{"id":75596,"date":"2020-01-20T11:43:05","date_gmt":"2020-01-20T06:13:05","guid":{"rendered":"https:\/\/techvidvan.com\/tutorials\/?p=75596"},"modified":"2020-01-20T11:43:05","modified_gmt":"2020-01-20T06:13:05","slug":"r-vector-functions","status":"publish","type":"post","link":"https:\/\/techvidvan.com\/tutorials\/r-vector-functions\/","title":{"rendered":"Vector Functions in R – Master R seq, sapply, rep functions"},"content":{"rendered":"

Are you finding difficulty working with R vectors? Don’t worry, look at some vector functions in R that will make your life easier with R programming.<\/strong><\/p>\n

Functions are pieces of code that are created to perform specific tasks. We make functions to avoid repetition of code and errors. They also help us in making the code organized and readable.<\/p>\n

In this R tutorial, we will take a look at a few commonly used vector functions in R. We will see how they are used and what they do. We will also look at some examples of their usage. So, let\u2019s get going!<\/p>\n

What are R vector functions?<\/h2>\n

There are functions in R that either help with creating a vector or take vectors as input arguments. We call such functions as vector functions<\/strong> in R programming.<\/p>\n

Today, we are going to study a few vector functions in R, that you will find very useful in R programming. These functions are:<\/p>\n

    \n
  1. rep()<\/li>\n
  2. seq()<\/li>\n
  3. is.vector()<\/li>\n
  4. as.vector()<\/li>\n
  5. any()<\/li>\n
  6. all()<\/li>\n
  7. lapply()<\/li>\n
  8. sapply()<\/li>\n<\/ol>\n

    These functions either take a vector as input or return a vector as output.<\/p>\n

    1. The rep() Function<\/h3>\n

    The rep()<\/code><\/strong> function repeats a vector, or value, a given number of times. It then returns a vector with the repeated values. For example:<\/p>\n

    Wait! Do you know what is R vector? \u2013 vectors in R<\/strong><\/a><\/p>\n

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

    repeated_vector <- rep(c(1,2,3),4)\nrepeated_vector<\/pre>\n
    Output:<\/strong><\/p>\n
    \"rep()<\/a><\/strong><\/p>\n
    We can also specify the length<\/strong> of the vector instead of the number of times using the length.out<\/code><\/strong> argument. The function keeps the repetition going until the mentioned length is reached.<\/p>\n
    Code:<\/strong><\/p>\n
    repeated_vector2 <- rep(c(4,5,6),length.out=15)\nrepeated_vector2<\/pre>\n
    Output:<\/strong><\/p>\n
    \"rep()<\/a><\/strong><\/p>\n
    We can also use the each<\/code><\/strong> argument to repeat each element of the repeating vector. For example:<\/p>\n
    Code:<\/strong><\/p>\n
    repeated_vector3 <- rep(c(4,5,6),each=3)\nrepeated_vector3<\/pre>\n
    Output:<\/strong><\/p>\n
    \"rep()<\/a><\/strong><\/p>\n
    2. The seq() Function<\/h3>\n
    The seq()<\/code><\/strong> function creates a sequence of numbers starting from the given from<\/code><\/strong> argument and ending at the to<\/code><\/strong> argument. We can also pass the by<\/code><\/strong> argument to specify the increase\/decrease step. By default, the increase step is 1.<\/p>\n
    Example 1:<\/strong><\/p>\n
    sequence1 <- seq(from=2,to=15,by=0.5)\nsequence1<\/pre>\n
    Output:<\/strong><\/p>\n
    \"seq()<\/a><\/strong><\/p>\n
    We can also use the length.out<\/code><\/strong> argument to specify the length of the output vector. This way R keeps the sequence going until the desired length is reached.<\/p>\n
    Example 2:<\/strong><\/p>\n
    sequence2 <- seq(from=5,length.out=12)\nsequence2<\/pre>\n
    Example 3:<\/strong><\/p>\n
    sequence3 <- seq(from=5,to=15,length.out=20)\nsequence3<\/pre>\n
    Output:<\/strong><\/p>\n
    \"seq()<\/a><\/strong><\/p>\n
    3. The is.vector() Function<\/h3>\n
    The is.vector()<\/code><\/strong> function takes an object as an input and returns TRUE<\/code><\/strong> if the input object is a vector. It returns FALSE<\/code><\/strong> if the object is not a vector<\/a>.<\/p>\n
    Code:<\/strong><\/p>\n
    is.vector(sequence3)<\/pre>\n
    Output:<\/strong><\/p>\n
    \"is.vector()<\/a><\/strong><\/p>\n
    4. The as.vector() Function<\/h3>\n
    The as.vector()<\/code><\/strong> function takes an object as an argument and converts it into a vector. Let’s take a look at the workings of this function with an example.<\/p>\n
    First, let’s create a matrix. We will name this matrix mat_to_vec<\/code><\/strong>, as we will be converting it into a vector soon.<\/p>\n
    Code:<\/strong><\/p>\n
    mat_to_vec <- matrix(c(1:9),c(3,3))\nmat_to_vec<\/pre>\n
    Output:<\/strong><\/p>\n
    [,1] [,2] [,3]
    \n[1,] 1 4 7
    \n[2,] 2 5 8
    \n[3,] 3 6 9<\/div>\n
    By using the class()<\/code>\u00a0<\/strong>function we can confirm that mat_to_vec<\/code><\/strong> is in fact a matrix.<\/p>\n
    Code:<\/strong><\/p>\n
    class(mat_to_vec)<\/pre>\n
    Output:<\/strong><\/p>\n
    [1] “matrix”<\/div>\n
    Now, let’s use the as.vector()<\/code><\/strong> function on our matrix.<\/p>\n
    Code:<\/strong><\/p>\n
    mat_to_vec <- as.vector(mat_to_vec)\nmat_to_vec<\/pre>\n
    Output:<\/strong><\/p>\n
    [1] 1 2 3 4 5 6 7 8 9<\/div>\n
    As you can see, mat_to_vec<\/code><\/strong> is now arranged in a single row instead of 3×3 rows and columns. Instead of an integer matrix, it should now be an integer vector and should have a class of integer<\/strong>.<\/p>\n
    Code:<\/strong><\/p>\n
    class(mat_to_vec)<\/pre>\n
    Output:<\/strong><\/p>\n
    [1] “integer”<\/div>\n
    \"as.vector()<\/a><\/strong><\/p>\n
    5. The any() Function<\/h3>\n
    The any()<\/code><\/strong> function takes a vector and a logical condition as input arguments. It checks the vector against the condition and creates a logical vector<\/strong>. It then returnTRUE<\/code><\/strong>, if any one<\/strong> of the elements in the logical vector is TRUE<\/code><\/strong>.<\/p>\n
    Code:<\/strong><\/p>\n
    vec <- as.integer(c(34,23,53,42,16,42,64,32,76))\nany(vec,vec>50)<\/pre>\n
    Output:<\/strong><\/p>\n
    \"any()<\/a><\/strong><\/p>\n
    6. The all() Function<\/h3>\n
    The all()<\/code><\/strong> function takes a vector and a logical condition as input arguments. It checks the vector against the condition and creates a logical vector. It then returns TRUE<\/code><\/strong> if all<\/strong> the elements in the logical vector are TRUE<\/code><\/strong>, and FALSE<\/code><\/strong> if all elements<\/strong> are not TRUE<\/code><\/strong>.<\/p>\n
    Code:<\/strong><\/p>\n
    all(vec,vec>50)<\/pre>\n
    Output:<\/strong>
    \n    \"all()<\/a><\/strong><\/p>\n
    7. The lapply() Function<\/h3>\n
    The lapply()<\/code><\/strong> function takes a vector, list or a data frame and a function. The lapply()<\/code><\/strong> function applies a function to all elements of a vector, list<\/strong><\/a> or data frames. The function then returns the result in the form of a list<\/strong>. For example:<\/p>\n
    Code:<\/strong><\/p>\n
    names <- c(\"JOHN\",\"RICK\",\"RAHUL\",\"ABDUL\")\nlapply(names,tolower)<\/pre>\n
    Output:<\/strong><\/p>\n
    \"lapply()<\/a><\/strong><\/p>\n
    8. The sapply() Function<\/h3>\n
    The sapply()<\/code><\/strong> is very similar to the lappy()<\/code><\/strong> function. The only difference is that the sapply()<\/code><\/strong> function returns the result in the form of a vector. For example:<\/p>\n
    Code:<\/strong><\/p>\n
    sapply(names,tolower)<\/pre>\n
    Output:<\/strong><\/p>\n
    \"sapply()<\/a><\/strong><\/p>\n
    Summary<\/h2>\n
    Vector functions are functions that perform operations on vectors or give output as vectors. In this article, we studied some important vector functions in R. We looked at their uses and also saw examples of their usage.<\/p>\n
    The above functions like is.vector()<\/code><\/strong>, as.vector()<\/code><\/strong>, lapply()<\/code>,<\/strong>\u00a0sapply()<\/code>, any()<\/code>, <\/strong>and seq()<\/code><\/strong>\u00a0are very important and commonly used functions in the R programming language.<\/p>\n
    Still, finding difficulty working with vector functions in R?<\/strong><\/p>\n
    Feel free to ask any queries related to R tutorial and our experts at TechVidvan<\/strong> will be happy to help you.<\/p>\n","protected":false},"excerpt":{"rendered":"
    Are you finding difficulty working with R vectors? Don’t worry, look at some vector functions in R that will make your life easier with R programming. Functions are pieces of code that are created...<\/p>\n","protected":false},"author":1,"featured_media":75627,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1020],"tags":[1396,1397,1398,1399,1254,1400,1401,1402,1260],"class_list":["post-75596","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-r","tag-any","tag-lapply-r","tag-r-function","tag-r-seq","tag-r-vector","tag-r-vector-functions","tag-rep-in-r","tag-sapply-r","tag-vector-function-in-r"],"yoast_head":"\nVector Functions in R - Master R seq, sapply, rep functions - TechVidvan<\/title>\n<meta name=\"description\" content=\"Vector functions in R are pieces of code that are created to perform specific tasks. 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