**Method 1: Using the c() function**

To **create** a **vector** in **R**, the easiest way is to use the **“c()”** function. The **c()** function combines its arguments.

```
rv <- c(11, 46)
print(rv)
```

**Output**

`[1] 11 46`

You can see that we created a vector **rv** using the **c()** function. It has two elements, 11 and 46.

To **get** the **length** of a **vector**, use the **length()** function.

```
rv <- c(11, 46)
print(length(rv))
```

**Output**

`[1] 2`

**Method 2: Using**** the : operator**

The **colon(:) operator** helps us create a vector of consecutive numbers.

```
rv2 <- 1:11
print(rv2)
print(length(rv2))
```

**Output**

```
[1] 1 2 3 4 5 6 7 8 9 10 11
[1] 11
```

Using the colon operator in this example, we created a vector of consecutive numbers.

**Create a regular sequence vector using the seq() function**

The seq() is a built-in R function that generates the general or regular sequences from the given inputs.

```
rv3 <- seq(1, 25, by = 5)
print(rv3)
print(length(rv3))
```

**Output**

```
[1] 1 6 11 16 21
[1] 5
```

To create a regular sequence vector, you can use the** “seq()”** function and declare the step size using the **by **parameter.

**Method 3: Using the assign() function**

The **assign()** is a built-in **R** function that assigns a value to a name in an environment.

`print(assign("rv4", c(19, 21, 11, 46)))`

**Output**

`[1] 19 21 11 46`

You can see that we created a vector that has four elements using the **“assign()”** function.

That’s it.

Krunal Lathiya is a Software Engineer with over eight years of experience. He has developed a strong foundation in computer science principles and a passion for problem-solving. In addition, Krunal has excellent knowledge of Data Science and Machine Learning, and he is an expert in R Language.