Given a list of lists, the task is to multiply each element in a sublist by its index and return a summed list. Given below are a few methods to solve the problem.
Method #1: Using Naive Method
Python3
# Python3 code to demonstrate # to multiply numbers with position # and add them to return num import numpy as np # initialising list ini_list = [[3, 4, 7], [ 6, 7, 8], [ 10, 7, 5], [ 11, 12, 13]] # printing initial_list print ("initial_list ", ini_list) res = [] # Using Naive Method for sub_list in ini_list: sublistsum = 0 for i, value in enumerate(sub_list): sublistsum = sublistsum + i * value res.append(sublistsum) # printing result print ("result", res) |
initial_list [[3, 4, 7], [6, 7, 8], [10, 7, 5], [11, 12, 13]] result [18, 23, 17, 38]
Time complexity: O(n^2)
Auxiliary space: O(n)
Method #2: Using List comprehension
Python3
# Python3 code to demonstrate # to multiply numbers with position # and add them to return num # initialising list ini_list = [[3, 4, 7], [ 6, 7, 8], [ 10, 7, 5], [ 11, 12, 13]] # printing initial_list print ("initial_list ", ini_list) # Using list comprehension res = [sum(i * j for i, j in enumerate(sublist)) for sublist in ini_list] # printing result print ("result", res) |
initial_list [[3, 4, 7], [6, 7, 8], [10, 7, 5], [11, 12, 13]] result [18, 23, 17, 38]
Time complexity: O(nm), where n is the number of sublists in the input list and m is the length of each sublist.
Auxiliary space: O(n), where n is the number of sublists in the input list. This is because the program uses list comprehension to create a new list of the same length as the input list.
Method #3: Using numpy
Python3
# Python3 code to demonstrate# to multiply numbers with position# and add them to return numimport numpy as np# initialising listini_list = [[3, 4, 7], [ 6, 7, 8], [ 10, 7, 5], [ 11, 12, 13]]# printing initial_listprint ("initial_list ", ini_list)# Using numpyres = [np.arange(len(sublist)).dot(sublist) for sublist in ini_list]# printing resultprint ("result", res) |
initial_list [[3, 4, 7], [6, 7, 8], [10, 7, 5], [11, 12, 13]] result [18, 23, 17, 38]
Time Complexity: The time complexity of the given code is O(n^2), where n is the number of elements in the list.
Auxiliary Space: The auxiliary space complexity of the code is O(n), where n is the number of elements in the list.
Method #4: Using Zip and List Comprehension
We can use the zip() function to solve the problem of multiplying each element in a sublist by its index and returning a summed list. We can use the range() function to generate the indices for each element in the sublist, and use the zip() function to pair each element with its index. Then, we can use a list comprehension to compute the sum of the products of the indices and elements.
Python3
# Python3 code to demonstrate# to multiply numbers with position# and add them to return num# initializing listini_list = [[3, 4, 7], [6, 7, 8], [10, 7, 5], [11, 12, 13]]# printing initial_listprint("initial_list", ini_list)# using zip and list comprehensionres = [sum(i * j for i, j in zip(range(len(sublist)), sublist)) for sublist in ini_list]# printing resultprint("result", res)# This code is contributed by Edula Vinay Kumar Reddy |
initial_list [[3, 4, 7], [6, 7, 8], [10, 7, 5], [11, 12, 13]] result [18, 23, 17, 38]
Time Complexity: The time complexity of this approach is O(n*m) where n is the number of sublists in the initial list and m is the length of each sublist. This is because we are iterating through each sublist and then iterating through each element of the sublist to calculate the dot product.
Auxiliary Space: The auxiliary space of this approach is O(n) where n is the number of sublists in the initial list. This is because we are creating a new list (res) to store the dot product of each sublist.
