This interactive R course covers everything from the basics, variables, and data types to advanced topics, such as recursion, file handling, and S3/S4 classes in R.

In today’s data-driven world, the ability to analyze large datasets is becoming a vital skill across industries. R, one of the most powerful languages for data analysis.
This interactive R course is designed for beginners, with no prior knowledge of R programming required. You will begin with fundamental concepts, such as R variables, data types in R, and basic functions like R print and R cat. As you progress, you will dive into more complex topics, including R vectors, lists, arrays, matrices, and data frames in R programming. You’ll also learn how to perform operations using arithmetic operators in R, relational operators in R, and logical operators in R. Further, the course covers advanced features like if statements in R, switch statements in R, loops in R, and recursion in R. 
Finally, you’ll gain hands-on experience with file handling in R, exception handling with try and except in R, and object-oriented programming using S3 and S4 classes in R.

Learn R

# Problem Statement
Implement a function `findTopper()` that takes input from three subject files: `math.csv`, `english.csv` and `science.csv`, and find the index of the student that has scored the maximum total marks adding all three of its marks.

## Input
Three files: `math.csv`, `english.csv` and `science.csv`

## Output
Index of the highest scoring student

## Sample Input
`math.csv`
```
Name,   Math
Andrew, 2.5
Mathew, 5.9
Dany,   1.9
Philip, 9.1
```
`english.csv`
```
Name,   English
Andrew, 8.2
Mathew, 2.5
Dany,   7.5
Philip, 9.3
```
`science.csv`
```
Name,   Science
Andrew, 5.2
Mathew, 9.5
Dany,   7.1
Philip, 1.9
```

## Sample Output
```
4
```
## Test Yourself
Write your code in the given area. If you get stuck, you can look at the solution.

Name,   Math
Andrew, 2.5
Mathew, 5.9
Dany,   1.9
Philip, 9.1


Name,   English
Andrew, 8.2
Mathew, 2.5
Dany,   7.5
Philip, 9.3


Name,   Science
Andrew, 5.2
Mathew, 9.5
Dany,   7.1
Philip, 1.9


findTopper <- function() 
{
    # Write your code here
}

findTopper <- function() 
{
    findIndexWithMaxNum <- function(myVector) # helper function that returns the index 
                                        # of the element that has the highest value
    {
        maxNumber = -Inf # We want this to be the lowest possible value for comparison
        maxIndex = 0

        index = 1
        for(i in myVector)
        {
            if(maxNumber < i)
            {
                maxNumber = i # set the max element
                maxIndex = index # set the max element's index
            }
            index = index + 1
        }
        return(maxIndex) # return the index of the max element
    }

    # MAIN FILE HANDLING CODE
    mathData = read.csv("math.csv") # fetch data from math.csv
    englishData = read.csv("english.csv") # fetch data from english.csv
    scienceData = read.csv("science.csv") # fetch data from science.csv

    tempData <- merge(mathData, englishData) # we use the merge function on data frames
    finalData <- merge(tempData, scienceData) # another merge function to merge the remaining data frame

    result <- vector("numeric", 0) # vector to store the total marks of each student

    for(student in 1:length(finalData)) # loop over all the rows/students
    {
        temp <- 0.0 # temporarily stores the total marks of the current student

        for(i in 2:ncol(finalData)){ # loop over all the columns (math, english, science)
        # We iterate from 2 to ncol(finalData) because the 1st column is just names of students

            temp <- temp + as.double(finalData[student, i]) # fetch respective student's marks
        }
        result <- c(result, temp) # store the total marks of the current student
    }
    return(findIndexWithMaxNum(result)) # return the index of the highest scoring student
}

---
In the next lesson, we give a brief overview of the solution to this problem.

Given multiple subject files find the student who has the maximum total marks.

Introduction to R

R variables

Data Structures in R

Operator in R

Conditional Statements in R

Loops in R

Function in R

Input/Output in R

Exception Handling in R

Classes in R

R Programming Challenges

Conclusion

Challenge 3: Find the Highest Achiever