R vector comes in two parts: Atomic vectors<\/strong> and Lists.<\/strong> They have three common properties:<\/p>\n These data structures share one difference, that is, they differ in the type of their elements:\u00a0 All elements of an atomic vector must be of the same type, whereas the elements of a list can have different types.<\/p>\n We have discussed R Lists<\/a>\u00a0in detail in our previous tutorial, you must check it.<\/strong><\/em><\/p>\n There are four common types of R atomic vectors:<\/p>\n Decimal values are referred to as numeric data types in R. If we assign a decimal value for any variable g,<\/em> as given below then, g will become a numeric type.<\/p>\n For example:<\/strong><\/p>\n Adding the class:<\/p>\n Output:<\/strong><\/p>\n A numeric value with no fraction called integer data is represented by \u201cInt\u201d.\u00a0-54 and 23 are two of the examples of an integer. Int size is 2 bytes while long Int size is 4 byte.<\/p>\n In order to assign an integer to a variable, there are two ways:<\/p>\n For checking data type:<\/p>\n For checking data type:<\/p>\n Output:<\/strong><\/p>\n The character is held as the one-byte integer in memory. There are two ways to create a character data type value in R:<\/p>\n For determining the type of x:<\/p>\n For determining the type of y:<\/p>\n Output:<\/strong><\/p>\n A logical data type returns either of the two values – TRUE or FALSE based on which condition is satisfied.<\/p>\n For example:<\/strong><\/p>\n Output:<\/strong><\/p>\n Learn about the R Data Types<\/a> in detail<\/strong><\/em><\/p>\n The c()<\/em> function is used for creating a vector in R. This function returns a one-dimensional array, also known as vector.<\/p>\n For example:<\/strong><\/p>\n Output:<\/strong><\/p>\n There are several other ways of creating a vector:<\/p>\n 1. Using the Operator<\/strong><\/p>\n For y operator:<\/p>\n Output:<\/strong><\/p>\n 2. Create R vector using\u00a0seq() function<\/strong><\/p>\n There are also two ways in this. The first way is to set the step size and the second method is by setting the length of the vector.<\/p>\n Output:<\/strong><\/p>\n Must Learn – How to apply Functions over R Vectors<\/a><\/strong><\/em><\/p>\n With the help of vector indexing, we can access the elements of vectors. Indexing denotes the position where the values in a vector are stored. This indexing can be performed with the help of integer, character or logic.<\/p>\n Unlike many programming languages like Python, C++, Java etc. where the indexing starts from 0, the indexing of vectors in R starts with 1.<\/p>\n We can perform indexing by specifying integer value in square braces [ ] next to our vector.<\/p>\n Output:<\/strong><\/p>\n Character vector indexing can be done as follows:<\/p>\n Output:<\/strong><\/p>\n In logical indexing, the positions whose corresponding position has logical vector TRUE are returned. For example, in the below code, R returns the positions of 1 and 3, where the corresponding logical vectors are TRUE.<\/p>\n Output:<\/strong><\/p>\n Functions\u00a0are used\u00a0to combine vectors.\u00a0In order to combine the two vectors in R, we will create two new vectors \u2018n\u2019 and \u2018s\u2019. Then, we will create another vector that will combine these two using c(n,s) as follows:<\/p>\n For example:<\/strong><\/p>\n Output:<\/strong><\/p>\n Wait! Have you checked – Data Structures in R<\/a><\/strong><\/em><\/p>\n Arithmetic operations on vectors can\u00a0be performed\u00a0member-by-member.<\/p>\n For example:<\/strong><\/p>\n Suppose we have two vectors a and b:<\/p>\n For subtraction:<\/p>\n For division:<\/p>\n For remainder operation:<\/p>\n Output:<\/strong><\/p>\n By using a logical index vector in R, we can form a new vector from a given vector, which has the same length as the original vector. If the corresponding members of the original vector are included in the slice, then vector members are TRUE and otherwise FALSE.<\/p>\n For example:<\/strong><\/p>\n Output:<\/strong><\/p>\n For indexing a numerical value in R<\/a>, we specify the index between square braces [ ]. If our index is negative, then R will return us all the values except for the index that we have specified. For example, specifying [-2] will prompt R to convert -2 into its absolute value and then search for the value that occupies that index.<\/p>\n For example:<\/strong><\/p>\n For negative index:<\/p>\n For out of range index:<\/p>\n Output:<\/strong><\/p>\n You must definitely explore the Numeric and Character Functions in R<\/a><\/strong><\/em><\/p>\n The index vector allows duplicate values. Hence, the following retrieves a member twice in one operation.<\/p>\n For example:<\/strong><\/p>\n Output:<\/strong><\/p>\n To produce a vector slice between two indexes, we can use the colon operator “:<\/strong>“. It is convenient for situations involving large vectors.<\/p>\n For example:<\/strong><\/p>\n Output:<\/strong><\/p>\n The index vector can even be out-of-order. Here is a vector slice with the order of first and second members reversed.<\/p>\n For example:<\/strong><\/p>\n Output:<\/strong><\/p>\n We first create our vector of characters:<\/p>\n Then, we name the first vector member as \u201cFirst\u201d and the second member as \u201cSecond\u201d.<\/p>\n We retrieve the first member by its name as follows:<\/p>\n We can also reverse the order using the character string index vector:<\/p>\n\n
Atomic Vectors in R<\/h3>\n
1. Numeric Data Type<\/h4>\n
> #Author DataFlair\r\n> g <- 53.5 #Assigning a decimal value to g\r\n> g #Printing the value of g<\/pre>\n
> class(g) #Printing the class name of g<\/pre>\n
![\"R](\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2017\/09\/Numeric-Data-Type-in-R-programming.png\")
<\/a><\/p>\n2. Integer Data Type<\/h4>\n
\n
> a <- as.integer(4) #Using as.integer()\r\n> a #printing a<\/pre>\n
> typeof(a) #checking data-type of a<\/pre>\n
\n
> b <- 4L #Appending L to 4 \r\n> b #printing b<\/pre>\n
> typeof(b) #Checking data-type of b<\/pre>\n
![\"R](\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2017\/09\/integer_data_type_in_r.png\")
<\/a><\/p>\n3. Character Data Type<\/h4>\n
\n
> x = \"DataFlair\"\r\n> x<\/pre>\n
> typeof(x)<\/pre>\n
\n
> y = as.character(42) \r\n> y<\/pre>\n
> typeof(y)<\/pre>\n
![\"R](\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2017\/09\/Character-Data-Type-in-R.png\")
<\/a><\/p>\n4. Logical Data Type<\/h4>\n
a =3; b =6 #sample values\r\ng = a>b # is a larger than b?\r\ng #print the logical value<\/pre>\n
![\"R](\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2017\/09\/Logical-Data-Type-in-R.png\")
<\/a><\/p>\nHow to Create Vector in R?<\/h3>\n
> x <- c(1,2,3,4)\r\n> x<\/pre>\n
![\"How](\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2017\/09\/Creating-R-vectors.png\")
<\/a><\/p>\nWays to Create Vectors in R<\/h4>\n
> x <- 1:5\r\n> x<\/pre>\n
> y <- 5:-5\r\n> y<\/pre>\n
![\"Create](\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2017\/09\/Create-R-vector-using-the-operator-.png\")
<\/a><\/p>\n\n
> seq(2,4, by = 0.4)<\/pre>\n
\n
> seq(1,4, length.out = 5)<\/pre>\n
![\"Create](\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2017\/09\/Create-R-vector-using-seq-function-.png\")
<\/a><\/h4>\nHow to Access Elements of R Vectors?<\/h3>\n
1. Indexing with Integer Vector<\/h4>\n
> x<\/pre>\n
> x[2] #indexing with vector<\/pre>\n
![\"](\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2017\/09\/Indexing-with-Integer-Vector-in-R.png\")
<\/a><\/p>\n2. Indexing with Character Vector<\/h4>\n
> x <- c(\"One\" = 1, \"Two\" = 2, \"Three\" = 3)\r\n> x[\"Two\"]<\/pre>\n
![\"](\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2017\/09\/Indexing-with-Character-Vector-in-R.png\")
<\/a><\/p>\n3. Indexing with Logic Vector<\/h4>\n
> a <- c(1,2,3,4)\r\n> a[c(TRUE, FALSE, TRUE, FALSE)]<\/pre>\n
![\"R](\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2017\/09\/Logic-indexing-in-R.png\")
<\/a><\/p>\nOperations in R\u00a0Vector<\/h2>\n
1. Combining Vector in R<\/h4>\n
> #Author DataFlair\r\n> n = c(1, 2, 3, 4) \r\n> s = c(\"Hadoop\", \"Spark\", \"HIVE\", \"Flink\")\r\n> c(n,s)<\/pre>\n
![\"Combine](\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2017\/09\/Combining-vector-in-R.png\")
<\/a><\/p>\n2. Arithmetic Operations on Vectors in R<\/h4>\n
> #Author DataFlair\r\n> a = c (1, 3)\r\n> b = c (1, 3)\r\n> a + b #Addition<\/pre>\n
> a - b #Subtraction<\/pre>\n
> a \/ b #Division<\/pre>\n
> a %% b #Remainder Operation\r\n<\/pre>\n
![\"R](\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2017\/09\/Arithmetic-Operations-on-Vectors-in-R.png\")
<\/a><\/p>\n3. Logical Index Vector in R<\/h4>\n
> #Author DataFlair\r\n> S = c(\"bb\", \"cc\")\r\n> L = c(TRUE, TRUE) #Defining our Logical Vector\r\n> S[L] #This will return elements of vector S that corrospond to logic vector L<\/pre>\n
![\"R](\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2017\/09\/Logical-Index-Vector-in-R.png\")
<\/a><\/p>\n4. Numeric Index<\/h4>\n
> # Author DataFlair\r\n> x <- c(\"aa\", \"bb\", \"cc\", \"dd\", \"ee\") #Creating our vector\r\n> x[3]<\/pre>\n
> x[-2] #Using Negative Index<\/pre>\n
> x[15] #Using an out-of-range index<\/pre>\n
![\"Numeric](\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2017\/09\/Numeric-Index.jpg\")
<\/a><\/p>\n5. Duplicate Index<\/h4>\n
> # Author DataFlair\r\n> s = c(\"aa\", \"bb\", \"cc\", \"dd\", \"ee\")\r\n> s[c(2,3,3)]<\/pre>\n
![\"R](\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2017\/09\/Duplicate-Index-in-R.png\")
<\/a><\/p>\n6. Range Indexes<\/h4>\n
> # Author DataFlair\r\n> s = c(\"aa\", \"bb\", \"cc\", \"dd\", \"ee\")\r\n> s[1:3]<\/pre>\n
![\"R](\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2017\/09\/Range-Indexes-in-R.png\")
<\/a><\/p>\n7. Out-of-order Indexes<\/h4>\n
> s [ c (2, 1, 3) ]<\/pre>\n
![\"Out-of-order](\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2017\/09\/Out-of-order-Indexes-in-R.png\")
<\/a><\/p>\n8. Named Vectors Members\u00a0<\/strong><\/h4>\n
> v = c(\"Hadoop\", \"Spark\")\r\n> v<\/pre>\n
> names(v) = c(\"First\", \"Second\")\r\n> v<\/pre>\n
> v[\"First\"]<\/pre>\n
> v[c(\"Second\", \"First\")]<\/pre>\n
![\"R](\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2017\/09\/Named-Vectors-Members-in-r.png\")
<\/a><\/p>\n