The R language is widely used in various fields like data science, scientific research, & statistical data analysis.

All of these fields deal with a large number of data sets, big data, or massive databases. Moreover, the R programming language is quite popular in data analytics and data engineering, where data is handled and molded according to underlying use cases.

R provides various data structures to store and work with massive datasets. One of these frequently used data structures is vectors. Let us begin by elaborating on the **vector data structure in R**.

## What is a vector?

Vectors are the most fundamental objects in R. Simply these are R lists of similar items. In addition, vectors are similar to arrays in C or Java languages.

They act as a container that can hold different entities of the same data type. One significant difference between vectors in **R** and similar data structures (arrays, lists) in other languages is that indexing of vectors starts from **1** rather than **0**.

## Types of vectors in R

Vectors in R come in six different types. These types differ based on the data types of objects which they store. These types are as follows.

**Logical Vectors**: stores logical data types like`[TRUE, TRUE, FALSE, TRUE]`

**Integer Vector**: stores integers like`[23, 10, 26, 5]`

**Double Vectors**: store doubles or floating point numbers like`[1.2, 2.6, 2.5, 7.5]`

**Complex Vectors:**store complex numbers like`[1 + 1i, 2 - 1i, 5 + 1i, 3 - 2i]`

**Character Vectors:**store variables of character data type like`"ALGOIDEAS"`

**Raw Vectors**store fixed-length byte sequences like`[0x6A, 0x7E, 0x12, 0x00]`

These are some types of vectors available in **R**. Now, Let’s look at how to create a vector in **R** to store the data points. The data points will be stored in contiguous memory locations.

## How to create vectors in R?

R offers multiple methods or ways to create vectors. Some of these are explained below.

### Colon Operator

The colon operator (`:`

) is used to create vectors of any type by defining a sequence whose starting point is on the left side of the colon operator, and the final point is on the right side. It will create a vector of the defined sequence, and the difference between every consecutive series term will be **1**.

`myVector <- 10 : 20`

It will create a vector named `myVector`

of sequence starting from `10`

and ending at `20`

(including boundary values). The vector created is `[10 11 12 13 14 15 16 17 18 19 20]`

.

`myVector <- 10.5 : 20.4`

It creates a vector of sequence starting from `10.5`

and ending at `20.4`

. The vector created is `[10.5 11.5 12.5 13.5 14.5 15.5 16.5 17.5 18.5 19.5]`

.

`Seq()`

Function

The sequence function can also be used to create a vector by defining a sequence. The difference between this operator and the colon operator is that we can determine the incrementing jump between every consecutive series term.

`myVector <- seq(10, 15, by = 0.5)`

It will create a vector `myVector`

starting from `10`

and ending at `15`

. Each consecutive value will differ by `0.5`

. The vector created is `[10.0 10.5 11.0 11.5 12.0 12.5 13.0 13.5 14.0 14.5 15.0]`

.

`c()`

Function

In R, programmers can utilize the `c()`

function to provide the specific values they want to store in the vector. These values still need to be of the same data type. If at least one value in `c()`

is a character value, then all other values are converted to character data type and stored in the vector.

`v <- c(1, 6, 9, -2, 55, 74, 21)`

`c()`

will create a vector `v`

containing argument values as `[1, 6, 9, -2, 55, 74, 21]`

.