R - Data Types

Generally, while doing programming in any programming language, you need to use various variables to store various information. Variables are nothing but reserved memory locations to store values. This means that, when you create a variable you reserve some space in memory.

You may pke to store information of various data types pke character, wide character, integer, floating point, double floating point, Boolean etc. Based on the data type of a variable, the operating system allocates memory and decides what can be stored in the reserved memory.

In contrast to other programming languages pke C and java in R, the variables are not declared as some data type. The variables are assigned with R-Objects and the data type of the R-object becomes the data type of the variable. There are many types of R-objects. The frequently used ones are −

Vectors

Lists

Matrices

Arrays

Factors

Data Frames

The simplest of these objects is the vector object and there are six data types of these atomic vectors, also termed as six classes of vectors. The other R-Objects are built upon the atomic vectors.

v <- TRUE 
print(class(v))

[1] "logical" 

v <- 23.5
print(class(v))

[1] "numeric"

v <- 2L
print(class(v))

[1] "integer"

v <- 2+5i
print(class(v))

[1] "complex"

v <- "TRUE"
print(class(v))

[1] "character"

v <- charToRaw("Hello")
print(class(v))

[1] "raw" 

In R programming, the very basic data types are the R-objects called vectors which hold elements of different classes as shown above. Please note in R the number of classes is not confined to only the above six types. For example, we can use many atomic vectors and create an array whose class will become array.

Vectors

When you want to create vector with more than one element, you should use c() function which means to combine the elements into a vector.

# Create a vector.
apple <- c( red , green ,"yellow")
print(apple)

# Get the class of the vector.
print(class(apple))

[1] "red"    "green"  "yellow"
[1] "character"

# Create a pst.
pst1 <- pst(c(2,5,3),21.3,sin)

# Print the pst.
print(pst1)

[[1]]
[1] 2 5 3

[[2]]
[1] 21.3

[[3]]
function (x)  .Primitive("sin")

# Create a matrix.
M = matrix( c( a , a , b , c , b , a ), nrow = 2, ncol = 3, byrow = TRUE)
print(M)

     [,1] [,2] [,3]
[1,] "a"  "a"  "b" 
[2,] "c"  "b"  "a"

# Create an array.
a <- array(c( green , yellow ),dim = c(3,3,2))
print(a)

, , 1

     [,1]     [,2]     [,3]    
[1,] "green"  "yellow" "green" 
[2,] "yellow" "green"  "yellow"
[3,] "green"  "yellow" "green" 

, , 2

     [,1]     [,2]     [,3]    
[1,] "yellow" "green"  "yellow"
[2,] "green"  "yellow" "green" 
[3,] "yellow" "green"  "yellow"  

# Create a vector.
apple_colors <- c( green , green , yellow , red , red , red , green )

# Create a factor object.
factor_apple <- factor(apple_colors)

# Print the factor.
print(factor_apple)
print(nlevels(factor_apple))

[1] green  green  yellow red    red    red    green 
Levels: green red yellow
[1] 3

# Create the data frame.
BMI <- 	data.frame(
   gender = c("Male", "Male","Female"), 
   height = c(152, 171.5, 165), 
   weight = c(81,93, 78),
   Age = c(42,38,26)
)
print(BMI)

  gender height weight Age
1   Male  152.0     81  42
2   Male  171.5     93  38
3 Female  165.0     78  26