In this post, we will show how to create vectors, factors, lists, matrices and datasets in R<\/p>\n
The vector is a very important tool in R programming. Through vectors, we create matrix and data frames. For example, lets create a numeric vector:<\/p>\n Also, we can have a character vector<\/p>\n Finally, we can create and logical vectors<\/p>\n Additionally, you can create a vector which combine a numeric and a character values. Also we can check if the vector is numeric or character.<\/p>\n Sometimes we might be interested to know the number of elements that a vector has, or in other words the length of vector.<\/p>\n A simple way to generate vectors is to use Factors are similar to vectors in R but they have another meaning. Factors have levels. In medical research, levels are widely used and they have an important meaning. For example, the smoking could be on 3 levels: never smoker, a former smoker, and current smoker. When we code smoking we can write 0, 1, 2 for never, former and current smoker, respectively. To create a factor the function Create a vector with 6 elements:<\/p>\n To make these factors, use the function When you conduct your analysis make sure that you have coded factors accurately.<\/p>\n Lists are vectors, but not like vectors links can combine different types of objects. For example, let suppose that we want to create a list of medical records. Medical records contain diagnosis, age, and treatment of patients.<\/p>\n The function to create lists is Now that you created a list let see how we can work with it. You may want to access a individuals element of the list.<\/p>\n Sometime you may want to know what is the size of the list, and for this use the function Matrices are vectors with more then one dimension, therefore, matrices has rows and columns. To defined number of columns and rows you use the functions Or simply you can create a matrix like this.<\/p>\n Another way of creating matrices is by using functions column-binding You can create matrix in an other way, by defining the vector and the names of columns and rows.<\/p>\n As you see above, the function Datasets are similar to the matrix, but in comparison with the matrix, data frame contains numeric and character elements. Therefore, a data frame can have one column with numbers and another column with a character. The function used to create data frames is Let’s create a simple dataset.<\/p>\n Frequently we are intrested to look the structure of dataset we use, and for this we use the function Here we end this post. Post a comment if you have any question.<\/p>\n","protected":false},"excerpt":{"rendered":" In this post, we will show how to create vectors, factors, lists, matrices and datasets in R Vectors The vector is a very important tool in R programming. Through vectors, we create matrix and data frames. Vectors can have numeric, character and logical values. The function c() is used to create vectors in R programming. […]<\/p>\n","protected":false},"author":1,"featured_media":181,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[6],"tags":[14,232],"class_list":["post-178","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-introduction","tag-data-frames","tag-rstats"],"views":80850,"_links":{"self":[{"href":"https:\/\/datascienceplus.com\/wp-json\/wp\/v2\/posts\/178","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/datascienceplus.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/datascienceplus.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/datascienceplus.com\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/datascienceplus.com\/wp-json\/wp\/v2\/comments?post=178"}],"version-history":[{"count":0,"href":"https:\/\/datascienceplus.com\/wp-json\/wp\/v2\/posts\/178\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/datascienceplus.com\/wp-json\/wp\/v2\/media\/181"}],"wp:attachment":[{"href":"https:\/\/datascienceplus.com\/wp-json\/wp\/v2\/media?parent=178"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/datascienceplus.com\/wp-json\/wp\/v2\/categories?post=178"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/datascienceplus.com\/wp-json\/wp\/v2\/tags?post=178"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
\nVectors can have numeric, character and logical values. The function c()<\/code> is used to create vectors in R programming.<\/p>\n\r\n# numeric\r\nx <- c(1, 3, 2, 5.2, -4, 5, 12)\r\nx\r\n1 3 2 5.2 -4 5 12<\/em>\r\n<\/pre>\n
\r\n# character\r\ny <- c(\"red\", \"blue\", \"green\", \"no color\")\r\ny\r\n\"red\" \"blue\" \"green\" \"no color\"<\/em>\r\n<\/pre>\n
\r\n# logical\r\nz <- c(TRUE, TRUE, FALSE)\r\nz\r\nTRUE TRUE FALSE<\/em>\r\n<\/pre>\n
\r\n# numeric and character\r\nx <- c(1, 2.2, \"blue\")\r\nx\r\n# check if it is numeric\r\nis.numeric(x)\r\n# check if it is character\r\nis.character(x)\r\n\"1\" \"2.2\" \"blue\"\r\nFALSE\r\nTRUE<\/em><\/pre>\n
\r\nx <- c(1,2,6,4,7)\r\nlength(x)\r\n5<\/em>\r\n<\/pre>\n
seq()<\/code> function in arithmetic progression.<\/p>\n\r\nx <- seq(from=2, to=10, by=2)\r\nx\r\n2 4 6 8 10<\/em>\r\n<\/pre>\n
Factors<\/h2>\n
factor()<\/code> is used.<\/p>\n\r\ns <- c(0, 1, 2, 1, 0, 0)\r\ns\r\n0, 1, 2, 1, 0<\/em><\/pre>\n
factor<\/code>:<\/p>\n\r\nsf <- factor(s)\r\nsf\r\n0 1 2 1 0 0\r\nLevels: 0 1 2<\/em><\/pre>\n
Lists<\/h2>\n
list()<\/code>. <\/p>\n\r\nx <- list(diagnosis=\"Gastritis\", age=79, medication=TRUE)\r\nx\r\n$diagnosis\r\n\"Gastritis\"\r\n$age\r\n79\r\n$medication\r\nTRUE<\/em><\/pre>\n
\r\nx$age\r\nx$medication\r\n79\r\nTRUE<\/em><\/pre>\n
length<\/code>.<\/p>\n\r\nlength(x)\r\n3<\/em><\/pre>\n
Matrices<\/h2>\n
nrow<\/code> and ncol<\/code>, respectively. Similarly to vectors, matrices can have numbers, characters and logical values.<\/p>\n\r\n# create matrix with 6 elements\r\ny <- matrix(1:6, nrow=3, ncol=2)\r\ny\r\n [,1] [,2]\r\n[1,] 1 4\r\n[2,] 2 5\r\n[3,] 3 6<\/em>\r\n<\/pre>\n
\r\n# create matrix with 10 elements\r\ny <- matrix(1:10, nrow=2)\r\n# number of row is 2, than the columns will be 5\r\ny\r\n [,1] [,2] [,3] [,4] [,5]\r\n[1,] 1 3 5 7 9\r\n[2,] 2 4 6 8 10<\/em><\/pre>\n
cbind()<\/code> or row-binding rbind()<\/code>.<\/p>\n\r\n# create vectors\r\nx <- 2:5\r\ny <- 9:12\r\n# sort by rows\r\nrbind(x,y)\r\n# sort by columns\r\ncbind(x,y)\r\n[,1] [,2] [,3] [,4]\r\nx 2 3 4 5\r\ny 9 10 11 12\r\n\r\n x y\r\n[1,] 2 9\r\n[2,] 3 10\r\n[3,] 4 11\r\n[4,] 5 12<\/em><\/pre>\n
\r\n# create matrix with 4 elements\r\ncells <- c(2,5,12,30)\r\ncolname <- c(\"Jan\", \"Feb\")\r\nrowname <- c(\"Apple\", \"Orange\")\r\ny <- matrix(cells, nrow=2, ncol=2, byrow=TRUE, dimnames=list(rowname, colname))\r\ny\r\n Jan Feb\r\nApple 2 5\r\nOrange 12 30<\/em><\/pre>\n
byrow=TRUE<\/code> set the order of cells by row, you can change in FALSE<\/code> as well.<\/p>\nDatasets<\/h2>\n
dataframe()<\/code><\/p>\n\r\nhospital <- c(\"New York\", \"California\")\r\npatients <- c(150, 350)\r\ndf <- data.frame(hospital, patients)\r\ndf\r\nhospital patients\r\nNew York 150\r\nCalifornia 350<\/em>\r\n<\/pre>\n
str()<\/code>:<\/p>\n\r\nstr(df)\r\n'data.frame':\t2 obs. of 2 variables:\r\n $ hospital: Factor w\/ 2 levels \"California\",\"New York\": 2 1\r\n $ patients: num 150 350<\/em><\/pre>\n