Contiguous Array | Using same Pattern Approach | Similar Problems | Leetcode 525
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This is the 86th Video of our Playlist "Arrays 1D/2D : Popular Interview Problems".
In this video we will try to solve a very good pattern problem : Contiguous Array | Using same Pattern Approach | Similar Problems | Leetcode 525
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Problem Name : Contiguous Array | Using same Pattern Approach | Similar Problems | Leetcode 525
Company Tags : Meta, Google
My solutions on Github(C++ & JAVA) : https://github.com/MAZHARMIK/Interview_DS_Algo/blob/master/Arrays/Cumulative_Sum(Prefix%20Array)/Contiguous%20Array.cpp
Leetcode Link : https://leetcode.com/problems/contiguous-array/description/
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Approaches Summary :
We are using the same pattern approach just like Leetcode-560, 930, 1074.
Leetcode-560, 1074 - https://youtu.be/-SWrz90jCUM?si=9dnkn65t_pgeHgyA
Leetcode 930 - https://youtu.be/5Quv9nnZs34?si=aMNPNqLGPaoluWrR
The provided approach is a solution to a problem aiming to find the maximum length of a contiguous subarray with an equal number of 0s and 1s within a given vector nums. The algorithm utilizes an unordered map mp to store the cumulative sum of the array elements encountered so far, with the key being the cumulative sum and the value being the index at which the sum was achieved. The algorithm iterates through the vector, updating the cumulative sum based on the value of the current element (incrementing by 1 for 1s and decrementing by 1 for 0s). At each step, it checks if the current cumulative sum exists in the map. If it does, it updates the maximum length (maxL) by taking the difference between the current index and the index stored in the map for that cumulative sum. Otherwise, it adds the current cumulative sum and its corresponding index to the map. Finally, the algorithm returns the maximum length found, which represents the length of the longest contiguous subarray with an equal number of 0s and 1s.
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✨ Timelines✨
00:00 - Introduction
03:22 - Why not Sliding Window ?
06:10 - Intuition using pattern Leetcode-560
10:51 - Complete Dry Run
18:14 - Coding it up
21:03 - Time & Space
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