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Program to calculate Percentile of a student based on rank
  • Difficulty Level : Easy
  • Last Updated : 01 Apr, 2021

Given the rank of a student and the total number of students appearing in an examination, the task is to find the percentile of the student. 
 

The percentile of a student is the % of the number of students having marks less than him/her.

Examples: 
 

Input: Rank: 805, Total Number of Students Appeared: 97481 
Output: 99.17 
Explaination: 
((97481 – 805) / 97481) * 100 = 99.17
Input: Rank: 65, Total Number of Students Appeared: 100 
Output: 35 
Explaination: 
((100 – 65) / 100) * 100 = 35 
 

 



Approach 
The formula to calculate the percentile when the rank of the student and the total number of students appeared is given is:
 

((Total Students – Rank) / Total Students) * 100

Below is the implementation of the above formula: 
 

C++ 

 

 

C++




// C++ program to calculate Percentile
// of a student based on rank
 
#include <bits/stdc++.h>
using namespace std;
 
// Program to calculate the percentile
float getPercentile(int rank, int students)
{
    // flat variable to store the result
    float result = float(students - rank)
                / students * 100;
 
    // calculate and return the percentile
    return result;
}
 
// Driver Code
int main()
{
    int your_rank = 805;
    int total_students = 97481;
 
    cout << getPercentile(
        your_rank, total_students);
}

Java




// Java program to calculate Percentile
// of a student based on rank
import java.util.*;
 
class GFG{
  
// Program to calculate the percentile
static float getPercentile(int rank, int students)
{
    // flat variable to store the result
    float result = (float)(students - rank)
                   / students * 100;
  
    // calculate and return the percentile
    return result;
}
  
// Driver Code
public static void main(String[] args)
{
    int your_rank = 805;
    int total_students = 97481;
  
    System.out.print(getPercentile(
        your_rank, total_students));
}
}
 
// This code is contributed by Princi Singh

Python3




# Python3 program to calculate Percentile
# of a student based on rank
 
# Program to calculate the percentile
def getPercentile(rank, students) :
 
    # flat variable to store the result
    result = (students - rank) / students * 100;
 
    # calculate and return the percentile
    return result;
 
# Driver Code
if __name__ == "__main__" :
 
    your_rank = 805;
    total_students = 97481;
 
    print(getPercentile(your_rank, total_students));
 
# This code is contributed by Yash_R

C#




// C# program to calculate Percentile
// of a student based on rank
using System;
 
class GFG{
   
// Program to calculate the percentile
static float getPercentile(int rank, int students)
{
    // flat variable to store the result
    float result = (float)(students - rank)
                   / students * 100;
   
    // calculate and return the percentile
    return result;
}
   
// Driver Code
public static void Main(String[] args)
{
    int your_rank = 805;
    int total_students = 97481;
   
    Console.Write(getPercentile(
        your_rank, total_students));
}
}
 
// This code is contributed by Princi Singh

Javascript




<script>
 
// JavaScript program to calculate Percentile
// of a student based on rank
 
    // Program to calculate the percentile
    function getPercentile(rank , students)
    {
        // flat variable to store the result
        var result =  (students - rank) / students * 100;
 
        // calculate and return the percentile
        return result;
    }
 
    // Driver Code
     
        var your_rank = 805;
        var total_students = 97481;
 
        document.write(getPercentile(your_rank, total_students).toFixed(4));
 
// This code contributed by aashish1995
 
</script>
Output: 
99.1742

 

Performance Analysis
 

  • Time Complexity: In the above approach, we are able to calculate percentile using a formula in constant time, so the time complexity is O(1)
     
  • Auxiliary Space Complexity: In the above approach, we are not using any extra space apart from a few constant size variables, so Auxiliary space complexity is O(1).

 

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