R Tutorial

Fundamentals of R

Variables

Input and Output

Decision Making

Control Flow

Functions

Strings

Vectors

Lists

Arrays

Matrices

Factors

DataFrames

Object Oriented Programming

Error Handling

File Handling

Packages in R

Data Interfaces

Data Visualization

Statistics

Machine Learning with R

if statement in R

The if statement in R allows you to conditionally execute a block of code. It's a foundational element of any programming language, allowing for decision-making in your scripts or functions.

In this tutorial, we'll explore:

Basic if Statement
Combining Conditions
Common Pitfalls

1. Basic `if` Statement

The basic structure of an if statement is:

if (condition) {
    # code to execute if condition is TRUE
}

The condition inside the parentheses is evaluated, and if it's TRUE, the code block within the curly braces {} will be executed.

Example:

x <- 10

if (x > 5) {
    print("x is greater than 5")
}

When you run this code, it will output: x is greater than 5

2. Combining Conditions

You can combine multiple conditions using logical operators:

& (and): Both conditions have to be TRUE
| (or): At least one condition has to be TRUE
! (not): Reverses the truth value of the condition

Example:

x <- 7
y <- 15

if (x > 5 & y < 20) {
    print("Both conditions are true!")
}

if (x < 5 | y < 20) {
    print("At least one condition is true!")
}

This will output:

[1] "Both conditions are true!"
[1] "At least one condition is true!"

3. Common Pitfalls

Ensure your condition returns a single logical value: If the condition in the if statement returns a vector with more than one value, R will warn you and only consider the first element.
```
vec <- c(TRUE, FALSE)
if (vec) {
    print("This will give a warning!")
}
```
You'll get: Warning: the condition has length > 1 and only the first element will be used
Comparing for exact equality with floating-point numbers: Due to the way floating-point arithmetic works, it's often not recommended to test for exact equality (==) with floating-point numbers. Instead, you can use a tolerance approach or the all.equal() function.
```
x <- sqrt(2)^2
if (!all.equal(x, 2)) {
    print("This won't print, because x is essentially 2!")
}
```

Conclusion

The if statement in R allows for decision-making based on conditions, enabling you to create dynamic scripts that respond to varying inputs or situations. It's essential to remember that the condition in an if statement should ideally evaluate to a single logical value. Using combined conditions and being aware of common pitfalls ensures effective and error-free conditional programming in R.

R code examples for using if statements:

# Simple if statement
x <- 10
if (x > 5) {
  print("x is greater than 5")
}

Comparing values with if statement in R:

# Comparing values with if statement
a <- 7
b <- 5
if (a > b) {
  print("a is greater than b")
}

Logical operators in if statements in R:

# Using logical operators in if statement
age <- 25
if (age >= 18 & age <= 60) {
  print("Person is between 18 and 60 years old")
}

Using if statements for control flow in R:

# Using if statements for control flow
temperature <- 28
if (temperature > 30) {
  print("It's a hot day!")
} else if (temperature > 20) {
  print("It's a pleasant day.")
} else {
  print("It's a cold day.")
}

Vectorized if statement in R programming:

# Vectorized if statement using ifelse()
vector_x <- c(2, 7, 10, 3, 8)
result_vector <- ifelse(vector_x > 5, "Greater than 5", "Less than or equal to 5")

Nested if statements in R:

# Nested if statements
x <- 10
y <- 8
if (x > 5) {
  if (y > 5) {
    print("Both x and y are greater than 5")
  } else {
    print("x is greater than 5, but y is not greater than 5")
  }
} else {
  print("x is not greater than 5")
}

if statement in R

1. Basic if Statement

Example:

2. Combining Conditions

Example:

3. Common Pitfalls

Conclusion

1. Basic `if` Statement