Syntax and Control Flow

Week 4

INSTITUT TEKNOLOGI SAINS BANDUNG

IDENTITY CARD

Name : Dhefio Alim Muzakki

Student ID : 52250014

Major : Data Science

Lecturer : Mr. Bakti Siregar, M.Sc., CDS.

library(tidyverse)
library(readr)
library(ggplot2)
library(dplyr)
library(ggridges)
library(knitr)
library(DT)

Introduction

Conditional statements and loops are basic concepts in programming. Conditional statements help a program make decisions based on certain conditions, while loops allow commands to be repeated automatically.

These concepts are useful in data analysis because they help process data efficiently. In this practicum, conditional statements and loops are applied using the R programming language with an employee dataset.

Conditional statements are used to calculate employee bonuses based on performance, and loops are used to display and analyze the data. This practicum helps students understand the basic use of if–else statements, for loops, and while loops in programming.

Objective

Understand and implement conditional statements.
Apply loops to analyze a dataset.

Conditional Statements

Conditional statements are used to make decisions in programming. In this practicum, conditional statements are used to determine employee bonuses based on their performance.

Dataset

employees <- data.frame(
  ID = c(1,2,3,4,5),
  Name = c("Bagas","Joan","Alya","Dwi","Nabil"),
  Age = c(25,30,27,35,40),
  Salary = c(5000,7000,6500,10000,12000),
  Position = c("Staff","Supervisor","Staff","Manager","Director"),
  Performance = c("Good","Very Good","Average","Good","Very Good")
)

knitr::kable(employees, caption = "Employee Dataset")

Employee Dataset
ID	Name	Age	Salary	Position	Performance
1	Bagas	25	5000	Staff	Good
2	Joan	30	7000	Supervisor	Very Good
3	Alya	27	6500	Staff	Average
4	Dwi	35	10000	Manager	Good
5	Nabil	40	12000	Director	Very Good

Bonus Calculation

Employee bonuses are calculated based on performance levels:

Very Good : 20% of salary
Good : 10% of salary
Average : 5% of salary

calculate_bonus <- function(performance, salary) {

  if (performance == "Very Good") {
    bonus <- salary * 0.20
  } else if (performance == "Good") {
    bonus <- salary * 0.10
  } else {
    bonus <- salary * 0.05
  }

  return(bonus)

}

employees$Bonus <- mapply(calculate_bonus,
                          employees$Performance,
                          employees$Salary)

knitr::kable(employees, caption = "Employee Dataset with Bonus")

Employee Dataset with Bonus
ID	Name	Age	Salary	Position	Performance	Bonus
1	Bagas	25	5000	Staff	Good	500
2	Joan	30	7000	Supervisor	Very Good	1400
3	Alya	27	6500	Staff	Average	325
4	Dwi	35	10000	Manager	Good	1000
5	Nabil	40	12000	Director	Very Good	2400

employees$Total <- employees$Salary + employees$Bonus

total_table <- employees[, c("Name","Salary","Bonus","Total")]

knitr::kable(total_table, caption = "Total Salary and Bonus of Employees")

Total Salary and Bonus of Employees
Name	Salary	Bonus	Total
Bagas	5000	500	5500
Joan	7000	1400	8400
Alya	6500	325	6825
Dwi	10000	1000	11000
Nabil	12000	2400	14400

Interpretation

The results show that the bonus amount depends on employee performance. Employees with Very Good performance receive the highest bonus, followed by Good, while Average performance receives the smallest bonus.

Loops (For & While)

Loops are used to repeat commands automatically. In this practicum, loops are used to iterate through the employee dataset and display specific information.

1. For Loop

The for loop is used to iterate through each row of the dataset. In this example, the loop checks which employees have a salary greater than 6000 and displays their names and salaries.

for(i in 1:nrow(employees)){
  
  if(employees$Salary[i] > 6000){
    
    cat("Name:", employees$Name[i],
        ", Salary:", employees$Salary[i], "\n")
    
  }
  
}

## Name: Joan , Salary: 7000 
## Name: Alya , Salary: 6500 
## Name: Dwi , Salary: 10000 
## Name: Nabil , Salary: 12000

Interpretation

The for loop checks each employee in the dataset. It displays only employees whose salary is greater than 6000, which helps filter data based on a specific condition.

2. While Loop

The while loop repeats a command as long as a condition is true. In this example, the program displays employee data until a manager position is found.

i <- 1

while(i <= nrow(employees)){
  
  cat("Name:", employees$Name[i],
      ", Position:", employees$Position[i], "\n")
  
  if(employees$Position[i] == "Manager"){
    
    cat("(Stop here)\n")
    break
    
  }
  
  i <- i + 1
}

## Name: Bagas , Position: Staff 
## Name: Joan , Position: Supervisor 
## Name: Alya , Position: Staff 
## Name: Dwi , Position: Manager 
## (Stop here)

Interpretation

The while loop displays employee information one by one until a manager position is found. When the manager appears, the loop stops automatically.

3. Break Example

Use break to stop the loop when an employee with salary above 10000 is found.

for(i in 1:nrow(employees)){
  
  if(employees$Salary[i] > 10000){
    
    cat("(Stopped because", employees$Name[i],
        "has a salary above 10,000)\n")
    break
    
  }
  
  cat("Name:", employees$Name[i],
      ", Salary:", employees$Salary[i], "\n")
}

## Name: Bagas , Salary: 5000 
## Name: Joan , Salary: 7000 
## Name: Alya , Salary: 6500 
## Name: Dwi , Salary: 10000 
## (Stopped because Nabil has a salary above 10,000)

Interpretation

The break statement stops the loop when a specific condition is met. In this example, the loop stops when an employee with a salary greater than 10000 is found.

4. Continue Example

Use continue (next in R) to skip employees with Average performance.

for(i in 1:nrow(employees)){
  
  if(employees$Performance[i] == "Average"){
    
    cat("(", employees$Name[i],
        "is skipped because the performance is Average )\n")
    next
    
  }
  
  cat("Name:", employees$Name[i],
      ", Performance:", employees$Performance[i], "\n")
}

## Name: Bagas , Performance: Good 
## Name: Joan , Performance: Very Good 
## ( Alya is skipped because the performance is Average )
## Name: Dwi , Performance: Good 
## Name: Nabil , Performance: Very Good

Interpretation

The next statement skips certain data during the loop. In this example, employees with Average performance are skipped and not displayed.

Conclusion

This practicum demonstrates the use of conditional statements and loops in R programming. Conditional statements are used to determine employee bonuses based on their performance levels. Meanwhile, loops such as for loops and while loops help iterate through the dataset to display and analyze employee information.

By applying these concepts, datasets can be processed more efficiently and repetitive tasks can be automated in data analysis.