Data Structures and Algorithms | Python | Javascript

Solve LeetCode 875 banana eating problem by finding the minimum eating speed k that lets Koko finish all banana piles within h hours, staying on a single pile each hour.

Observe that k ranges from 1 to max(piles) and apply brute force to find the minimal k that finishes all piles within h hours using ceil(pile/k) per pile.

Use brute force to test k from 1 to max files, computing time to eat bananas by dividing by k and rounding up, return first k with time ≤ h.

Explain the brute force complexity by showing the outer loop runs m times and the inner loop runs n times, yielding O(n*m) time and O(1) space.

Learn to apply binary search to find the minimum workable speed for eating piles with max value m within a time limit, reducing time complexity to O(n log m).

Compare two binary search loop forms—while left < right and while left <= right—and learn how updating right to mid - 1 or to mid affects tracking the found index.

Use binary search to find the eating speed k to finish all banana piles in h hours. Start with left 1 and right max pile, updating by time with ceil(pile/k).

Implement an optimal JavaScript solution to find the minimum eating speed via binary search over banana piles. Compute time with Math.ceil and adjust bounds to fit the hour limit.

Explore LeetCode 42 trapping rainwater by analyzing an elevation map of non-negative integers with unit-width bars, visualize the barriers, and compute trapped water using two solution approaches with an example.

Identify the left and right max at each index, take their minimum to estimate water storage, then subtract the index height to get actual water.

Compute water at each index as min(left max, right max) minus the height. Include the current height in left max and right max to avoid negative results.

Explore two dynamic programming approaches to the trapping rain water problem: using left max and right max arrays, and a two-pointer method.

The lecture demonstrates a dynamic programming approach using two auxiliary arrays to compute left max and right max for the height array, handle edge cases, and calculate water storage.

Master the two-pointer approach to compute water storage with O(n) time and O(1) space by moving left and right pointers and updating left max and right max, avoiding auxiliary arrays.

Demonstrate that the two-pointer approach achieves O(n) time with a single pass and O(1) space by avoiding auxiliary arrays. Proceed to code the discussed method from this video.

Implement the two-pointer approach to solve the trapping rain water problem, tracking left and right indices, left max, and right max to accumulate water in a single pass.

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