Python - Union of two or more Lists

The union of two or more lists combines all elements ensuring no duplicates if specified. In this article we will explore various methods to get a union of two lists.

Using set.union (Most Efficient for Uniqueness)

The union() method ensures that the resulting list contains unique elements. Here we convert the lists to sets perform a union and convert back to a list. This approach automatically removes duplicates.

a = [1, 2, 3, 4]
b = [3, 4, 5, 6]

# Find the union of lists
union_list = list(set(a).union(b))

print("Union lists:", union_list)

Union lists: [1, 2, 3, 4, 5, 6]

Let's see some other methods on how to do union of two more lists.

Using '|' Operator for Sets

The '|'operator is shorthand for the union operation between sets. It is similar to set.union() but it's more concise. This will removes duplicates automatically and combines the lists.

a = [1, 2, 3, 4]
b = [3, 4, 5, 6]

# Find the union of lists
union_list = list(set(a) | set(b))
print("Union lists:", union_list)

Union lists: [1, 2, 3, 4, 5, 6]

Using List Concatenation (Includes Duplicates)

Using list concatenation will simply combines all elements without removing duplicates. We can use this approach if duplicate elements are acceptable.

a = [1, 2, 3, 4]
b = [3, 4, 5, 6]

# Concatenate the lists
union_list = a + b

print(union_list)

[1, 2, 3, 4, 3, 4, 5, 6]

Using List Comprehension

This method combines the lists and removes duplicates manually. Here we combines the lists and removes duplicates using set().

a = [1, 2, 3, 4]
b = [3, 4, 5, 6]

# Find unique union using list comprehension
union_list = list(set([x for x in a + b]))
print(union_list)

[1, 2, 3, 4, 5, 6]

Using NumPy's union1d() for Numerical Lists

NumPy provides an optimized method to compute the union of arrays.

import numpy as np

a = [1, 2, 3, 4]
b = [3, 4, 5, 6]

# Find the union of lists
union_list = np.union1d(a, b)

print("Union of lists:", union_list)

Union of lists: [1 2 3 4 5 6]

Explanation:

• NumPy’s union1d() function returns a sorted array with unique elements from the input arrays.
• More Suitable for numerical data and large datasets.