mean) # Applying a function to each row of a matrix apply(mat, 1, sum) # Applying a function to each element of a 3D array apply(arr, c(1, 2), sum)
Indexing and slicing arrays in R:
# Indexing a matrix mat[1, 2] # Slicing a matrix mat[, 1:2] # Indexing a 3D array arr[1, 2, 3]
R array operations and arithmetic:
# Element-wise addition of two arrays arr1 <- array(1:24, dim = c(2, 3, 4)) arr2 <- array(25:48, dim = c(2, 3, 4)) arr_sum <- arr1 + arr2
Converting matrices to arrays in R:
# Converting a matrix to an array mat <- matrix(1:6, nrow = 2, ncol = 3) arr_from_mat <- array(mat, dim = c(2, 3, 1))
Reshaping data into arrays in R:
# Reshaping a vector into a matrix vec <- 1:6 mat_from_vec <- matrix(vec, nrow = 2, ncol = 3)