Sometimes, while working with records, we can have a problem in which we need to multiply all the columns of a container of lists that are tuples. This kind of application is common in web development domain. Let’s discuss certain ways in which this task can be performed.
Method #1 : Using loop + list comprehension + zip()
This task can be performed using combination of above functions. In this, we cumulate the like index elements, i.e columns using zip(), and then iterate through them using list comprehension and perform product using explicit function.
Python3
# Python3 code to demonstrate working of # Record Index Product # using list comprehension + loop + zip() # getting Product def prod(val) : res = 1 for ele in val: res *= ele return res # initialize list test_list = [(1, 2, 3), (6, 7, 6), (1, 6, 8)] # printing original list print("The original list : " + str(test_list)) # Record Index Product # using list comprehension + loop + zip() res = [prod(ele) for ele in zip(*test_list)] # printing result print("The Cumulative column product is : " + str(res)) |
Output:
The original list : [(1, 2, 3), (6, 7, 6), (1, 6, 8)] The Cumulative column product is : [6, 84, 144]
Time Complexity: O(n) where n is the number of elements in the list “test_list”. loop + list comprehension + zip() performs n number of operations.
Auxiliary Space: O(n), extra space is required where n is the number of elements in the list
Method #2 : Using zip() + map() + loop
This method is similar to the above method. In this, the task performed by list comprehension is performed by map(), which extends the product of columns to zipped elements.
Python3
# Python3 code to demonstrate working of # Record Index Product # using zip() + map() + loop # getting Product def prod(val) : res = 1 for ele in val: res *= ele return res # initialize list test_list = [(1, 2, 3), (6, 7, 6), (1, 6, 8)] # printing original list print("The original list : " + str(test_list)) # Record Index Product # using zip() + map() + loop res = list(map(prod, zip(*test_list))) # printing result print("The Cumulative column product is : " + str(res)) |
Output:
The original list : [(1, 2, 3), (6, 7, 6), (1, 6, 8)] The Cumulative column product is : [6, 84, 144]
Time Complexity: O(n*n), where n is the length of the input list. This is because we’re using zip() + map() + loop which has a time complexity of O(n*n) in the worst case.
Auxiliary Space: O(n), as we’re using additional space res other than the input list itself with the same size of input list
# Method #3 : Using numpy.prod()
This method uses the numpy library which is an optimization of the above both methods. In this, we take the help of in-built function prod() which performs the product of all the elements in an array.
Python3
# Python3 code to demonstrate working of# Record Index Product# using numpy.prod() # importing numpyimport numpy as np # initialize listtest_list = [(1, 2, 3), (6, 7, 6), (1, 6, 8)] # printing original listprint("The original list : " + str(test_list)) # Record Index Product# using numpy.prod()res = np.prod(list(zip(*test_list)), axis = 1) # printing resultprint("The Cumulative column product is : " + str(res))#This code is contributed by Edula Vinay Kumar Reddy |
Output:
The original list : [(1, 2, 3), (6, 7, 6), (1, 6, 8)]
The Cumulative column product is : [ 6 84 144]
Time complexity: O(n)
Space complexity: O(n)
