set in python | Lec-17
In this video, I have talked about the fundamentals of programming and Python. If you complete this, you will be well-versed in using tuples for different use cases.
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Пікірлер: 11
i always shyed away from python but because of you i started learning it. Thanks a million you are awesome.
superb video thanks
Big fan Manish Kumar :).
time complexity - o(n) becoz of only one loop , extra spacis used but in worst case maximum element can be appended then o(n) space complexity
Time and Space both will be O(n). As it has to traverse to each number and for storing the number also it has to add all till the match.
Time complexity O(n) as it traverse using for loop and space complexity O(N) as it uses space to append the result
time complexity is o(n^3) since to ( first loop o(n) x check element in list1 o(n) x check in list2 o(n) )
# Q1 list1 = [1,2,3,4,5,6] list2 = [4,5,6,7,8] t1 = set(list1) t2 = set(list2) print(f"Missing values in list1 ={list(t2.difference(t1))}") print(f"Additional values in list2 = {list(t1.difference(t2))}") print(f"Missing values in list1 = {list (t1.difference(t2))}") print(f"Additional values in list2 ={list(t2.difference(t1))}") # Q2 ar1 = [1, 5, 10, 20, 40, 80] ar2 = [6, 7, 20, 80, 100] ar3 = [3, 4, 15, 20, 30, 70, 80, 120] common_items = set(ar1).intersection(set(ar2),set(ar3)) print(list(common_items)) Time complexity will be O(n) to convert to set, and O(n) to do the intersetion. So , final time complexity will be O(n) Space complexity will be O(n) too as each list will be stored as set.
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@PranshuHasani
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