{"id":75678,"date":"2020-01-23T10:53:55","date_gmt":"2020-01-23T05:23:55","guid":{"rendered":"https:\/\/techvidvan.com\/tutorials\/?p=75678"},"modified":"2020-01-23T10:53:55","modified_gmt":"2020-01-23T05:23:55","slug":"r-matrix-functions","status":"publish","type":"post","link":"https:\/\/techvidvan.com\/tutorials\/r-matrix-functions\/","title":{"rendered":"Matrix Functions in R – solve(), dim(), sum(), mean(), cbind()"},"content":{"rendered":"

In this article, we will learn what are matrix functions in R and different functions that operate on matrices. We will see their usage and look at a few examples.<\/p>\n

If you skipped the\u00a0<\/span>R matrix<\/span><\/strong><\/a> tutorial, then revise R matrices before understanding its function.<\/span><\/p>\n

What are R Matrices?<\/h3>\n

In R, matrices are two-dimensional<\/strong> data structures. They can store values of the same data type in the form of rows and columns. They have a dim<\/code><\/strong>attribute that defines their dimensions. We can create a matrix using the matrix()<\/code><\/strong> function.<\/p>\n

What are the Matrix Functions in R?<\/h2>\n

Functions that take a matrix as input or return a matrix as output are called matrix functions<\/strong>. There are a lot of matrix functions in R. The major one that we are going to discuss today are:<\/p>\n

    \n
  1. is.matrix() function<\/li>\n
  2. %*% operator<\/li>\n
  3. solve() function<\/li>\n
  4. t() function<\/li>\n
  5. dim() and dimnames() functions<\/li>\n
  6. cbind() and rbind() functions<\/li>\n
  7. diag() function<\/li>\n
  8. det() function<\/li>\n
  9. colSums(), rowSums(), and sum() functions<\/li>\n
  10. colMeans(), rowMeans(), and mean() functions<\/li>\n<\/ol>\n

    1. is.matrix() Function<\/h3>\n

    The is.matrix()<\/code><\/strong> function takes an object as input and returns TRUE<\/code><\/strong> if the object is a matrix. For example:<\/p>\n

    Code:<\/strong><\/p>\n

    mat1 <- matrix(c(1:9),c(3,3))\nis.matrix(mat1)<\/pre>\n
    Output:<\/strong><\/p>\n
    \"is.matrix()<\/a><\/strong><\/p>\n
    2. %*% Operator<\/h3>\n
    We can perform the element-wise multiplication of two matrices using the *<\/code><\/strong> operator. But we can do matrix multiplication, with the %*%<\/code><\/strong> operator. For example:<\/p>\n
    Code:<\/strong><\/p>\n
    mat2 <- matrix(c(3,2,0,0,0,1,2,-2,1),c(3,3))\nmat1*mat2<\/pre>\n
    Code:<\/strong><\/p>\n
    mat1%*%mat2<\/pre>\n
    Output:<\/strong><\/p>\n
    \"%*%<\/a><\/p>\n
    3. solve() Function<\/h3>\n
    The solve()<\/code><\/strong> function takes a matrix as input and returns the matrix\u2019s inverse as output. For example:<\/p>\n
    Code:<\/strong><\/p>\n
    mat2I <- solve(mat2)\nmat2I<\/pre>\n
    Output:<\/strong><\/p>\n
    \"solve()<\/a><\/strong><\/p>\n
    4. t() Function<\/h3>\n
    The t()<\/code><\/strong> function in R<\/a> gives us the transpose of a matrix. For example:<\/p>\n
    Code:<\/strong><\/p>\n
    tmat1 <- t(mat1)\ntmat1<\/pre>\n
    Output:<\/strong><\/p>\n
    \"t()<\/a><\/strong><\/p>\n
    5. dim() and dimnames() Functions<\/h3>\n
    The dim()<\/code><\/strong> function shows the dimension of a matrix. It can also change the dimension of a matrix and also convert a vector<\/strong><\/a> into a matrix by giving it dimensions.<\/p>\n
    The dimnames()<\/code><\/strong> function shows the names of the rows and columns of a matrix. It can also set or change the names of the rows and columns of a matrix. For example:<\/p>\n
    Code:<\/strong><\/p>\n
    dim(mat1)<\/pre>\n
    Code:<\/strong><\/p>\n
    dim(mat1) <- c(9,1)\nmat1<\/pre>\n
    Output:<\/strong><\/p>\n
    \"dim()<\/a><\/strong><\/p>\n
    Code:<\/strong><\/p>\n
    dimnames(mat2)<\/pre>\n
    Code:<\/strong><\/p>\n
    rnames <- c(\"row1\",\"row2\",\"row3\")\ncnames <- c(\"col1\",\"col2\",\"col3\")\ndimnames(mat2) <- list(rnames,cnames)\nmat2<\/pre>\n
    Output:<\/strong><\/p>\n
    \"dimnames()<\/a><\/strong><\/p>\n
    6. cbind() and rbind() Functions<\/h3>\n
    The cbind()<\/code><\/strong> function joins two or more matrices or vectors column-wise<\/strong>. The rbind()<\/code><\/strong> function joins them row-wise<\/strong>. For example:<\/p>\n
    Code:<\/strong><\/p>\n
    mat3 <- matrix(c(1:12),c(3,4))\nmat4 <- matrix(c(11:22),c(3,4))\ncbind(mat3,mat4)<\/pre>\n
    Code:<\/strong><\/p>\n
    rbind(mat3,mat4)<\/pre>\n
    Output:<\/strong><\/p>\n
    \"cbind()<\/a><\/strong><\/p>\n
    7. diag() Function<\/h3>\n
    The diag()<\/code><\/strong> function can extract or replace the diagonal of a matrix and can also construct a diagonal matrix. For example:<\/p>\n
    Code:<\/strong><\/p>\n
    diag(mat3)<\/pre>\n
    Code:<\/strong><\/p>\n
    diag(diag(mat3))<\/pre>\n
    Output:<\/strong><\/p>\n
    \"diag()<\/a><\/strong><\/p>\n
    8. det() Function<\/h3>\n
    The det()<\/code><\/strong> function returns the determinant of the input matrix. For example:<\/p>\n
    Code:<\/strong><\/p>\n
    det(mat2)<\/pre>\n
    Output:<\/strong><\/p>\n
    \"det()<\/a><\/strong><\/p>\n
    9. colSums(), rowSums(), and sum() Functions<\/h3>\n
    The colSums()<\/code><\/strong> function returns the sums of each column<\/strong> of the matrix. The rowSums()<\/code><\/strong> function returns the sum of each row<\/strong> of a matrix. The sum()<\/code><\/strong> function returns the sum of all the elements of the matrix. For example:<\/p>\n
    Code:<\/strong><\/p>\n
    colSums(mat3)<\/pre>\n
    Code:<\/strong><\/p>\n
    rowSums(mat3)<\/pre>\n
    Code:<\/strong><\/p>\n
    sum(mat3)<\/pre>\n
    Output:<\/strong><\/p>\n
    \"colsums(),<\/a><\/strong><\/p>\n
    10. colMeans(), rowMeans(), and mean() Function<\/h3>\n
    The colMeans()<\/code><\/strong> function shows the means of each column of a matrix. The rowMeans()<\/code><\/strong> function shows the means of each row of the matrix. The mean()<\/code><\/strong> function returns the mean of all the elements of the matrix. For example:<\/p>\n
    Code:<\/strong><\/p>\n
    colMeans(mat3)<\/pre>\n
    Code:<\/strong><\/p>\n
    rowMeans(mat3)<\/pre>\n
    Code:<\/strong><\/p>\n
    mean(mat3)<\/pre>\n
    Output:<\/strong><\/p>\n
    \"colmeans(),rowmeans()<\/a><\/strong><\/p>\n
    Summary<\/h2>\n
    Matrices are two-dimensional, homogeneous data-structures in R. They have rows and columns and they can store data of only a single type.<\/p>\n
    In this tutorial, we learned about matrices and matrix functions in R. We looked at a few common matrix functions. We also looked at their usage and their examples.<\/p>\n
    R has a lot of useful functions<\/strong><\/a> to perform complex calculations on matrices. With practice, you should be able to discover some more weird quirks and behaviors of these functions.<\/p>\n
    Any queries while executing these R matrix functions?<\/strong><\/p>\n
    Don’t worry! Ask below, and our <\/span>TechVidvan<\/span><\/strong>\u00a0experts will be happy to help you.\"?\"<\/span><\/p>\n
    Keep Executing!!<\/p>\n","protected":false},"excerpt":{"rendered":"
    In this article, we will learn what are matrix functions in R and different functions that operate on matrices. We will see their usage and look at a few examples. If you skipped the\u00a0R...<\/p>\n","protected":false},"author":1,"featured_media":75740,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1020],"tags":[1270,1411,1412,1413,1253,1414,1415,1416],"class_list":["post-75678","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-r","tag-matrix-function-in-r","tag-matrix-functions-in-r","tag-r-cbind","tag-r-dim","tag-r-matrix","tag-r-mean","tag-r-solve","tag-r-sum"],"yoast_head":"\nMatrix Functions in R - solve(), dim(), sum(), mean(), cbind() - TechVidvan<\/title>\n<meta name=\"description\" content=\"How to execute solve(), dim(), sum(), mean() matrix functions in R? 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