diff --git a/searches/quick_select.py b/searches/quick_select.py
new file mode 100644
index 000000000..e5e2ce99c
--- /dev/null
+++ b/searches/quick_select.py
@@ -0,0 +1,47 @@
+import collections
+import sys
+import random
+import time
+import math
+"""
+A python implementation of the quick select algorithm, which is efficient for calculating the value that would appear in the index of a list if it would be sorted, even if it is not already sorted
+https://en.wikipedia.org/wiki/Quickselect
+"""
+def _partition(data, pivot):
+    """
+    Three way partition the data into smaller, equal and greater lists,
+    in relationship to the pivot
+    :param data: The data to be sorted (a list)
+    :param pivot: The value to partition the data on
+    :return: Three list: smaller, equal and greater
+    """
+    less, equal, greater = [], [], []
+    for element in data:
+        if element.address < pivot.address:
+            less.append(element)
+        elif element.address > pivot.address:
+            greater.append(element)
+        else:
+            equal.append(element)
+    return less, equal, greater
+    
+    def quickSelect(list, k):
+    #k = len(list) // 2 when trying to find the median (index that value would be when list is sorted)
+      smaller = []
+      larger = []
+      pivot = random.randint(0, len(list) - 1)
+      pivot = list[pivot]
+      count = 0
+      smaller, equal, larger =_partition(list, pivot)
+      count = len(equal)
+      m = len(smaller)
+
+      #k is the pivot
+      if m <= k < m + count:
+        return pivot
+    # must be in smaller
+      elif m > k:
+        return quickSelect(smaller, k)
+    #must be in larger
+      else:
+        return quickSelect(larger, k - (m + count))