Basic data types

R Programming works with numerous data types, including

• Scalars
• Vectors (numerical, character, logical)
• Matrices
• Data frames
• Lists

Basics types

• 4.5 is a decimal value called numerics.
• 4 is a natural value called integers. Integers are also numerics.
• TRUE or FALSE is a Boolean value called logical.
• The value inside " " or ’ ’ are text (string). They are called characters.

We can check the type of a variable with the class function

• Example 1:
• Example 2:
• Example 3:

# Declare variables of different types
# Numeric
x <- 28
class(x)

## [1] "numeric"

# String
y <- "R is Fantastic"
class(y)

## [1] "character"

# Boolean
z <- TRUE
class(z)

## [1] "logical"

Variables

Variables store values and are an important component in programming, especially for a data scientist. A variable can store a number, an object, a statistical result, vector, dataset, a model prediction basically anything R outputs. We can use that variable later simply by calling the name of the variable.

To declare a variable, we need to assign a variable name. The name should not have space. We can use _ to connect to words.

To add a value to the variable, use <- or =.

Here is the syntax:

# First way to declare a variable:  use the `<-`
name_of_variable <- value
# Second way to declare a variable:  use the `=`
name_of_variable = value

In the command line, we can write the following codes to see what happens:

• Example 1:
• Example 2:
• Example 3:

# Print variable x
x <- 42

y  <- 10
y

## [1] 10

# We call x and y and apply a subtraction
x - y

## [1] 32

Vectors

A vector is a one-dimensional array. We can create a vector with all the basic data type we learnt before. The simplest way to build a vector in R, is to use the c command.

• Example 1:
• Example 2:
• Example 3:
• Example 4:
• Example 5:
• Example 6:

# Numerical
vec_num <- c(1, 10, 49)
vec_num

## [1]  1 10 49

# Character 
vec_chr <- c("a", "b", "c")
vec_chr

## [1] "a" "b" "c"

# Boolean 
vec_bool <-  c(TRUE, FALSE, TRUE)
vec_bool

## [1]  TRUE FALSE  TRUE

# Create the vectors
vect_1 <- c(1, 3, 5)
vect_2 <- c(2, 4, 6)
# Take the sum of A_vector and B_vector
sum_vect <- vect_1 + vect_2
# Print out total_vector
sum_vect

## [1]  3  7 11

# Slice the first five rows of the vector
slice_vector <- c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)
slice_vector[1:5]

## [1] 1 2 3 4 5

# Faster way to create adjacent values
c(1:10)

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

Arithmetic Operators

We will first see the basic arithmetic operations in R. The following operators stand for:

You can easily copy and paste the above R code into Rstudio Console. The output is displayed after the character #. For instance, we write the code print(‘Hello world’) the output will be ##[1] “Hello world”.

The ## means we print an output and the number in the square bracket ([1]) is the number of the display

The sentences starting with # annotation. We can use # inside an R script to add any comment we want. R won’t read it during the running time.

• Example 1:
• Example 2:
• Example 3:
• Example 4:
• Example 5:

# An addition
3 + 4

## [1] 7

# A multiplication
3 * 5

## [1] 15

# A division
(5 + 5) / 2

## [1] 5

# Exponentiation
2^5

## [1] 32

# Modulo
28 %% 6

## [1] 4

Logical Operators

With logical operators, we want to return values inside the vector based on logical conditions. Following is a detailed list of logical operators available in R

The logical statements in R are wrapped inside the [ ]. We can add many conditional statements as we like but we need to include them in a parenthesis. We can follow this structure to create a conditional statement:

variable_name[(conditional_statement)]

With variable_name referring to the variable, we want to use for the statement. We create the logical statement i.e. variable_name > 0. Finally, we use the square bracket to finalize the logical statement. Below, an example of a logical statement.

• Example 1:
• Example 2:
• Example 3:

# Create a vector from 1 to 10
logical_vector <- c(1:10)
logical_vector > 5

##  [1] FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE

# Print value strictly above 5
logical_vector[(logical_vector > 5)]

## [1]  6  7  8  9 10

# Print 5 and 6
logical_vector <- c(1:10)
logical_vector[(logical_vector > 4) & (logical_vector < 7)]

## [1] 5 6