2023-06-21
2448. Minimum Cost to Make Array Equal

Topic: Array, Binary Search, Greedy, Sorting, Prefix Sum
Difficulty: Hard

Problem:
You are given two 0-indexed arrays nums and cost consisting each of n positive integers.

You can do the following operation any number of times:

• Increase or decrease any element of the array nums by 1.

The cost of doing one operation on the i^th element is cost[i].

Return the minimum total cost such that all the elements of the array nums become equal.

Example 1:

Input: nums = [1,3,5,2], cost = [2,3,1,14]
Output: 8
Explanation: We can make all the elements equal to 2 in the following way:
- Increase the 0^th element one time. The cost is 2.
- Decrease the 1^st element one time. The cost is 3.
- Decrease the 2^nd element three times. The cost is 1 + 1 + 1 = 3.
The total cost is 2 + 3 + 3 = 8.
It can be shown that we cannot make the array equal with a smaller cost.

Example 2:

Input: nums = [2,2,2,2,2], cost = [4,2,8,1,3]
Output: 0
Explanation: All the elements are already equal, so no operations are needed.

Constraints:

• n == nums.length == cost.length
• 1 <= n <= 10^5
• 1 <= nums[i], cost[i] <= 10^6

2023-06-22
714. Best Time to Buy and Sell Stock with Transaction Fee

Topic: Array, Dynamic Programming, Greedy
Difficulty: Medium

Problem:
You are given an array prices where prices[i] is the price of a given stock on the i^th day, and an integer fee representing a transaction fee.

Find the maximum profit you can achieve. You may complete as many transactions as you like, but you need to pay the transaction fee for each transaction.

Note: You may not engage in multiple transactions simultaneously (i.e., you must sell the stock before you buy again).

Example 1:

Input: prices = [1,3,2,8,4,9], fee = 2
Output: 8
Explanation: The maximum profit can be achieved by:
- Buying at prices[0] = 1
- Selling at prices[3] = 8
- Buying at prices[4] = 4
- Selling at prices[5] = 9
The total profit is ((8 - 1) - 2) + ((9 - 4) - 2) = 8.

Example 2:

Input: prices = [1,3,7,5,10,3], fee = 3
Output: 6

Constraints:

• 1 <= prices.length <= 5 * 10^4
• 1 <= prices[i] < 5 * 10^4
• 0 <= fee < 5 * 10^4

2023-06-23
1027. Longest Arithmetic Subsequence

Topic: Array, Hash Table, Binary Search, Dynamic Programming
Difficulty: Medium

Problem:
Given an array nums of integers, return the length of the longest arithmetic subsequence in nums.

Note that:

• A subsequence is an array that can be derived from another array by deleting some or no elements without changing the order of the remaining elements.
• A sequence seq is arithmetic if seq[i + 1] - seq[i] are all the same value (for 0 <= i < seq.length - 1).

Example 1:

Input: nums = [3,6,9,12]
Output: 4
Explanation:  The whole array is an arithmetic sequence with steps of length = 3.

Example 2:

Input: nums = [9,4,7,2,10]
Output: 3
Explanation:  The longest arithmetic subsequence is [4,7,10].

Example 3:

Input: nums = [20,1,15,3,10,5,8]
Output: 4
Explanation:  The longest arithmetic subsequence is [20,15,10,5].

Constraints:

• 2 <= nums.length <= 1000
• 0 <= nums[i] <= 500

2023-06-24
956. Tallest Billboard

Topic: Array, Dynamic Programming
Difficulty: Hard

Problem:
You are installing a billboard and want it to have the largest height. The billboard will have two steel supports, one on each side. Each steel support must be an equal height.

You are given a collection of rods that can be welded together. For example, if you have rods of lengths 1, 2, and 3, you can weld them together to make a support of length 6.

Return the largest possible height of your billboard installation. If you cannot support the billboard, return 0.

Example 1:

Input: rods = [1,2,3,6]
Output: 6
Explanation: We have two disjoint subsets {1,2,3} and {6}, which have the same sum = 6.

Example 2:

Input: rods = [1,2,3,4,5,6]
Output: 10
Explanation: We have two disjoint subsets {2,3,5} and {4,6}, which have the same sum = 10.

Example 3:

Input: rods = [1,2]
Output: 0
Explanation: The billboard cannot be supported, so we return 0.

Constraints:

• 1 <= rods.length <= 20
• 1 <= rods[i] <= 1000
• sum(rods[i]) <= 5000

2023-06-25
1575. Count All Possible Routes

Topic: Array, Dynamic Programming, Memoization
Difficulty: Hard

Problem:
You are given an array of distinct positive integers locations where locations[i] represents the position of city i. You are also given integers start, finish and fuel representing the starting city, ending city, and the initial amount of fuel you have, respectively.

At each step, if you are at city i, you can pick any city j such that j != i and 0 <= j < locations.length and move to city j. Moving from city i to city j reduces the amount of fuel you have by |locations[i] - locations[j]|. Please notice that |x| denotes the absolute value of x.

Notice that fuel cannot become negative at any point in time, and that you are allowed to visit any city more than once (including start and finish).

Return the count of all possible routes from start to finish. Since the answer may be too large, return it modulo 10^9 + 7.

Example 1:

Input: locations = [2,3,6,8,4], start = 1, finish = 3, fuel = 5
Output: 4
Explanation: The following are all possible routes, each uses 5 units of fuel:
1 -> 3
1 -> 2 -> 3
1 -> 4 -> 3
1 -> 4 -> 2 -> 3

Example 2:

Input: locations = [4,3,1], start = 1, finish = 0, fuel = 6
Output: 5
Explanation: The following are all possible routes:
1 -> 0, used fuel = 1
1 -> 2 -> 0, used fuel = 5
1 -> 2 -> 1 -> 0, used fuel = 5
1 -> 0 -> 1 -> 0, used fuel = 3
1 -> 0 -> 1 -> 0 -> 1 -> 0, used fuel = 5

Example 3:

Input: locations = [5,2,1], start = 0, finish = 2, fuel = 3
Output: 0
Explanation: It is impossible to get from 0 to 2 using only 3 units of fuel since the shortest route needs 4 units of fuel.

Constraints:

• 2 <= locations.length <= 100
• 1 <= locations[i] <= 10^9
• All integers in locations are distinct.
• 0 <= start, finish < locations.length
• 1 <= fuel <= 200

2023-06-26
2462. Total Cost to Hire K Workers

Topic: Array, Two Pointers, Heap (Priority Queue), Simulation
Difficulty: Medium

Problem:
You are given a 0-indexed integer array costs where costs[i] is the cost of hiring the i^th worker.

You are also given two integers k and candidates. We want to hire exactly k workers according to the following rules:

• You will run k sessions and hire exactly one worker in each session.
• In each hiring session, choose the worker with the lowest cost from either the first candidates workers or the last candidates workers. Break the tie by the smallest index.
• For example, if costs = [3,2,7,7,1,2] and candidates = 2, then in the first hiring session, we will choose the 4^th worker because they have the lowest cost [3,2,7,7,1,2].
• In the second hiring session, we will choose 1^st worker because they have the same lowest cost as 4^th worker but they have the smallest index [3,2,7,7,2]. Please note that the indexing may be changed in the process.
• If there are fewer than candidates workers remaining, choose the worker with the lowest cost among them. Break the tie by the smallest index.
• A worker can only be chosen once.

Return the total cost to hire exactly k workers.

Example 1:

Input: costs = [17,12,10,2,7,2,11,20,8], k = 3, candidates = 4
Output: 11
Explanation: We hire 3 workers in total. The total cost is initially 0.
- In the first hiring round we choose the worker from [17,12,10,2,7,2,11,20,8]. The lowest cost is 2, and we break the tie by the smallest index, which is 3. The total cost = 0 + 2 = 2.
- In the second hiring round we choose the worker from [17,12,10,7,2,11,20,8]. The lowest cost is 2 (index 4). The total cost = 2 + 2 = 4.
- In the third hiring round we choose the worker from [17,12,10,7,11,20,8]. The lowest cost is 7 (index 3). The total cost = 4 + 7 = 11. Notice that the worker with index 3 was common in the first and last four workers.
The total hiring cost is 11.

Example 2:

Input: costs = [1,2,4,1], k = 3, candidates = 3
Output: 4
Explanation: We hire 3 workers in total. The total cost is initially 0.
- In the first hiring round we choose the worker from [1,2,4,1]. The lowest cost is 1, and we break the tie by the smallest index, which is 0. The total cost = 0 + 1 = 1. Notice that workers with index 1 and 2 are common in the first and last 3 workers.
- In the second hiring round we choose the worker from [2,4,1]. The lowest cost is 1 (index 2). The total cost = 1 + 1 = 2.
- In the third hiring round there are less than three candidates. We choose the worker from the remaining workers [2,4]. The lowest cost is 2 (index 0). The total cost = 2 + 2 = 4.
The total hiring cost is 4.

Constraints:

• 1 <= costs.length <= 10^5
• 1 <= costs[i] <= 10^5
• 1 <= k, candidates <= costs.length

2023-06-27
373. Find K Pairs with Smallest Sums

Topic: Array, Heap (Priority Queue)
Difficulty: Medium

Problem:
You are given two integer arrays nums1 and nums2 sorted in ascending order and an integer k.

Define a pair (u, v) which consists of one element from the first array and one element from the second array.

Return the k pairs (u_1, v_1), (u_2, v_2), ..., (u_k, v_k) with the smallest sums.

Example 1:

Input: nums1 = [1,7,11], nums2 = [2,4,6], k = 3
Output: [[1,2],[1,4],[1,6]]
Explanation: The first 3 pairs are returned from the sequence: [1,2],[1,4],[1,6],[7,2],[7,4],[11,2],[7,6],[11,4],[11,6]

Example 2:

Input: nums1 = [1,1,2], nums2 = [1,2,3], k = 2
Output: [[1,1],[1,1]]
Explanation: The first 2 pairs are returned from the sequence: [1,1],[1,1],[1,2],[2,1],[1,2],[2,2],[1,3],[1,3],[2,3]

Example 3:

Input: nums1 = [1,2], nums2 = [3], k = 3
Output: [[1,3],[2,3]]
Explanation: All possible pairs are returned from the sequence: [1,3],[2,3]

Constraints:

• 1 <= nums1.length, nums2.length <= 10^5
• -10^9 <= nums1[i], nums2[i] <= 10^9
• nums1 and nums2 both are sorted in ascending order.
• 1 <= k <= 10^4

2023-06-28
1514. Path with Maximum Probability

Topic: Array, Graph, Heap (Priority Queue), Shortest Path
Difficulty: Medium

Problem:
You are given an undirected weighted graph of n nodes (0-indexed), represented by an edge list where edges[i] = [a, b] is an undirected edge connecting the nodes a and b with a probability of success of traversing that edge succProb[i].

Given two nodes start and end, find the path with the maximum probability of success to go from start to end and return its success probability.

If there is no path from start to end, return 0. Your answer will be accepted if it differs from the correct answer by at most 1e-5.

Example 1:

Image: https://assets.leetcode.com/uploads/2019/09/20/1558_ex1.png

Input: n = 3, edges = [[0,1],[1,2],[0,2]], succProb = [0.5,0.5,0.2], start = 0, end = 2
Output: 0.25000
Explanation: There are two paths from start to end, one having a probability of success = 0.2 and the other has 0.5 * 0.5 = 0.25.

Example 2:

Image: https://assets.leetcode.com/uploads/2019/09/20/1558_ex2.png

Input: n = 3, edges = [[0,1],[1,2],[0,2]], succProb = [0.5,0.5,0.3], start = 0, end = 2
Output: 0.30000

Example 3:

Image: https://assets.leetcode.com/uploads/2019/09/20/1558_ex3.png

Input: n = 3, edges = [[0,1]], succProb = [0.5], start = 0, end = 2
Output: 0.00000
Explanation: There is no path between 0 and 2.

Constraints:

• 2 <= n <= 10^4
• 0 <= start, end < n
• start != end
• 0 <= a, b < n
• a != b
• 0 <= succProb.length == edges.length <= 2*10^4
• 0 <= succProb[i] <= 1
• There is at most one edge between every two nodes.

2023-06-29
864. Shortest Path to Get All Keys

Topic: Array, Bit Manipulation, Breadth-First Search, Matrix
Difficulty: Hard

Problem:
You are given an m x n grid grid where:

• '.' is an empty cell.
• '#' is a wall.
• '@' is the starting point.
• Lowercase letters represent keys.
• Uppercase letters represent locks.

You start at the starting point and one move consists of walking one space in one of the four cardinal directions. You cannot walk outside the grid, or walk into a wall.

If you walk over a key, you can pick it up and you cannot walk over a lock unless you have its corresponding key.

For some 1 <= k <= 6, there is exactly one lowercase and one uppercase letter of the first k letters of the English alphabet in the grid. This means that there is exactly one key for each lock, and one lock for each key; and also that the letters used to represent the keys and locks were chosen in the same order as the English alphabet.

Return the lowest number of moves to acquire all keys. If it is impossible, return -1.

Example 1:

Image: https://assets.leetcode.com/uploads/2021/07/23/lc-keys2.jpg

Input: grid = ["@.a..","###.#","b.A.B"]
Output: 8
Explanation: Note that the goal is to obtain all the keys not to open all the locks.

Example 2:

Image: https://assets.leetcode.com/uploads/2021/07/23/lc-key2.jpg

Input: grid = ["@..aA","..B#.","....b"]
Output: 6

Example 3:

Image: https://assets.leetcode.com/uploads/2021/07/23/lc-keys3.jpg

Input: grid = ["@Aa"]
Output: -1

Constraints:

• m == grid.length
• n == grid[i].length
• 1 <= m, n <= 30
• grid[i][j] is either an English letter, '.', '#', or '@'.
• The number of keys in the grid is in the range [1, 6].
• Each key in the grid is unique.
• Each key in the grid has a matching lock.

2023-06-30
1970. Last Day Where You Can Still Cross

Topic: Array, Binary Search, Depth-First Search, Breadth-First Search, Union Find, Matrix
Difficulty: Hard

Problem:
There is a 1-based binary matrix where 0 represents land and 1 represents water. You are given integers row and col representing the number of rows and columns in the matrix, respectively.

Initially on day 0, the entire matrix is land. However, each day a new cell becomes flooded with water. You are given a 1-based 2D array cells, where cells[i] = [r_i, c_i] represents that on the i^th day, the cell on the r_i^th row and c_i^th column (1-based coordinates) will be covered with water (i.e., changed to 1).

You want to find the last day that it is possible to walk from the top to the bottom by only walking on land cells. You can start from any cell in the top row and end at any cell in the bottom row. You can only travel in the four cardinal directions (left, right, up, and down).

Return the last day where it is possible to walk from the top to the bottom by only walking on land cells.

Example 1:

Image: https://assets.leetcode.com/uploads/2021/07/27/1.png

Input: row = 2, col = 2, cells = [[1,1],[2,1],[1,2],[2,2]]
Output: 2
Explanation: The above image depicts how the matrix changes each day starting from day 0.
The last day where it is possible to cross from top to bottom is on day 2.

Example 2:

Image: https://assets.leetcode.com/uploads/2021/07/27/2.png

Input: row = 2, col = 2, cells = [[1,1],[1,2],[2,1],[2,2]]
Output: 1
Explanation: The above image depicts how the matrix changes each day starting from day 0.
The last day where it is possible to cross from top to bottom is on day 1.

Example 3:

Image: https://assets.leetcode.com/uploads/2021/07/27/3.png

Input: row = 3, col = 3, cells = [[1,2],[2,1],[3,3],[2,2],[1,1],[1,3],[2,3],[3,2],[3,1]]
Output: 3
Explanation: The above image depicts how the matrix changes each day starting from day 0.
The last day where it is possible to cross from top to bottom is on day 3.

Constraints:

• 2 <= row, col <= 2 * 10^4
• 4 <= row * col <= 2 * 10^4
• cells.length == row * col
• 1 <= r_i <= row
• 1 <= c_i <= col
• All the values of cells are unique.

2023-07-01
2305. Fair Distribution of Cookies

Topic: Array, Dynamic Programming, Backtracking, Bit Manipulation, Bitmask
Difficulty: Medium

Problem:
You are given an integer array cookies, where cookies[i] denotes the number of cookies in the i^th bag. You are also given an integer k that denotes the number of children to distribute all the bags of cookies to. All the cookies in the same bag must go to the same child and cannot be split up.

The unfairness of a distribution is defined as the maximum total cookies obtained by a single child in the distribution.

Return the minimum unfairness of all distributions.

Example 1:

Input: cookies = [8,15,10,20,8], k = 2
Output: 31
Explanation: One optimal distribution is [8,15,8] and [10,20]
- The 1^st child receives [8,15,8] which has a total of 8 + 15 + 8 = 31 cookies.
- The 2^nd child receives [10,20] which has a total of 10 + 20 = 30 cookies.
The unfairness of the distribution is max(31,30) = 31.
It can be shown that there is no distribution with an unfairness less than 31.

Example 2:

Input: cookies = [6,1,3,2,2,4,1,2], k = 3
Output: 7
Explanation: One optimal distribution is [6,1], [3,2,2], and [4,1,2]
- The 1^st child receives [6,1] which has a total of 6 + 1 = 7 cookies.
- The 2^nd child receives [3,2,2] which has a total of 3 + 2 + 2 = 7 cookies.
- The 3^rd child receives [4,1,2] which has a total of 4 + 1 + 2 = 7 cookies.
The unfairness of the distribution is max(7,7,7) = 7.
It can be shown that there is no distribution with an unfairness less than 7.

Constraints:

• 2 <= cookies.length <= 8
• 1 <= cookies[i] <= 10^5
• 2 <= k <= cookies.length

2023-07-02
1601. Maximum Number of Achievable Transfer Requests

Topic: Array, Backtracking, Bit Manipulation, Enumeration
Difficulty: Hard

Problem:
We have n buildings numbered from 0 to n - 1. Each building has a number of employees. It's transfer season, and some employees want to change the building they reside in.

You are given an array requests where requests[i] = [from_i, to_i] represents an employee's request to transfer from building from_i to building to_i.

All buildings are full, so a list of requests is achievable only if for each building, the net change in employee transfers is zero. This means the number of employees leaving is equal to the number of employees moving in. For example if n = 3 and two employees are leaving building 0, one is leaving building 1, and one is leaving building 2, there should be two employees moving to building 0, one employee moving to building 1, and one employee moving to building 2.

Return the maximum number of achievable requests.

Example 1:

Image: https://assets.leetcode.com/uploads/2020/09/10/move1.jpg

Input: n = 5, requests = [[0,1],[1,0],[0,1],[1,2],[2,0],[3,4]]
Output: 5
Explantion: Let's see the requests:
From building 0 we have employees x and y and both want to move to building 1.
From building 1 we have employees a and b and they want to move to buildings 2 and 0 respectively.
From building 2 we have employee z and they want to move to building 0.
From building 3 we have employee c and they want to move to building 4.
From building 4 we don't have any requests.
We can achieve the requests of users x and b by swapping their places.
We can achieve the requests of users y, a and z by swapping the places in the 3 buildings.

Example 2:

Image: https://assets.leetcode.com/uploads/2020/09/10/move2.jpg

Input: n = 3, requests = [[0,0],[1,2],[2,1]]
Output: 3
Explantion: Let's see the requests:
From building 0 we have employee x and they want to stay in the same building 0.
From building 1 we have employee y and they want to move to building 2.
From building 2 we have employee z and they want to move to building 1.
We can achieve all the requests.

Example 3:

Input: n = 4, requests = [[0,3],[3,1],[1,2],[2,0]]
Output: 4

Constraints:

• 1 <= n <= 20
• 1 <= requests.length <= 16
• requests[i].length == 2
• 0 <= from_i, to_i < n

2023-07-03
859. Buddy Strings

Topic: Hash Table, String
Difficulty: Easy

Problem:
Given two strings s and goal, return true if you can swap two letters in s so the result is equal to goal, otherwise, return false.

Swapping letters is defined as taking two indices i and j (0-indexed) such that i != j and swapping the characters at s[i] and s[j].

• For example, swapping at indices 0 and 2 in "abcd" results in "cbad".

Example 1:

Input: s = "ab", goal = "ba"
Output: true
Explanation: You can swap s[0] = 'a' and s[1] = 'b' to get "ba", which is equal to goal.

Example 2:

Input: s = "ab", goal = "ab"
Output: false
Explanation: The only letters you can swap are s[0] = 'a' and s[1] = 'b', which results in "ba" != goal.

Example 3:

Input: s = "aa", goal = "aa"
Output: true
Explanation: You can swap s[0] = 'a' and s[1] = 'a' to get "aa", which is equal to goal.

Constraints:

• 1 <= s.length, goal.length <= 2 * 10^4
• s and goal consist of lowercase letters.

2023-07-04
137. Single Number II

Topic: Array, Bit Manipulation
Difficulty: Medium

Problem:
Given an integer array nums where every element appears three times except for one, which appears exactly once. Find the single element and return it.

You must implement a solution with a linear runtime complexity and use only constant extra space.

Example 1:

Input: nums = [2,2,3,2]
Output: 3

Example 2:

Input: nums = [0,1,0,1,0,1,99]
Output: 99

Constraints:

• 1 <= nums.length <= 3 * 10^4
• -2^31 <= nums[i] <= 2^31 - 1
• Each element in nums appears exactly three times except for one element which appears once.

2023-07-05
1493. Longest Subarray of 1's After Deleting One Element

Topic: Array, Dynamic Programming, Sliding Window
Difficulty: Medium

Problem:
Given a binary array nums, you should delete one element from it.

Return the size of the longest non-empty subarray containing only 1's in the resulting array. Return 0 if there is no such subarray.

Example 1:

Input: nums = [1,1,0,1]
Output: 3
Explanation: After deleting the number in position 2, [1,1,1] contains 3 numbers with value of 1's.

Example 2:

Input: nums = [0,1,1,1,0,1,1,0,1]
Output: 5
Explanation: After deleting the number in position 4, [0,1,1,1,1,1,0,1] longest subarray with value of 1's is [1,1,1,1,1].

Example 3:

Input: nums = [1,1,1]
Output: 2
Explanation: You must delete one element.

Constraints:

• 1 <= nums.length <= 10^5
• nums[i] is either 0 or 1.

2023-07-06
209. Minimum Size Subarray Sum

Topic: Array, Binary Search, Sliding Window, Prefix Sum
Difficulty: Medium

Problem:
Given an array of positive integers nums and a positive integer target, return the minimal length of a subarray whose sum is greater than or equal to target. If there is no such subarray, return 0 instead.

Example 1:

Input: target = 7, nums = [2,3,1,2,4,3]
Output: 2
Explanation: The subarray [4,3] has the minimal length under the problem constraint.

Example 2:

Input: target = 4, nums = [1,4,4]
Output: 1

Example 3:

Input: target = 11, nums = [1,1,1,1,1,1,1,1]
Output: 0

Constraints:

• 1 <= target <= 10^9
• 1 <= nums.length <= 10^5
• 1 <= nums[i] <= 10^4

Follow up: If you have figured out the O(n) solution, try coding another solution of which the time complexity is O(n log(n)).

2023-07-07
2024. Maximize the Confusion of an Exam

Topic: String, Binary Search, Sliding Window, Prefix Sum
Difficulty: Medium

Problem:
A teacher is writing a test with n true/false questions, with 'T' denoting true and 'F' denoting false. He wants to confuse the students by maximizing the number of consecutive questions with the same answer (multiple trues or multiple falses in a row).

You are given a string answerKey, where answerKey[i] is the original answer to the i^th question. In addition, you are given an integer k, the maximum number of times you may perform the following operation:

• Change the answer key for any question to 'T' or 'F' (i.e., set answerKey[i] to 'T' or 'F').

Return the maximum number of consecutive 'T's or 'F's in the answer key after performing the operation at most k times.

Example 1:

Input: answerKey = "TTFF", k = 2
Output: 4
Explanation: We can replace both the 'F's with 'T's to make answerKey = "TTTT".
There are four consecutive 'T's.

Example 2:

Input: answerKey = "TFFT", k = 1
Output: 3
Explanation: We can replace the first 'T' with an 'F' to make answerKey = "FFFT".
Alternatively, we can replace the second 'T' with an 'F' to make answerKey = "TFFF".
In both cases, there are three consecutive 'F's.

Example 3:

Input: answerKey = "TTFTTFTT", k = 1
Output: 5
Explanation: We can replace the first 'F' to make answerKey = "TTTTTFTT"
Alternatively, we can replace the second 'F' to make answerKey = "TTFTTTTT". 
In both cases, there are five consecutive 'T's.

Constraints:

• n == answerKey.length
• 1 <= n <= 5 * 10^4
• answerKey[i] is either 'T' or 'F'
• 1 <= k <= n

2023-07-08
2551. Put Marbles in Bags

Topic: Array, Greedy, Sorting, Heap (Priority Queue)
Difficulty: Hard

Problem:
You have k bags. You are given a 0-indexed integer array weights where weights[i] is the weight of the i^th marble. You are also given the integer k.

Divide the marbles into the k bags according to the following rules:

• No bag is empty.
• If the i^th marble and j^th marble are in a bag, then all marbles with an index between the i^th and j^th indices should also be in that same bag.
• If a bag consists of all the marbles with an index from i to j inclusively, then the cost of the bag is weights[i] + weights[j].

The score after distributing the marbles is the sum of the costs of all the k bags.

Return the difference between the maximum and minimum scores among marble distributions.

Example 1:

Input: weights = [1,3,5,1], k = 2
Output: 4
Explanation: 
The distribution [1],[3,5,1] results in the minimal score of (1+1) + (3+1) = 6. 
The distribution [1,3],[5,1], results in the maximal score of (1+3) + (5+1) = 10. 
Thus, we return their difference 10 - 6 = 4.

Example 2:

Input: weights = [1, 3], k = 2
Output: 0
Explanation: The only distribution possible is [1],[3]. 
Since both the maximal and minimal score are the same, we return 0.

Constraints:

• 1 <= k <= weights.length <= 10^5
• 1 <= weights[i] <= 10^9

2023-07-09
2272. Substring With Largest Variance

Topic: Array, Dynamic Programming
Difficulty: Hard

Problem:
The variance of a string is defined as the largest difference between the number of occurrences of any 2 characters present in the string. Note the two characters may or may not be the same.

Given a string s consisting of lowercase English letters only, return the largest variance possible among all substrings of s.

A substring is a contiguous sequence of characters within a string.

Example 1:

Input: s = "aababbb"
Output: 3
Explanation:
All possible variances along with their respective substrings are listed below:
- Variance 0 for substrings "a", "aa", "ab", "abab", "aababb", "ba", "b", "bb", and "bbb".
- Variance 1 for substrings "aab", "aba", "abb", "aabab", "ababb", "aababbb", and "bab".
- Variance 2 for substrings "aaba", "ababbb", "abbb", and "babb".
- Variance 3 for substring "babbb".
Since the largest possible variance is 3, we return it.

Example 2:

Input: s = "abcde"
Output: 0
Explanation:
No letter occurs more than once in s, so the variance of every substring is 0.

Constraints:

• 1 <= s.length <= 10^4
• s consists of lowercase English letters.

2023-07-10
111. Minimum Depth of Binary Tree

Topic: Tree, Depth-First Search, Breadth-First Search, Binary Tree
Difficulty: Easy

Problem:
Given a binary tree, find its minimum depth.

The minimum depth is the number of nodes along the shortest path from the root node down to the nearest leaf node.

Note: A leaf is a node with no children.

Example 1:

Image: https://assets.leetcode.com/uploads/2020/10/12/ex_depth.jpg

Input: root = [3,9,20,null,null,15,7]
Output: 2

Example 2:

Input: root = [2,null,3,null,4,null,5,null,6]
Output: 5

Constraints:

• The number of nodes in the tree is in the range [0, 10^5].
• -1000 <= Node.val <= 1000