Python | Intersection of two lists

Intersection of two list means we need to take all those elements which are common to both of the initial lists and store them into another list. Now there are various ways in Python, through which we can perform the Intersection of the lists. 
Examples: 

Input : 
lst1 = [15, 9, 10, 56, 23, 78, 5, 4, 9]
lst2 = [9, 4, 5, 36, 47, 26, 10, 45, 87]
Output :
[9, 10, 4, 5]

Input :
lst1 = [4, 9, 1, 17, 11, 26, 28, 54, 69]
lst2 = [9, 9, 74, 21, 45, 11, 63, 28, 26]
Output :
[9, 11, 26, 28]

Method 1:
This is the simplest method where we haven’t used any built-in functions. 

Python3

# Python program to illustrate the intersection
# of two lists in most simple way
def intersection(lst1, lst2):
    lst3 = [value for value in lst1 if value in lst2]
    return lst3

# Driver Code
lst1 = [4, 9, 1, 17, 11, 26, 28, 54, 69]
lst2 = [9, 9, 74, 21, 45, 11, 63, 28, 26]
print(intersection(lst1, lst2))

Output: 

[9, 11, 26, 28]

Method 2:
This method includes the use of set() method. 

Python3

# Python program to illustrate the intersection
# of two lists using set() method
def intersection(lst1, lst2):
    return list(set(lst1) & set(lst2))

# Driver Code
lst1 = [15, 9, 10, 56, 23, 78, 5, 4, 9]
lst2 = [9, 4, 5, 36, 47, 26, 10, 45, 87]
print(intersection(lst1, lst2))

Output: 

[9, 10, 4, 5]

The time complexity of the above program is O(n), where n is the length of the longer list between lst1 and lst2.

The space complexity of the program is O(n), where n is the length of the smaller list between lst1 and lst2. 

Method 3:
In this method we set() the larger list and then use the built-in function called intersection() to compute the intersected list. intersection() is a first-class part of set. 

Python3

# Python program to illustrate the intersection
# of two lists using set() and intersection()
def Intersection(lst1, lst2):
    return set(lst1).intersection(lst2)

# Driver Code
lst1 = [ 4, 9, 1, 17, 11, 26, 28, 28, 26, 66, 91]
lst2 = [9, 9, 74, 21, 45, 11, 63]
print(Intersection(lst1, lst2))

Output: 

{9, 11}

Method 4:
By the use of this hybrid method the complexity of the program falls to O(n). This is an efficient way of doing the following program. 

Python3

# Python program to illustrate the intersection
# of two lists
def intersection(lst1, lst2):

    # Use of hybrid method
    temp = set(lst2)
    lst3 = [value for value in lst1 if value in temp]
    return lst3

# Driver Code
lst1 = [9, 9, 74, 21, 45, 11, 63]
lst2 = [4, 9, 1, 17, 11, 26, 28, 28, 26, 66, 91]
print(intersection(lst1, lst2))

Output: 

[9, 9, 11]

Method 5:
This is the where the intersection is performed over sub-lists inside other lists. Here we have used the concept of filter().

Python3

# Python program to illustrate the intersection
# of two lists, sublists and use of filter()
def intersection(lst1, lst2):
    lst3 = [list(filter(lambda x: x in lst1, sublist)) for sublist in lst2]
    return lst3

# Driver Code
lst1 = [1, 6, 7, 10, 13, 28, 32, 41, 58, 63]
lst2 = [[13, 17, 18, 21, 32], [7, 11, 13, 14, 28], [1, 5, 6, 8, 15, 16]]
print(intersection(lst1, lst2))

Working: The filter part takes each sublist’s item and checks to see if it is in the source list. The list comprehension is executed for each sublist in list2. 
Output: 

[[13, 32], [7, 13, 28], [1, 6]]

Method 6: Using reduce():
Algorithm:

1. Import the reduce function from functools module.
2. Define two lists.
3. Initialize the variable intersection with an empty list.
4. Use the reduce function to iterate over the elements of lst1.
5. Inside the lambda function, check if the current element is present in lst2 and not already present in the intersection list.
6. If it is, then add the current element to the intersection list.
7. Return the intersection list.
8. Print the intersection list.

Python3

from functools import reduce

lst1 = [15, 9, 10, 56, 23, 78, 5, 4, 9]
lst2 = [9, 4, 5, 36, 47, 26, 10, 45, 87]

intersection = reduce(lambda acc, x: acc + [x] if x in lst2 and x not in acc else acc, lst1, [])

print(intersection)
#This code is contributed by Rayudu.

Output

[9, 10, 5, 4]

Time Complexity: O(n^2), where n is the length of lst1.
Space Complexity: O(n), where n is the length of lst1.