# What are the Data Types in the R programming language?

## What are the Data Types in the R programming language?

**DATA TYPES: **

It is a data item used by the programming language to perform the operations.

The types of data types used in the R programming language are:

- Vectors
- Data Frames
- Array
- Matrix
- Lists
- Factor

R language supports all kinds of primitive data types such as char, integer, double, and complex who can process a single value.

**Vector:**The complex, character, numeric, integer, and logical are varieties of the vector. Vector is a collection of the same types in a one-dimensional approach. The c() function is used to concatenate all the elements in a single vector. The most used vector functions are length(), is.null(), rep(), class(), is.logical().

**Examples of vector**

Create a vector with more than one element. For this, we use the c() function to combine all the vector elements into one.

**color < - c('pink', 'green', 'orange')**

# print() function is used to print the vector

**print(color)**

**OUTPUT:**

[1] "pink" "green" "orange"

# class() function is used to obtain the class of the vector

**print(class(color)) **

**OUTPUT:**

[1] "character"

**Data Frames:**The data items represent in tabular form in data frames data type or can also say it is in a two-dimensional form with an equal length. The data items can be different in columns, but the length of data items should be the same in all the rows. It is a list of vectors of equal length. The data.frame() function is used to create the data frame.

**Example of Data Frames:**

Y <- data.frame(name = c("John", "Joe", "Sandy"), age=c("32", "19", "25"))

#print data frame

**print(Y)**

**OUTPUT:**

1 John 32

2 Joe 19

3 Sandy 25

**Array:**Array is also two-dimensional data set. Unlike matrix, the number of rows and columns are equal. The array() function is used to create an array.

**Example of Array**

color <- array(c('pink','blue'),dim = c(3,3,2))

# print array

**print(color)**

**OUTPUT**

, , 1

[,1] [,2] [,3]

[1,] "pink" "blue" "pink"

[2,] "blue" "pink" "blue"

[3,] "pink" "blue" "pink"

, , 2

[,1] [,2] [,3]

[1,] "blue" "pink" "blue"

[2,] "pink" "blue" "pink"

[3,] "blue" "pink" "blue"

**Matrices:**It is a two-dimensional data set that has rows and columns. Three ways to create a matrix are:

-- Using matrix function

-- Binding vectors

-- Converting the vector into the matrix

The Matrix() function is used to create the matrix.

**Example in Matrices**

Mat = matrix( c('a','a','b','c','b','a'), nrow = 2, ncol = 3, byrow = TRUE)

#print matrices

**print(Mat)**

**OUTPUT**

[,1] [,2] [,3]

[1,] "a" "a" "b"

[2,] "c" "b" "a"

**Lists:**It contains objects and elements. Elements can be arrays, matrices, characters, or else. It can also contain another list.

**Example of lists**

lists_example <- list(c(2,5,3),21.3,sin)

#print lists

**print(lists_example)**

**OUTPUT**

[[1]]

[1] 2 5 3

[[2]]

[1] 21.3

[[3]]

function (x) .Primitive("sin")

**Factor:**factor() function is used to create factor. They are the r-objects. The factor keeps the vector and labels. Labels are characters of any type, such as numeric, character, or boolean. It is useful in statistical modeling.

**Example of Factor**

colors <- c('green','green','yellow','red','red','red','green')

# Create a factor object.

**factor_colors <- factor(colors)**

# Print the factor.

**print(factor_color)**

**print(nlevels(factor_color))**

**OUTPUT**

[1] green green yellow red red red green

Levels: green red yellow

[1] 3