R-Vectors

R Vectors are the same as the arrays in R language which are used to hold multiple data values of the same type. One major key point is that in R Programming Language the indexing of the vector will start from '1' and not from '0'. We can create numeric vectors and character vectors as well. 

1. Creating a vector in R

A vector is a basic data structure that represents a one-dimensional array. to create a array we use the "c" function which the most common method use in R Programming Language. We can also use seq() function or use colons ":" also as shown in the example.

X<- c(61, 4, 21, 67, 89, 2)
cat('using c function', X, '\n')

Y<- seq(1, 10, length.out = 5) 
cat('using seq() function', Y, '\n') 

Z<- 2:7
cat('using colon', Z)

Output:

using c function 61 4 21 67 89 2
using seq() function 1 3.25 5.5 7.75 10
using colon 2 3 4 5 6 7

2. Types of R vectors

Vectors are of different types which are used in R. Following are some of the types of vectors:

2.1 Numeric vectors

Numeric vectors are those which contain numeric values such as integer, float, etc. The L suffix in R is used to specify that a number is an integer and not a numeric (floating-point) value.

v1 <- c(4, 5, 6, 7)
typeof(v1)

v2 <- c(1L, 4L, 2L, 5L)
typeof(v2)

Output:

[1] "double"
[1] "integer"

2.2 Character vectors

Character vectors in R contain alphanumeric values and special characters. In R, when a vector contains elements of mixed types (like characters and numbers), R automatically coerces the entire vector to a single type. Since characters are more general than numbers in R, the vector is coerced to a character vector.

v1 <- c('geeks', '2', 'hello', 57)
typeof(v1)

Output:

[1] "character"

2.3 Logical vectors

Logical vectors in R contain Boolean values such as TRUE, FALSE and NA for Null values. In R, NA is a special value used to represent missing or undefined data. When used in a logical vector, NA is treated as a logical value because it is specifically designed to work with logical vectors and other types of data.

v1 <- c(TRUE, FALSE, TRUE, NA)
typeof(v1)

Output:

[1] "logical"

3. Length of R vector

In R, the length of a vector is determined by the number of elements it contains. we can use the length() function to retrieve the length of a vector.

x <- c(1, 2, 3, 4, 5)
length(x)

y <- c("apple", "banana", "cherry")
length(y)

z <- c(TRUE, FALSE, TRUE, TRUE)
length(z)

Output:

> length(x)
[1] 5

> length(y)
[1] 3

> length(z)
[1] 4

4. Accessing R vector elements

Accessing elements in a vector is the process of performing operation on an individual element of a vector. There are many ways through which we can access the elements of the vector. The most common is using the '[]', symbol.

Note: Vectors in R are 1 based indexing unlike the normal C, python, etc format.

X <- c(2, 5, 18, 1, 12)
cat('Using Subscript operator', X[2], '\n')

Y <- c(4, 8, 2, 1, 17)
cat('Using combine() function', Y[c(4, 1)], '\n')

Output:

Using Subscript operator 5
Using combine() function 1 4

5. Modifying a R vector

Modification of a Vector is the process of applying some operation on an individual element of a vector to change its value in the vector. There are different ways through which we can modify a vector: 

X <- c(2, 7, 9, 7, 8, 2)

X[3] <- 1
X[2] <- 9
cat('subscript operator', X, '\n')

X[1:5] <- 0
cat('Logical indexing', X, '\n')

X <- X[c(3, 2, 1)]
cat('combine() function', X)

Output:

subscript operator 2 9 1 7 8 2
Logical indexing 0 0 0 0 0 2
combine() function 0 0 0

6. Deleting a R vector

Deletion of a Vector is the process of deleting all of the elements of the vector. This can be done by assigning it to a NULL value. 

M <- c(8, 10, 2, 5)

M <- NULL

print(cat('Output vector', M, "\f"))

Output:

Output vector NULL

7. Sorting elements of a R Vector

sort() function is used with the help of which we can sort the values in ascending or descending order. 

X <- c(8, 2, 7, 1, 11, 2)

A <- sort(X)
cat('ascending order', A, '\n')

B <- sort(X, decreasing = TRUE)
cat('descending order', B)

Output:

ascending order 1 2 2 7 8 11
descending order 11 8 7 2 2 1