devmgupta
diff --git a/‎algorithms/sorting/insertion_sort.py‎
Lines changed: 0 additions & 1 deletion b/‎algorithms/sorting/insertion_sort.py‎
Lines changed: 0 additions & 1 deletion
diff --git a/‎algorithms/sorting/merge_sort.py‎
Lines changed: 51 additions & 0 deletions b/‎algorithms/sorting/merge_sort.py‎
Lines changed: 51 additions & 0 deletions
@@ -2,7 +2,6 @@
 High Level Description:
 For every element in the given list, find its correct index by iterating
 backwards and finding a slot. This forms a sorted array.
-
 Time Complexity:
 Every element is visited, which contributes O(n). Swapping backwards takes
 O(n/2) time on average, meaning that the total complexity is O(n^2)
 
@@ -0,0 +1,51 @@
+"""
+High level explanation:
+
+mergeSort is a Divide and conquer algorithm that splits in halves the array and
+then builds it back up by merging and sorting at the same time its elements.
+
+Time complexity:
+
+mergeSort has a time complexity of O(n log n).
+"""
+
+def mergeSort(arr): 
+    if len(arr) >1: 
+        mid = len(arr)//2 #Finding the mid of the array 
+        L = arr[:mid] # Dividing the array elements  
+        R = arr[mid:] # into 2 halves 
+  
+        mergeSort(L) # Sorting the first half 
+        mergeSort(R) # Sorting the second half 
+  
+        i = j = k = 0
+          
+        # Copy data to temp arrays L[] and R[] 
+        while i < len(L) and j < len(R): 
+            if L[i] < R[j]: 
+                arr[k] = L[i] 
+                i+=1
+            else: 
+                arr[k] = R[j] 
+                j+=1
+            k+=1
+          
+        # Checking if any element was left 
+        while i < len(L): 
+            arr[k] = L[i] 
+            i+=1
+            k+=1
+          
+        while j < len(R): 
+            arr[k] = R[j] 
+            j+=1
+            k+=1
+
+test_array = [10,30,20,100,40,80,90,210,34]
+
+mergeSort(test_array)
+
+print(test_array)
+
+# This code is contributed by Mayank Khanna
+# and extented by thanasis mpalatsoukas