R Data Structures: Introduction to Matrices

gist_matrix.R

# syntax
args(matrix)

# numeric matrix of 3 rows filled by columns
mat <- matrix(data = 1:9, nrow = 3, byrow = FALSE)
mat

# error in specifying rows/columns
mat1 <- matrix(data = 1:9, nrow = 2)
mat

mat <- matrix(data = 1:10, ncol = 3)
mat

# fill data by rows/columns
# matrix filled by rows
mat_row <- matrix(1:9, nrow = 3, byrow = TRUE)
mat_row

# matrix filled by columns
mat_col <- matrix(1:9, nrow = 3, byrow = FALSE)
mat_col

# number of rows/columns
# number of rows specified
mat1 <- matrix(1:9, nrow = 3)
mat1

# number of columns specified
mat2 <- matrix(1:9, ncol = 3)
mat2

# specify row/column names using list
# creating a simple list
# character vector
names <- c('John', 'Jovial', 'Jack')

# numeric vector
age <- c(25, 28, 24)

# create a list
details <- list(names, age)
details

# row names
row_names <- c('row1', 'row2', 'row3')
col_names <- c('col1', 'col2', 'col3')

# matrix with row/column names
mat_names <- matrix(data = 1:9, nrow = 3, dimnames = list(row_names, col_names))
mat_names

# check dimension using dim function
# 3 x 3 matrix
mat1 <- matrix(1:9, nrow = 3)

# 3 x 4 matrix
mat2 <- matrix(1:12, nrow = 3)

# check dimension
dim(mat1)
dim(mat2)

# modify dimension using the dim function
# 3 x 4 matrix
mat1 <- matrix(1:12, nrow = 3)
mat1

# change dimension to 4 x 3
dim(mat1) <- c(4, 3)
mat1

# 2 x 6 matrix
mat <- matrix(1:12, nrow = 2)
mat

# change dimension to 6 x 2
dim(mat) <- c(6, 2)
mat

# coerce vectors 
vect1 <- 1:10
vect1
dim(vect1)

# use dim to modify dimension
dim(vect1) <- c(2, 5)
vect1
dim(vect1)

# as.matrix function
vect1 <- 1:10
vect1

# coerce to type matrix
as.matrix(vect1)

# matrix addition
mat1 <- matrix(1:9, nrow = 3)
mat2 <- matrix(sample(9), nrow = 3)

# add mat1 and mat2
mat1 + mat2

# add 5 to all elements of mat1
mat1 + 5

# add 3 to all elements of mat2
mat2 + 3

# matrix subtraction
mat1

mat2

# element wise matrix subtraction
mat1 - mat2

# subtract 3 from all elements of mat1
mat1 - 3

# subtract 5 from all elements of mat2
mat2 - 5

# matrix division
mat1

mat2

# element wise matrix division
mat1 / mat2

# divide all elements of mat1 by 3
mat1 / 3

# divide all elements of mat2 by 5
mat2 / 5

# transpose of a matrix
# 3 x 4 matrix
mat1 <- matrix(1:12, nrow = 3)
mat1

# 4 x 3 matrix
t(mat1)

# matrix multiplication
# 3 x 4 matrix
mat1 <- matrix(1:12, nrow = 3)
mat1

# 4 x 3 matrix
mat2 <- matrix(sample(12), nrow = 4)
mat2

# use %*% to multiply matrices
mat1 %*% mat2


# matrix inverse
# 3 x 3 matrix
mat1 <- matrix(sample(9), nrow = 3)
mat1

# use solve() to compute the inverse
solve(mat1)


# append vector to columns
# 3 x 3 matrix
mat1 <- matrix(sample(9), nrow = 3)
mat1

# numeric vector
vect1 <- sample(3)
vect1

# append new row
rbind(mat1, vect1)

# append new column
cbind(mat1, vect1)

# combine matrices
mat1 <- matrix(1:9, nrow = 3)
mat1

mat2 <- matrix(sample(9), ncol = 3)
mat2

# combine by rows
rbind(mat1, mat2)

# combine by columns
cbind(mat1, mat2)


# index/subset matrices
# 4 x 3 matrix
mat <- matrix(1:12, nrow = 4)
mat

# subset element in first row/first column
mat[1, 1]

# subset element in second row/first column
mat[2, 1]

# subset element in fourth row/third column
mat[4, 3]


# 4 x 3 matrix
mat <- matrix(1:12, nrow = 4)
mat

# subset all rows of first column
mat[, 1]

# subset all columns of the second row
mat[2, ]

# subset using row/column names
# row names
row_names <- c('row1', 'row2', 'row3')
col_names <- c('col1', 'col2', 'col3')

# matrix with row/column names
mat_names <- matrix(data = 1:9, nrow = 3, dimnames = list(row_names, col_names))
mat_names

# subset elements in first row/column
mat_names['row1', 'col1']

# subset elements in second row
mat_names['row2', ]

# subset using logical expressions
# 4 x 3 matrix
mat <- matrix(1:12, nrow = 4)
mat

# elements greater than 4
mat > 4

# extract elements greater than 4
mat[mat > 4]

# dissolve a matrix
# 3 x 3 matrix
mat <- matrix(1:9, nrow = 3)
mat

# use the c function
c(mat)

# use the as.vector function
as.vector(mat)