Control Statements: If - Conditional Block

Why Learn Control Statements in Data Analytics?

Imagine you are developing a credit approval system for a bank. You have a dataset of customer credit scores. You need to categorize each applicant automatically based on their score:

• Score of 700 or above: Status is "Approved".
• Score between 600 and 699: Status is "Under Review".
• Score below 600: Status is "Denied".

If you write a simple sequential script, it will execute every line of code without stopping to think. To make decisions, you must deviate from this straight path. You need Control Statements (if, else if, and else) to guide the program down different paths depending on each applicant's credit score.

1. Relational Operators in R

R uses relational operators to compare values. Every comparison returns a logical value: TRUE or FALSE.

# Testing comparisons
age <- 18
is_adult <- age >= 18
print(is_adult)  # TRUE

2. Logical Operators in R

R has two types of logical operators: short-circuiting (used in if conditions) and element-wise (used for data filtering, which we will learn later).

For if statements, always use the short-circuiting double operators:

Short-Circuit Evaluation

• && stops at the first FALSE: If the left side is FALSE, R knows the entire expression must be FALSE and skips evaluating the right side.
• || stops at the first TRUE: If the left side is TRUE, R knows the entire expression must be TRUE and skips evaluating the right side.

3. The if Statement Syntax

In R, conditions must be enclosed in parentheses ( ), and the block of code to run must be enclosed in curly braces { }.

score <- 750

if (score >= 700) {
  print("Status: Approved")
}

4. Multi-Way Conditionals: else if and else

To handle multiple branches, chain them together using else if and else:

score <- 650

if (score >= 700) {
  print("Status: Approved")
} else if (score >= 600) {
  print("Status: Under Review")
} else {
  print("Status: Denied")
}

if (score >= 700) {
  print("Approved")
}
else { # This will throw a syntax error in R!
  print("Denied")
}

5. Inline Conditionals: ifelse() vs. if_else()

For simple conditional assignments, writing a full multi-line if/else block can be verbose. R offers vectorized inline functions for this.

Base R: ifelse()

The built-in ifelse(test, yes, no) evaluates a test condition, returning the yes value if TRUE and the no value if FALSE:

score <- 550
status <- ifelse(score >= 600, "Pass", "Fail")
print(status) # "Fail"

Base R's ifelse() is flexible and will automatically coerce data types if they differ between the yes and no values (e.g., mixing characters and numbers).

Tidyverse: if_else()

The dplyr package (part of the tidyverse) provides a stricter alternative called if_else(condition, true, false, missing = NULL):

library(dplyr)
score <- 650
# Returns "large" if >600, else "small"
status <- if_else(score > 600, "large", "small")
print(status)

Hands-on Exercises

Exercise 1: Risk Profiling

In investment analysis, a client's risk tolerance is determined by their age. Write R code to:

1. Assign age <- 62.
2. Write an if / else if / else structure:
   • If age is under 35, print "Risk Profile: Aggressive".
   • If age is between 35 and 60, print "Risk Profile: Moderate".
   • If age is above 60, print "Risk Profile: Conservative".

# Write your code below and click Run Code

age <- 62

if (age < 35) {
  print("Risk Profile: Aggressive")
} else if (age <= 60) {
  print("Risk Profile: Moderate")
} else {
  print("Risk Profile: Conservative")
}

Exercise 2: Premium Pricing Logic

A subscription service charges $15 for normal users, but offers a discount based on two criteria:

• If the user is a student OR is under 18, the subscription price is $10.
• Otherwise, the price is $15.

Write R code to:

1. Set is_student <- TRUE and age <- 22.
2. Calculate the price using if / else with logical operators.
3. Print the final price.

# Write your code below and click Run Code

is_student <- TRUE
age <- 22

if (is_student || age < 18) {
  price <- 10
} else {
  price <- 15
}

print(paste("Subscription Price: $", price))