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Find Common Elements in Two Arrays in Python

Last Updated : 23 Jul, 2025

Given two arrays arr1[] and arr2[], the task is to find all the common elements among them.

Examples:

Input: arr1[] = {1, 2, 3, 4, 5}, arr2[] = {3, 4, 5, 6, 7}
Output: 3 4 5
Explanation: 3, 4 and 5 are common to both the arrays.

Input: arr1: {2, 4, 0, 5, 8}, arr2: {0, 1, 2, 3, 4}
Output: 0 2 4
Explanation: 0, 2 and 4 are common to both the arrays.

This is a brute force approach, simply traverse in the first array, for every element of the first array traverse in the second array to find whether it exists there or not, if true then check it in the result array (to avoid repetition), after that if we found that this element is not present in result array then print it and store it in the result array.

Step-by-step approach:

• Iterate over each element in arr1.
• For each element in arr1, iterate over each element in arr2.
• Compare the current element of arr1 with each element of arr2.
• If a common element is found between the two arrays, proceed to the next steps. Otherwise, continue to the next iteration.
• Check if the common element found is already present in the result array.
• If the common element is not a duplicate, add it to the result array.
• Print the common elements found during the iterations.

Below is the implementation of the above approach:

# Python Program for find commom element using two array
import array

arr1 = array.array('i', [1, 2, 3, 4, 5])
arr2 = array.array('i', [3, 4, 5, 6, 7])
result = array.array('i')

print("Common elements are:", end=" ")

# To traverse array1.
for i in range(len(arr1)):
    # To traverse array2.
    for j in range(len(arr2)):
        # To match elements of array1 with elements of array2.
        if arr1[i] == arr2[j]:
            # Check whether the found element is already present in the result array or not.
            if arr1[i] not in result:
                result.append(arr1[i])
                print(arr1[i], end=" ")
                break

Common elements are: 3 4 5 

Time Complexity: O(n * m), where n is the number of elements in array arr1[] and m is the number of elements in arr2[].
Auxiliary Space: O(k), where k is the number of common elements between the two arrays.

To find the common elements in two arrays in python, we have used list comprehension. For each element X in arr1, we check if X is present in arr2 and store it in a list.

Step-by-step approach:

• Use list comprehension to iterate over each element x in arr1.
  • For each element, check if it exists in arr2. If it does, add it to a new array called common_elements.
• Convert the common_elements array to a list and return it.
• Print the result.

Below is the implementation of the above approach:

# Python Program for the above approach
from array import array
def find_common_elements(arr1, arr2):
    common_elements = array('i', [x for x in arr1 if x in arr2])
    return list(common_elements)
  
# Driver Code
arr1 = array('i', [1, 2, 3, 4, 5])
arr2 = array('i', [3, 4, 5, 6, 7])
common_elements = find_common_elements(arr1, arr2)
print("Common elements:", common_elements)

Common elements: [3, 4, 5]

Time Complexity : O(n*m)
Auxiliary Space: O(k), where k is the number of common elements between the two arrays.

To find the common elements in two arrays in Python, we have to first sort the arrays, then just iterate in the sorted arrays to find the common elements between those arrays.

Step-by-step approach:

• Sort both arrays arr1 and arr2 in non-decreasing order.
• Initialize two pointers pointer1 and pointer2 to the beginning of both arrays.
• Iterate through both arrays simultaneously:
  • If the elements pointed by pointer1 and pointer2 are equal, add the element to the result vector and move both pointers forward.
  • If the element in arr1 pointed by pointer1 is less than the element in arr2 pointed by pointer2, move pointer1 forward.
  • If the element in arr2 pointed by pointer2 is less than the element in arr1 pointed by pointer1, move pointer2 forward.
• Repeat this process until one of the pointers reaches the end of its array.
• Return the result containing the common elements found in both arrays.

Below is the implementation of the above approach:

import array

def find_common_elements(arr1, arr2):
    # Convert arrays to lists for sorting
    arr1_list = list(arr1)
    arr2_list = list(arr2)

    # Sort both lists in non-decreasing order
    arr1_list.sort()
    arr2_list.sort()

    # Initialize pointers
    pointer1 = 0
    pointer2 = 0

    # Initialize an empty array to store common elements
    common_elements = array.array('i')

    # Iterate through both arrays simultaneously
    while pointer1 < len(arr1_list) and pointer2 < len(arr2_list):
        # If the elements pointed by pointer1 and pointer2 are equal
        if arr1_list[pointer1] == arr2_list[pointer2]:
            # Add the element to the result array
            common_elements.append(arr1_list[pointer1])
            # Move both pointers forward
            pointer1 += 1
            pointer2 += 1
        # If the element in arr1 pointed by pointer1 is less than the element in arr2 pointed by pointer2
        elif arr1_list[pointer1] < arr2_list[pointer2]:
            # Move pointer1 forward
            pointer1 += 1
        # If the element in arr2 pointed by pointer2 is less than the element in arr1 pointed by pointer1
        else:
            # Move pointer2 forward
            pointer2 += 1

    return common_elements


# Test the function with example arrays
arr1 = array.array('i', [1, 2, 3, 4, 5])
arr2 = array.array('i', [3, 4, 5, 6, 7])
common_elements = find_common_elements(arr1, arr2)
print "Common elements:",
for element in common_elements:
    print element,

Common elements: 3 4 5

Time Complexity: O(N log(N)+ M log(M)), where N is the size of the first array and M is the size of the second array.
Auxilliary Space: O(N+M)

To find the common elements in two arrays in Python, in this approach we will use sets. Initially, we convert both the arrays arr1 and arr2 to sets set1 and set2. Then, we use the intersection method of set to find the common elements in both the sets. Finally, we return the common elements as a list.

Step-by-step approach:

• Import the array module to use arrays in Python.
• Define a function named find_common_elements that takes two arrays (arr1 and arr2) as input.
• Within the function, convert both arrays to sets (set1 and set2) for faster lookup.
• Find the intersection of the sets (set1.intersection(set2)), which represents the common elements between the two arrays.
• Convert the set of common elements to a list and return it.
• Initialize two arrays arr1 and arr2. Call the find_common_elements function with these arrays and store the result in common_elements.
• Print the result.

Below is the implementation of the above approach:

# Python Program for the above approach
from array import array
def find_common_elements(arr1, arr2):
    # Convert arrays to sets for faster lookup
    set1 = set(arr1)
    set2 = set(arr2)
    # Find intersection of the sets (common elements)
    common_elements = set1.intersection(set2)
    return list(common_elements)

# Driver Code
arr1 = array('i', [1, 2, 3, 4, 5])
arr2 = array('i', [3, 4, 5, 6, 7])
common_elements = find_common_elements(arr1, arr2)
print("Common elements:", common_elements)

Common elements: [3, 4, 5]

Time Complexity : O(n+m)
Auxiliary Space: O((n+m+k), where k is the number of common elements between the two arrays.

In this approach, we can utilize hash maps to efficiently find the common elements between the two arrays. We'll create a hash map to the store the frequency of the each element in the first array and then iterate through the second array to the check if each element exists in the hash map. If an element exists in the hash map and its frequency is greater than 0 and we'll add it to the list of common elements and decrease its frequency in the hash map.

Here's the step-by-step algorithm:

• Create a hash map to store the frequency of the each element in the first array where the key is the element and the value is its frequency.
• Iterate through the second array.
• For each element in the second array and check if it exists in the hash map and its frequency is greater than 0.
• If both conditions are met add the element to the list of the common elements and decrease its frequency in the hash map.
• After iterating through the second array, return the list of the common elements.

Example code:

def GFG(arr1, arr2):
    # Create a hash map to store the frequency of the each element in arr1
    frequency_map = {}
    for num in arr1:
        frequency_map[num] = frequency_map.get(num, 0) + 1
    # Initialize a list to store the common elements
    common_elements = []
    # Iterate through arr2 to the find common elements
    for num in arr2:
        if num in frequency_map and frequency_map[num] > 0:
            common_elements.append(num)
            frequency_map[num] -= 1

    return common_elements
# Test the function with the example arrays
arr1 = [1, 2, 3, 4, 5]
arr2 = [3, 4, 5, 6, 7]
common_elements = GFG(arr1, arr2)
print("Common elements:", common_elements)

output :

Common elements: 3, 4, 5

Time Complexity : O(n+m)

Auxiliary Space: O(N)

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