# Median of an unsorted array using Quick Select Algorithm

Given an unsorted array arr[] of length N, the task is to find the median of of this array.
Median of a sorted array of size N is defined as the middle element when n is odd and average of middle two elements when n is even.

Examples:

Input: arr[] = {12, 3, 5, 7, 4, 19, 26}
Output: 7
Sorted sequence of given array arr[] = {3, 4, 5, 7, 12, 19, 26}
Since the number of elements is odd, the median is 4th element in the sorted sequence of given array arr[], which is 7

Input: arr[] = {12, 3, 5, 7, 4, 26}
Output: 6
Since number of elements are even, median is average of 3rd and 4th element in sorted sequence of given array arr[], which means (5 + 7)/2 = 6

## Recommended: Please try your approach on {IDE} first, before moving on to the solution.

Naive Approach:

• Sort the array arr[] in increasing order.
• If number of elements in arr[] is odd, then median is arr[n/2].
• If the number of elements in arr[] is even, median is average of arr[n/2] and arr[n/2+1].

Efficient Approach: using Randomized QuickSelect

• Randomly pick pivot element from arr[] and the using the partition step from the quick sort algorithm arrange all the elements smaller than the pivot on its left and the elements greater than it on its right.
• If after the previous step, the position of the chosen pivot is the middle of the array then it is the required median of the given array.
• If the position is before the middle element then repeat the step for the subarray starting from previous starting index and the chosen pivot as the ending index.
• If the position is after the middle element then repeat the step for the subarray starting from the chosen pivot and ending at the previous ending index.
• Note that in case of even number of elements, the middle two elements have to be found and their average will be the median of the array.

Below is the implementation of the above approach:

## C++

 `// CPP program to find median of ` `// an array ` ` `  `#include "bits/stdc++.h" ` `using` `namespace` `std; ` ` `  `// Utility function to swapping of element ` `void` `swap(``int``* a, ``int``* b) ` `{ ` `    ``int` `temp = *a; ` `    ``*a = *b; ` `    ``*b = temp; ` `} ` ` `  `// Returns the correct position of ` `// pivot element ` `int` `Partition(``int` `arr[], ``int` `l, ``int` `r) ` `{ ` `    ``int` `lst = arr[r], i = l, j = l; ` `    ``while` `(j < r) { ` `        ``if` `(arr[j] < lst) { ` `            ``swap(&arr[i], &arr[j]); ` `            ``i++; ` `        ``} ` `        ``j++; ` `    ``} ` `    ``swap(&arr[i], &arr[r]); ` `    ``return` `i; ` `} ` ` `  `// Picks a random pivot element between ` `// l and r and partitions arr[l..r] ` `// around the randomly picked element ` `// using partition() ` `int` `randomPartition(``int` `arr[], ``int` `l, ` `                    ``int` `r) ` `{ ` `    ``int` `n = r - l + 1; ` `    ``int` `pivot = ``rand``() % n; ` `    ``swap(&arr[l + pivot], &arr[r]); ` `    ``return` `Partition(arr, l, r); ` `} ` ` `  `// Utility function to find median ` `void` `MedianUtil(``int` `arr[], ``int` `l, ``int` `r, ` `                ``int` `k, ``int``& a, ``int``& b) ` `{ ` ` `  `    ``// if l < r ` `    ``if` `(l <= r) { ` ` `  `        ``// Find the partition index ` `        ``int` `partitionIndex ` `            ``= randomPartition(arr, l, r); ` ` `  `        ``// If partion index = k, then ` `        ``// we found the median of odd ` `        ``// number element in arr[] ` `        ``if` `(partitionIndex == k) { ` `            ``b = arr[partitionIndex]; ` `            ``if` `(a != -1) ` `                ``return``; ` `        ``} ` ` `  `        ``// If index = k - 1, then we get ` `        ``// a & b as middle element of ` `        ``// arr[] ` `        ``else` `if` `(partitionIndex == k - 1) { ` `            ``a = arr[partitionIndex]; ` `            ``if` `(b != -1) ` `                ``return``; ` `        ``} ` ` `  `        ``// If partitionIndex >= k then ` `        ``// find the index in first half ` `        ``// of the arr[] ` `        ``if` `(partitionIndex >= k) ` `            ``return` `MedianUtil(arr, l, ` `                              ``partitionIndex - 1, ` `                              ``k, a, b); ` ` `  `        ``// If partitionIndex <= k then ` `        ``// find the index in second half ` `        ``// of the arr[] ` `        ``else` `            ``return` `MedianUtil(arr, ` `                              ``partitionIndex + 1, ` `                              ``r, k, a, b); ` `    ``} ` ` `  `    ``return``; ` `} ` ` `  `// Function to find Median ` `void` `findMedian(``int` `arr[], ``int` `n) ` `{ ` `    ``int` `ans, a = -1, b = -1; ` ` `  `    ``// If n is odd ` `    ``if` `(n % 2 == 1) { ` `        ``MedianUtil(arr, 0, n - 1, ` `                   ``n / 2, a, b); ` `        ``ans = b; ` `    ``} ` ` `  `    ``// If n is even ` `    ``else` `{ ` `        ``MedianUtil(arr, 0, n - 1, ` `                   ``n / 2, a, b); ` `        ``ans = (a + b) / 2; ` `    ``} ` ` `  `    ``// Print the Median of arr[] ` `    ``cout << ``"Median = "` `<< ans; ` `} ` ` `  `// Driver program to test above methods ` `int` `main() ` `{ ` `    ``int` `arr[] = { 12, 3, 5, 7, 4, 19, 26 }; ` `    ``int` `n = ``sizeof``(arr) / ``sizeof``(arr[0]); ` `    ``findMedian(arr, n); ` `    ``return` `0; ` `} `

## Java

 `// JAVA program to find median of ` `// an array ` `class` `GFG  ` `{ ` `    ``static` `int` `a, b; ` ` `  `    ``// Utility function to swapping of element ` `    ``static` `int``[] swap(``int``[] arr, ``int` `i, ``int` `j) ` `    ``{ ` `        ``int` `temp = arr[i]; ` `        ``arr[i] = arr[j]; ` `        ``arr[j] = temp; ` `        ``return` `arr; ` `    ``} ` ` `  `    ``// Returns the correct position of ` `    ``// pivot element ` `    ``static` `int` `Partition(``int` `arr[], ``int` `l, ``int` `r) ` `    ``{ ` `        ``int` `lst = arr[r], i = l, j = l; ` `        ``while` `(j < r)  ` `        ``{ ` `            ``if` `(arr[j] < lst) ` `            ``{ ` `                ``arr = swap(arr, i, j); ` `                ``i++; ` `            ``} ` `            ``j++; ` `        ``} ` `        ``arr = swap(arr, i, r); ` `        ``return` `i; ` `    ``} ` ` `  `    ``// Picks a random pivot element between ` `    ``// l and r and partitions arr[l..r] ` `    ``// around the randomly picked element ` `    ``// using partition() ` `    ``static` `int` `randomPartition(``int` `arr[], ``int` `l, ``int` `r) ` `    ``{ ` `        ``int` `n = r - l + ``1``; ` `        ``int` `pivot = (``int``) (Math.random() % n); ` `        ``arr = swap(arr, l + pivot, r); ` `        ``return` `Partition(arr, l, r); ` `    ``} ` ` `  `    ``// Utility function to find median ` `    ``static` `int` `MedianUtil(``int` `arr[], ``int` `l, ``int` `r, ``int` `k)  ` `    ``{ ` ` `  `        ``// if l < r ` `        ``if` `(l <= r)  ` `        ``{ ` ` `  `            ``// Find the partition index ` `            ``int` `partitionIndex = randomPartition(arr, l, r); ` ` `  `            ``// If partion index = k, then ` `            ``// we found the median of odd ` `            ``// number element in arr[] ` `            ``if` `(partitionIndex == k) ` `            ``{ ` `                ``b = arr[partitionIndex]; ` `                ``if` `(a != -``1``) ` `                    ``return` `Integer.MIN_VALUE; ` `            ``} ` ` `  `            ``// If index = k - 1, then we get ` `            ``// a & b as middle element of ` `            ``// arr[] ` `            ``else` `if` `(partitionIndex == k - ``1``) ` `            ``{ ` `                ``a = arr[partitionIndex]; ` `                ``if` `(b != -``1``) ` `                    ``return` `Integer.MIN_VALUE; ` `            ``} ` ` `  `            ``// If partitionIndex >= k then ` `            ``// find the index in first half ` `            ``// of the arr[] ` `            ``if` `(partitionIndex >= k) ` `                ``return` `MedianUtil(arr, l, partitionIndex - ``1``, k); ` ` `  `            ``// If partitionIndex <= k then ` `            ``// find the index in second half ` `            ``// of the arr[] ` `            ``else` `                ``return` `MedianUtil(arr, partitionIndex + ``1``, r, k); ` `        ``} ` ` `  `        ``return` `Integer.MIN_VALUE; ` `    ``} ` ` `  `    ``// Function to find Median ` `    ``static` `void` `findMedian(``int` `arr[], ``int` `n) ` `    ``{ ` `        ``int` `ans; ` `        ``a = -``1``; ` `        ``b = -``1``; ` ` `  `        ``// If n is odd ` `        ``if` `(n % ``2` `== ``1``)  ` `        ``{ ` `            ``MedianUtil(arr, ``0``, n - ``1``, n / ``2``); ` `            ``ans = b; ` `        ``} ` ` `  `        ``// If n is even ` `        ``else`  `        ``{ ` `            ``MedianUtil(arr, ``0``, n - ``1``, n / ``2``); ` `            ``ans = (a + b) / ``2``; ` `        ``} ` ` `  `        ``// Print the Median of arr[] ` `        ``System.out.print(``"Median = "` `+ ans); ` `    ``} ` ` `  `    ``// Driver code ` `    ``public` `static` `void` `main(String[] args)  ` `    ``{ ` `        ``int` `arr[] = { ``12``, ``3``, ``5``, ``7``, ``4``, ``19``, ``26` `}; ` `        ``int` `n = arr.length; ` `        ``findMedian(arr, n); ` `    ``} ` `} ` ` `  `// This code is contributed by 29AjayKumar `

## Python3

 `# Python3 program to find median of  ` `# an array  ` `import` `random ` ` `  `a, b ``=` `None``, ``None``; ` ` `  `# Returns the correct position of  ` `# pivot element  ` `def` `Partition(arr, l, r) :  ` ` `  `    ``lst ``=` `arr[r]; i ``=` `l; j ``=` `l;  ` `    ``while` `(j < r) : ` `        ``if` `(arr[j] < lst) : ` `            ``arr[i], arr[j] ``=` `arr[j],arr[i];  ` `            ``i ``+``=` `1``;  ` `         `  `        ``j ``+``=` `1``;  ` ` `  `    ``arr[i], arr[r] ``=` `arr[r],arr[i];  ` `    ``return` `i;  ` ` `  `# Picks a random pivot element between  ` `# l and r and partitions arr[l..r]  ` `# around the randomly picked element  ` `# using partition()  ` `def` `randomPartition(arr, l, r) : ` `    ``n ``=` `r ``-` `l ``+` `1``; ` `    ``pivot ``=` `random.randrange(``1``, ``100``) ``%` `n; ` `    ``arr[l ``+` `pivot], arr[r] ``=` `arr[r], arr[l ``+` `pivot]; ` `    ``return` `Partition(arr, l, r);  ` ` `  `# Utility function to find median  ` `def` `MedianUtil(arr, l, r,  ` `                ``k, a1, b1) :  ` ` `  `    ``global` `a, b; ` `     `  `    ``# if l < r ` `    ``if` `(l <``=` `r) : ` `         `  `        ``# Find the partition index ` `        ``partitionIndex ``=` `randomPartition(arr, l, r); ` `         `  `        ``# If partion index = k, then ` `        ``# we found the median of odd ` `        ``# number element in arr[] ` `        ``if` `(partitionIndex ``=``=` `k) : ` `            ``b ``=` `arr[partitionIndex]; ` `            ``if` `(a1 !``=` `-``1``) : ` `                ``return``; ` `                 `  `        ``# If index = k - 1, then we get ` `        ``# a & b as middle element of ` `        ``# arr[] ` `        ``elif` `(partitionIndex ``=``=` `k ``-` `1``) : ` `            ``a ``=` `arr[partitionIndex]; ` `            ``if` `(b1 !``=` `-``1``) : ` `                ``return``; ` `                 `  `        ``# If partitionIndex >= k then ` `        ``# find the index in first half ` `        ``# of the arr[] ` `        ``if` `(partitionIndex >``=` `k) : ` `            ``return` `MedianUtil(arr, l, partitionIndex ``-` `1``, k, a, b); ` `             `  `        ``# If partitionIndex <= k then ` `        ``# find the index in second half ` `        ``# of the arr[] ` `        ``else` `: ` `            ``return` `MedianUtil(arr, partitionIndex ``+` `1``, r, k, a, b); ` `             `  `    ``return``;  ` ` `  `# Function to find Median  ` `def` `findMedian(arr, n) : ` `    ``global` `a; ` `    ``global` `b; ` `    ``a ``=` `-``1``; ` `    ``b ``=` `-``1``; ` `     `  `    ``# If n is odd ` `    ``if` `(n ``%` `2` `=``=` `1``) : ` `        ``MedianUtil(arr, ``0``, n ``-` `1``, n ``/``/` `2``, a, b); ` `        ``ans ``=` `b; ` `         `  `    ``# If n is even ` `    ``else` `: ` `        ``MedianUtil(arr, ``0``, n ``-` `1``, n ``/``/` `2``, a, b); ` `        ``ans ``=` `(a ``+` `b) ``/``/` `2``; ` `         `  `    ``# Print the Median of arr[] ` `    ``print``(``"Median = "` `,ans);  ` ` `  ` `  `# Driver code ` `arr ``=` `[ ``12``, ``3``, ``5``, ``7``, ``4``, ``19``, ``26` `];  ` `n ``=` `len``(arr);  ` `findMedian(arr, n);  ` ` `  `# This code is contributed by AnkitRai01 `

## C#

 `// C# program to find median of ` `// an array ` `using` `System; ` ` `  `class` `GFG  ` `{ ` `    ``static` `int` `a, b; ` ` `  `    ``// Utility function to swapping of element ` `    ``static` `int``[] swap(``int``[] arr, ``int` `i, ``int` `j) ` `    ``{ ` `        ``int` `temp = arr[i]; ` `        ``arr[i] = arr[j]; ` `        ``arr[j] = temp; ` `        ``return` `arr; ` `    ``} ` ` `  `    ``// Returns the correct position of ` `    ``// pivot element ` `    ``static` `int` `Partition(``int` `[]arr, ``int` `l, ``int` `r) ` `    ``{ ` `        ``int` `lst = arr[r], i = l, j = l; ` `        ``while` `(j < r)  ` `        ``{ ` `            ``if` `(arr[j] < lst) ` `            ``{ ` `                ``arr = swap(arr, i, j); ` `                ``i++; ` `            ``} ` `            ``j++; ` `        ``} ` `        ``arr = swap(arr, i, r); ` `        ``return` `i; ` `    ``} ` ` `  `    ``// Picks a random pivot element between ` `    ``// l and r and partitions arr[l..r] ` `    ``// around the randomly picked element ` `    ``// using partition() ` `    ``static` `int` `randomPartition(``int` `[]arr, ``int` `l, ``int` `r) ` `    ``{ ` `        ``int` `n = r - l + 1; ` `        ``int` `pivot = (``int``) (``new` `Random().Next() % n); ` `        ``arr = swap(arr, l + pivot, r); ` `        ``return` `Partition(arr, l, r); ` `    ``} ` ` `  `    ``// Utility function to find median ` `    ``static` `int` `MedianUtil(``int` `[]arr, ``int` `l, ``int` `r, ``int` `k)  ` `    ``{ ` ` `  `        ``// if l < r ` `        ``if` `(l <= r)  ` `        ``{ ` ` `  `            ``// Find the partition index ` `            ``int` `partitionIndex = randomPartition(arr, l, r); ` ` `  `            ``// If partion index = k, then ` `            ``// we found the median of odd ` `            ``// number element in []arr ` `            ``if` `(partitionIndex == k) ` `            ``{ ` `                ``b = arr[partitionIndex]; ` `                ``if` `(a != -1) ` `                    ``return` `int``.MinValue; ` `            ``} ` ` `  `            ``// If index = k - 1, then we get ` `            ``// a & b as middle element of ` `            ``// []arr ` `            ``else` `if` `(partitionIndex == k - 1) ` `            ``{ ` `                ``a = arr[partitionIndex]; ` `                ``if` `(b != -1) ` `                    ``return` `int``.MinValue; ` `            ``} ` ` `  `            ``// If partitionIndex >= k then ` `            ``// find the index in first half ` `            ``// of the []arr ` `            ``if` `(partitionIndex >= k) ` `                ``return` `MedianUtil(arr, l, partitionIndex - 1, k); ` ` `  `            ``// If partitionIndex <= k then ` `            ``// find the index in second half ` `            ``// of the []arr ` `            ``else` `                ``return` `MedianUtil(arr, partitionIndex + 1, r, k); ` `        ``} ` ` `  `        ``return` `int``.MinValue; ` `    ``} ` ` `  `    ``// Function to find Median ` `    ``static` `void` `findMedian(``int` `[]arr, ``int` `n) ` `    ``{ ` `        ``int` `ans; ` `        ``a = -1; ` `        ``b = -1; ` ` `  `        ``// If n is odd ` `        ``if` `(n % 2 == 1)  ` `        ``{ ` `            ``MedianUtil(arr, 0, n - 1, n / 2); ` `            ``ans = b; ` `        ``} ` ` `  `        ``// If n is even ` `        ``else` `        ``{ ` `            ``MedianUtil(arr, 0, n - 1, n / 2); ` `            ``ans = (a + b) / 2; ` `        ``} ` ` `  `        ``// Print the Median of []arr ` `        ``Console.Write(``"Median = "` `+ ans); ` `    ``} ` ` `  `    ``// Driver code ` `    ``public` `static` `void` `Main(String[] args)  ` `    ``{ ` `        ``int` `[]arr = { 12, 3, 5, 7, 4, 19, 26 }; ` `        ``int` `n = arr.Length; ` `        ``findMedian(arr, n); ` `    ``} ` `} ` ` `  `// This code is contributed by PrinciRaj1992 `

Output:

```Median = 7
```

Time Complexity: O(N2) where N is the number of elements in arr[].

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