Python Program to Check if two arrays are equal

Arrays are fundamental data structures in Python, and checking if two arrays are equal is a common operation. Python provides several techniques to compare arrays based on whether they contain the same elements, regardless of order.

Understanding Array Equality

Array equality can be checked in two ways:

• Element-wise comparison ? Same elements at same positions

• Set-based comparison ? Same elements regardless of order

Let's explore different methods to check array equality ?

Method 1: Using NumPy for Element-wise Comparison

NumPy's array_equal() function compares arrays element by element ?

import numpy as np

arr1 = [1, 2, 3, 4, 5]
arr2 = [1, 2, 3, 4, 5]
arr3 = [5, 4, 3, 2, 1]

# Element-wise comparison
print("arr1 == arr2:", np.array_equal(arr1, arr2))
print("arr1 == arr3:", np.array_equal(arr1, arr3))

# Using == operator with all()
result = (np.array(arr1) == np.array(arr2)).all()
print("Using == with all():", result)

arr1 == arr2: True
arr1 == arr3: False
Using == with all(): True

Method 2: Using Sorting for Content Comparison

Sort both arrays and compare element by element to check if they contain the same elements ?

def arrays_equal_sorted(arr1, arr2):
    if len(arr1) != len(arr2):
        return False
    
    # Create copies to avoid modifying original arrays
    sorted_arr1 = sorted(arr1)
    sorted_arr2 = sorted(arr2)
    
    return sorted_arr1 == sorted_arr2

# Test with different arrays
arr1 = [1, 3, 5, 2, 4]
arr2 = [5, 4, 3, 2, 1]
arr3 = [1, 2, 3, 4, 6]

print("arr1 and arr2:", arrays_equal_sorted(arr1, arr2))
print("arr1 and arr3:", arrays_equal_sorted(arr1, arr3))

arr1 and arr2: True
arr1 and arr3: False

Method 3: Using Sets for Unique Element Comparison

Convert arrays to sets to check if they contain the same unique elements ?

def arrays_equal_sets(arr1, arr2):
    return set(arr1) == set(arr2)

# Test arrays
arr1 = [1, 2, 3, 2, 1]
arr2 = [3, 1, 2, 1, 2]
arr3 = [1, 2, 4]

print("arr1 and arr2 (same elements):", arrays_equal_sets(arr1, arr2))
print("arr1 and arr3 (different elements):", arrays_equal_sets(arr1, arr3))

# Note: Sets ignore duplicates
arr4 = [1, 1, 2, 2]
arr5 = [1, 2]
print("Sets ignore duplicates:", arrays_equal_sets(arr4, arr5))

arr1 and arr2 (same elements): True
arr1 and arr3 (different elements): False
Sets ignore duplicates: True

Method 4: Using Counter for Frequency Comparison

Use Counter from collections to compare element frequencies ?

from collections import Counter

def arrays_equal_counter(arr1, arr2):
    return Counter(arr1) == Counter(arr2)

# Test with duplicate elements
arr1 = [1, 2, 2, 3, 3, 3]
arr2 = [3, 3, 2, 1, 2, 3]
arr3 = [1, 2, 3, 3, 3]  # Different frequency

print("Same frequencies:", arrays_equal_counter(arr1, arr2))
print("Different frequencies:", arrays_equal_counter(arr1, arr3))

Same frequencies: True
Different frequencies: False

Comparison of Methods

Conclusion

Choose numpy.array_equal() for exact element-wise comparison, sorted() comparison for same elements in any order, or Counter when element frequency matters. Sets are ideal when only unique elements need to be compared.