# Data Types in R

In R programming, there are five basic data types. Also, everything in R is an object, so we will refer to these data types as classes of objects. So, these five types of objects are:

- Numeric
- Integer
- Complex
- Logical
- Character

Let's briefly look at each of these.

### Numeric

In R, decimal values such as `8.5`

are numeric. You can assign a numeric value to a variable and then that variable will be of numeric data type.

For any variable or object, you can check it's data type by using the `class`

command.

```
> # Assign a decimal value to x
>
> x <- 8.5
>
> # Print the value of x
> x
[1] 8.5
>
> # Print the class name of x
>
> class(x)
[1] "numeric"
>
```

### Integer

Integers are the natural numbers such as 1, 2, 3, etc. In R, when you assign a number to a variable, it is by default of the numeric class type. In order to create an integer variable, we use a function called `as.integer()`

. This ensures that the variable created is indeed an integer.

```
> #Assign a value to a variable
> x <- 8
>
> #check the class type of x
> class(x)
[1] "numeric"
>
> # You will notice that it is numeric.
>
> # Use the as.integer() function to create an integer
>
> y <- as.integer(8)
>
> #check the class type of yx
> class(y)
[1] "integer"
>
> > # It is an integer now
>
```

### Complex

In R, a complex value is defined using a pure imaginary value `<em>i</em>`

.

```
> #Assign a complex value to a variable
> x = 1 + 2i
>
> #Print the complex value x
> x
[1] 1+2i
>
> #Print the class of x
> class(x)
[1] "complex"
>
```

### Logical

Logical values are boolen values (`TRUE`

or `FALSE`

) often created by comparison between variables.

```
> #Create sample variables
> x <- 5
> y <- 7
>
> #Check if y is less than x
> z <- y < x
>
> # z will have a logical value. Let's print it
>
> z
[1] FALSE
>
> #Print the class of z
> class(z)
[1] "logical"
>
```

### Character

Character values are string or text values. We can create a character type variable by assigning a string to the variable. Notice the use of double quotes.

```
> #Create a character variable
>
> x <-"John Doe"
>
> #Print the character string
>
> x
[1] "John Doe"
>
```

If we have an object of some other data type (e.g., numeric), we can convert it into character type using the `as.character()`

function.

```
> #Create a numeric variable
>
> x <- 8.75
>
> #Print the variable x
>
> x
[1] 8.75
>
> #Print the class of x
>
> class(x)
[1] "numeric"
>
> #convert x into a character value
>
> y <- as.character(x)
>
> #Print the variable y
>
> y
[1] "8.75"
>
> #Print the class of y
>
> class(y)
[1] "character"
>
```

### Standard Logical Operations

We can perform standard logical operations such as "&" (and), "|" (or), and "!" (negation) on logical values in R.

```
> x = TRUE; y = FALSE
> x & y # Checks that both x AND y are true
[1] FALSE
> x | y # Checks that either x OR y is true
[1] TRUE
> !x # Returns the negation of x
[1] FALSE
>
```

### Standard String Operations

We can easily perform basic string operations in R such as concatenation, or creating readable strings.

```
> #Define sample character variables
> fname <- "John"
> lname <- 'Doe'
>
> # Concatenate strings using paste function
> paste(fname, lname)
[1] "John Doe"
>
> #Create a readable string using sprintf() function
> #Use %s for strings and %d for numeric values
>
> sprintf("His first name is %s and last name is %s",fname,lname)
[1] "His first name is John and last name is Doe"
>
> # Extract a substr from a long string. In the following example, we
> # are extracting stock symbol from text
>
> substr("Google's stock symbol is GOOG", start=26, stop=29)
[1] "GOOG"
>
> #Replace the first occurance of a word in a string by another word.
>
> sub("John","Sam","His first name is John")
[1] "His first name is Sam"
>
```

The sprintf() function allows you to create strings as output using formatted data. For example:

```
sprintf("I go for a walk at %s:%s%s a.m.", 7, 0, 5)
```

This will output:

```
#> [1] "I go for a walk at 7:05 a.m."
```

See the special syntax `%s`

. Each `%`

is referred to as a slot, which is basically a placeholder for a variable that will be formatted. The values after the comma are the variables or values that will be filled in each slot.

### Getting Help

We can find many more functions for these data types in the R documentation. For each function, the help also provides details about how to use these functions. For example, you can get help for `sprintf()`

function by using the command `help('sprintf')`

. The documentation will open in the help window (bottom right).

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