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# Detailed Missing Values Report
def missing_data_report(df):
    total = df.isnull().sum().sort_values(ascending=False)
    percent = (df.isnull().sum()/df.isnull().count()*100).sort_values(ascending=False)
    missing_df = pd.concat([total, percent], axis=1, keys=['Total Missing', 'Percent Missing (%)'])
    return missing_df[missing_df['Total Missing'] > 0]

print("\nMissing Data Report:")
print(missing_data_report(df))

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#####################################################
# Setting the Stage: Our Dataset
#####################################################

import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
import plotly.express as px
import plotly.graph_objects as go

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/* C implementation QuickSort */
#include <stdio.h>

// A utility function to swap two elements
void swap(int *a, int *b)
{
	int t = *a;
	*a = *b;
	*b = t;
}

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/* C program for Merge Sort */
#include <stdio.h>
#include <stdlib.h>

// Merges two subarrays of arr[].
// First subarray is arr[l..m]
// Second subarray is arr[m+1..r]
void merge(int arr[], int l, int m, int r)
{
    int i, j, k;

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// C program for implementation of Bubble sort
#include <stdio.h> 
  
void swap(int *xp, int *yp) 
{ 
    int temp = *xp; 
    *xp = *yp; 
    *yp = temp; 
} 
  

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// C program for implementation of selection sort
#include <stdio.h>

void swap(int *xp, int *yp)
{
    int temp = *xp;
    *xp = *yp;
    *yp = temp;
}

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// C program for insertion sort
#include <math.h>
#include <stdio.h>

/* Function to sort an array using insertion sort*/
void insertionSort(int arr[], int n)
{
    int i, key, j;
    for (i = 1; i < n; i++)
    {