Add solutions and explanations for problems 3583, 3772, 3771, 3770, 3766, 3768, 3767, 3765, 3761, 3760

books/All.md

@@ -8922,6 +8922,68 @@ class Solution:
         return res
 ```
 
+## 1431. Kids With the Greatest Number of Candies [Easy]
+https://leetcode.com/problems/kids-with-the-greatest-number-of-candies/
+
+### Explanation
+
+## 1431. Kids With the Greatest Number of Candies [Easy]
+
+https://leetcode.com/problems/kids-with-the-greatest-number-of-candies
+
+## Description
+There are `n` kids with candies. You are given an integer array `candies`, where each `candies[i]` represents the number of candies the `i`th kid has, and an integer `extraCandies`, denoting the number of extra candies that you have.
+
+Return a boolean array `result` of length `n`, where `result[i]` is `true` if, after giving the `i`th kid all the `extraCandies`, they will have the greatest number of candies among all the kids, or false otherwise.
+
+Note that multiple kids can have the greatest number of candies.
+
+**Examples**
+
+```text
+Input: candies = [2,3,5,1,3], extraCandies = 3
+Output: [true,true,true,false,true]
+Explanation: If you give all extraCandies to:
+- Kid 1, they will have 2 + 3 = 5 candies, which is the greatest among the kids.
+- Kid 2, they will have 3 + 3 = 6 candies, which is the greatest among the kids.
+- Kid 3, they will have 5 + 3 = 8 candies, which is the greatest among the kids.
+- Kid 4, they will have 1 + 3 = 4 candies, which is not the greatest among the kids.
+- Kid 5, they will have 3 + 3 = 6 candies, which is the greatest among the kids.
+
+Input: candies = [4,2,1,1,2], extraCandies = 1
+Output: [true,false,false,false,false]
+
+Input: candies = [12,1,12], extraCandies = 10
+Output: [true,false,true]
+```
+
+**Constraints**
+
+```text
+- n == candies.length
+- 2 <= n <= 100
+- 1 <= candies[i] <= 100
+- 1 <= extraCandies <= 50
+```
+
+## Hint
+For each kid, check if their candies plus `extraCandies` is at least as much as the current maximum.
+
+## Explanation
+First, you want to know the highest number of candies any kid currently has. This is important because you need a reference point to see if giving extra candies to a kid will make them "the greatest."
+
+For each kid, you add the `extraCandies` to their current amount. You do this because you want to see if, after the bonus, they can reach or beat the current maximum. If they do, you mark them as `True` in our answer list; otherwise, False.
+
+You only need to find the maximum once, and then just compare each kid's total to it. Don't need to recalculate the maximum for every kid.
+
+### Solution
+
+```python
+def kidsWithCandies(candies, extraCandies):
+    max_candies = max(candies)  # Find the current maximum
+    return [(c + extraCandies) >= max_candies for c in candies]
+```
+
 ## 1448. Count Good Nodes in Binary Tree [Medium]
 https://leetcode.com/problems/count-good-nodes-in-binary-tree/
 

books/LeetCode_75.md

@@ -517,6 +517,68 @@ def uniqueOccurrences(arr):
     return len(set(count.values())) == len(count)
 ```
 
+## 1431. Kids With the Greatest Number of Candies [Easy]
+https://leetcode.com/problems/kids-with-the-greatest-number-of-candies/
+
+### Explanation
+
+## 1431. Kids With the Greatest Number of Candies [Easy]
+
+https://leetcode.com/problems/kids-with-the-greatest-number-of-candies
+
+## Description
+There are `n` kids with candies. You are given an integer array `candies`, where each `candies[i]` represents the number of candies the `i`th kid has, and an integer `extraCandies`, denoting the number of extra candies that you have.
+
+Return a boolean array `result` of length `n`, where `result[i]` is `true` if, after giving the `i`th kid all the `extraCandies`, they will have the greatest number of candies among all the kids, or false otherwise.
+
+Note that multiple kids can have the greatest number of candies.
+
+**Examples**
+
+```text
+Input: candies = [2,3,5,1,3], extraCandies = 3
+Output: [true,true,true,false,true]
+Explanation: If you give all extraCandies to:
+- Kid 1, they will have 2 + 3 = 5 candies, which is the greatest among the kids.
+- Kid 2, they will have 3 + 3 = 6 candies, which is the greatest among the kids.
+- Kid 3, they will have 5 + 3 = 8 candies, which is the greatest among the kids.
+- Kid 4, they will have 1 + 3 = 4 candies, which is not the greatest among the kids.
+- Kid 5, they will have 3 + 3 = 6 candies, which is the greatest among the kids.
+
+Input: candies = [4,2,1,1,2], extraCandies = 1
+Output: [true,false,false,false,false]
+
+Input: candies = [12,1,12], extraCandies = 10
+Output: [true,false,true]
+```
+
+**Constraints**
+
+```text
+- n == candies.length
+- 2 <= n <= 100
+- 1 <= candies[i] <= 100
+- 1 <= extraCandies <= 50
+```
+
+## Hint
+For each kid, check if their candies plus `extraCandies` is at least as much as the current maximum.
+
+## Explanation
+First, you want to know the highest number of candies any kid currently has. This is important because you need a reference point to see if giving extra candies to a kid will make them "the greatest."
+
+For each kid, you add the `extraCandies` to their current amount. You do this because you want to see if, after the bonus, they can reach or beat the current maximum. If they do, you mark them as `True` in our answer list; otherwise, False.
+
+You only need to find the maximum once, and then just compare each kid's total to it. Don't need to recalculate the maximum for every kid.
+
+### Solution
+
+```python
+def kidsWithCandies(candies, extraCandies):
+    max_candies = max(candies)  # Find the current maximum
+    return [(c + extraCandies) >= max_candies for c in candies]
+```
+
 ## 2215. Find the Difference of Two Arrays [Easy]
 https://leetcode.com/problems/find-the-difference-of-two-arrays/
 

books/Visualization.md

@@ -86,6 +86,68 @@ def __init__(self, val=0, next=None):
         self.next = next
 ```
 
+## 1431. Kids With the Greatest Number of Candies [Easy]
+https://leetcode.com/problems/kids-with-the-greatest-number-of-candies/
+
+### Explanation
+
+## 1431. Kids With the Greatest Number of Candies [Easy]
+
+https://leetcode.com/problems/kids-with-the-greatest-number-of-candies
+
+## Description
+There are `n` kids with candies. You are given an integer array `candies`, where each `candies[i]` represents the number of candies the `i`th kid has, and an integer `extraCandies`, denoting the number of extra candies that you have.
+
+Return a boolean array `result` of length `n`, where `result[i]` is `true` if, after giving the `i`th kid all the `extraCandies`, they will have the greatest number of candies among all the kids, or false otherwise.
+
+Note that multiple kids can have the greatest number of candies.
+
+**Examples**
+
+```text
+Input: candies = [2,3,5,1,3], extraCandies = 3
+Output: [true,true,true,false,true]
+Explanation: If you give all extraCandies to:
+- Kid 1, they will have 2 + 3 = 5 candies, which is the greatest among the kids.
+- Kid 2, they will have 3 + 3 = 6 candies, which is the greatest among the kids.
+- Kid 3, they will have 5 + 3 = 8 candies, which is the greatest among the kids.
+- Kid 4, they will have 1 + 3 = 4 candies, which is not the greatest among the kids.
+- Kid 5, they will have 3 + 3 = 6 candies, which is the greatest among the kids.
+
+Input: candies = [4,2,1,1,2], extraCandies = 1
+Output: [true,false,false,false,false]
+
+Input: candies = [12,1,12], extraCandies = 10
+Output: [true,false,true]
+```
+
+**Constraints**
+
+```text
+- n == candies.length
+- 2 <= n <= 100
+- 1 <= candies[i] <= 100
+- 1 <= extraCandies <= 50
+```
+
+## Hint
+For each kid, check if their candies plus `extraCandies` is at least as much as the current maximum.
+
+## Explanation
+First, you want to know the highest number of candies any kid currently has. This is important because you need a reference point to see if giving extra candies to a kid will make them "the greatest."
+
+For each kid, you add the `extraCandies` to their current amount. You do this because you want to see if, after the bonus, they can reach or beat the current maximum. If they do, you mark them as `True` in our answer list; otherwise, False.
+
+You only need to find the maximum once, and then just compare each kid's total to it. Don't need to recalculate the maximum for every kid.
+
+### Solution
+
+```python
+def kidsWithCandies(candies, extraCandies):
+    max_candies = max(candies)  # Find the current maximum
+    return [(c + extraCandies) >= max_candies for c in candies]
+```
+
 ## 1798. Maximum Number of Consecutive Values You Can Make [Medium]
 https://leetcode.com/problems/maximum-number-of-consecutive-values-you-can-make/
 

data/book-sets.json

@@ -176,13 +176,13 @@
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-      3685, 3686, 3689, 3690, 3691, 3693, 3694, 3695, 3698, 3699, 3700, 3702, 3703, 3704, 3705, 3706, 3708, 3709, 3710, 3711, 3713, 3714, 3715, 3716,
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-      3781, 3782, 3783, 3784, 3785, 3786, 3787, 3788, 3789, 3790, 3791, 3792, 3793, 3794, 3795, 3796, 3797, 3798, 3799
+      3561, 3562, 3563, 3564, 3566, 3567, 3568, 3569, 3570, 3572, 3573, 3574, 3575, 3576, 3577, 3578, 3579, 3580, 3582, 3584, 3585, 3586, 3587, 3588,
+      3589, 3590, 3591, 3592, 3593, 3594, 3597, 3598, 3599, 3600, 3601, 3604, 3605, 3609, 3611, 3612, 3613, 3614, 3615, 3617, 3618, 3619, 3620, 3621,
+      3624, 3626, 3627, 3628, 3629, 3630, 3633, 3634, 3635, 3636, 3637, 3638, 3639, 3640, 3642, 3643, 3644, 3645, 3646, 3648, 3649, 3650, 3651, 3652,
+      3653, 3654, 3655, 3657, 3658, 3659, 3660, 3661, 3664, 3665, 3666, 3669, 3670, 3671, 3673, 3674, 3675, 3676, 3677, 3679, 3680, 3681, 3684, 3685,
+      3686, 3689, 3690, 3691, 3693, 3694, 3695, 3698, 3699, 3700, 3702, 3703, 3704, 3705, 3706, 3708, 3709, 3710, 3711, 3713, 3714, 3715, 3716, 3717,
+      3719, 3720, 3721, 3725, 3729, 3730, 3732, 3733, 3734, 3735, 3744, 3746, 3749, 3758, 3763, 3773, 3774, 3775, 3776, 3777, 3778, 3779, 3780, 3781,
+      3782, 3783, 3784, 3785, 3786, 3787, 3788, 3789, 3790, 3791, 3792, 3793, 3794, 3795, 3796, 3797, 3798, 3799
     ],
     "premium": [
       27, 156, 157, 158, 159, 161, 163, 170, 186, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 259, 261, 265, 266, 267, 269,

explanations/3583/en.md

@@ -0,0 +1,56 @@
+## Explanation
+
+### Strategy (The "Why")
+
+**Restate the problem:** We need to count special triplets (i, j, k) where i < j < k, nums[i] == nums[j] * 2, and nums[k] == nums[j] * 2. In other words, for each middle element j, we need to count how many i < j have nums[i] == target and how many k > j have nums[k] == target, where target = nums[j] * 2.
+
+**1.1 Constraints & Complexity:**
+- Input size: `3 <= n <= 10^5`, `0 <= nums[i] <= 10^5`
+- **Time Complexity:** O(n) - single pass through array with hash map operations
+- **Space Complexity:** O(n) for hash maps storing frequencies
+- **Edge Case:** If no triplets exist, return 0
+
+**1.2 High-level approach:**
+We process each position j as the middle element. We maintain two frequency maps: one for elements before j (freq_before) and one for elements after j (freq_after). For each j, we count how many i < j have nums[i] == target and how many k > j have nums[k] == target, then multiply these counts.
+
+![Frequency counting for triplets visualization](https://assets.leetcode.com/static_assets/others/frequency-counting-triplets.png)
+
+**1.3 Brute force vs. optimized strategy:**
+- **Brute Force:** Check all triplets (i, j, k) where i < j < k, which is O(n³)
+- **Optimized Strategy:** For each j, use hash maps to count valid i and k positions in O(1), achieving O(n) time
+- **Emphasize the optimization:** Hash maps allow us to count frequencies before and after each position efficiently without nested loops
+
+**1.4 Decomposition:**
+1. Initialize freq_before (empty) and freq_after (contains all elements initially)
+2. Process each position j from left to right
+3. Remove nums[j] from freq_after (since j is no longer "after")
+4. Calculate target = nums[j] * 2
+5. Count valid i positions (freq_before[target]) and valid k positions (freq_after[target])
+6. Multiply counts and add to result (modulo 10^9 + 7)
+7. Add nums[j] to freq_before for future j positions
+
+### Steps (The "How")
+
+**2.1 Initialization & Example Setup:**
+Let's use the example: `nums = [6, 3, 6]`
+- Initialize: `freq_before = {}`, `freq_after = {6: 2, 3: 1}`, `res = 0`, `MOD = 10^9 + 7`
+
+**2.2 Start Processing:**
+We iterate through each position j from 0 to n-1.
+
+**2.3 Trace Walkthrough:**
+
+| j | nums[j] | Remove from freq_after | target | freq_before[target] | freq_after[target] | Count | res |
+|---|---------|------------------------|--------|---------------------|-------------------|-------|-----|
+| 0 | 6 | freq_after = {6: 1, 3: 1} | 12 | 0 | 0 | 0 * 0 = 0 | 0 |
+| 0 | - | Add to freq_before | - | freq_before = {6: 1} | - | - | 0 |
+| 1 | 3 | freq_after = {6: 1} | 6 | 1 (from freq_before) | 1 (from freq_after) | 1 * 1 = 1 | 1 |
+| 1 | - | Add to freq_before | - | freq_before = {6: 1, 3: 1} | - | - | 1 |
+| 2 | 6 | freq_after = {} | 12 | 0 | 0 | 0 * 0 = 0 | 1 |
+
+**2.4 Increment and Loop:**
+For each j, we update frequency maps and count triplets where j is the middle element.
+
+**2.5 Return Result:**
+After processing all positions, `res = 1`, which is the number of special triplets. The triplet is (0, 1, 2) where nums[0] = 6 = 3 * 2 and nums[2] = 6 = 3 * 2.
+

explanations/3760/en.md

@@ -2,55 +2,50 @@
 
 ### Strategy (The "Why")
 
-**Restate the problem:** We need to convert string `source` to `target` with minimum cost using substring conversions. Operations must be disjoint or identical (can't overlap partially).
+**Restate the problem:** We need to find the maximum number of substrings we can split a string into such that each substring starts with a distinct character. No two substrings can start with the same character.
 
 **1.1 Constraints & Complexity:**
-- Input size: `1 <= source.length == target.length <= 1000`, `1 <= original.length <= 100`
-- **Time Complexity:** O(m³ + n² * m) where m is number of unique strings and n is string length, due to Floyd-Warshall and DP
-- **Space Complexity:** O(m² + n) for distance matrix and DP array
-- **Edge Case:** If source == target, return 0
+- Input size: `1 <= s.length <= 10^5`
+- **Time Complexity:** O(n) - single pass to count distinct characters
+- **Space Complexity:** O(1) - using a set of at most 26 characters (lowercase English letters)
+- **Edge Case:** If all characters are the same (e.g., "aaaa"), we can only have 1 substring
 
 **1.2 High-level approach:**
-We model substring conversions as a graph, use Floyd-Warshall to find shortest paths, then use dynamic programming to find the minimum cost to convert prefixes of the source string.
+The key insight is that each substring must start with a distinct character. Since we can only use each starting character once, the maximum number of substrings equals the number of distinct characters in the string.
 
-![DP with substring matching visualization](https://assets.leetcode.com/static_assets/others/dp-substring-matching.png)
+![Distinct characters visualization](https://assets.leetcode.com/static_assets/others/distinct-characters.png)
 
 **1.3 Brute force vs. optimized strategy:**
-- **Brute Force:** Try all possible sequences of substring conversions, which is exponential.
-- **Optimized Strategy:** Precompute shortest paths between all string pairs using Floyd-Warshall, then use DP where dp[i] = minimum cost to convert first i characters.
+- **Brute Force:** Try all possible ways to split the string, which is exponential
+- **Optimized Strategy:** Simply count distinct characters - each distinct character can start exactly one substring, so the answer is the count of distinct characters
+- **Emphasize the optimization:** The constraint that each substring must start with a distinct character directly limits the answer to the number of distinct characters
 
 **1.4 Decomposition:**
-1. Assign unique IDs to all unique strings in original and changed arrays
-2. Build graph and run Floyd-Warshall to find shortest conversion costs
-3. Use DP: dp[i] = min cost to convert source[0:i] to target[0:i]
-4. For each position, try all possible substring conversions ending there
-5. Return dp[n] or -1 if impossible
+1. Count the number of distinct characters in the string
+2. Since each substring must start with a distinct character, and we can only use each character once as a start
+3. The maximum number of substrings equals the number of distinct characters
+4. Return the count
 
 ### Steps (The "How")
 
 **2.1 Initialization & Example Setup:**
-Let's use the example: `source = "abcd"`, `target = "acbe"`, `original = ["a","b","c","c","e","d"]`, `changed = ["b","c","b","e","b","e"]`, `cost = [2,5,5,1,2,20]`
-- Map strings to IDs: a→0, b→1, c→2, e→3, d→4
-- Build graph and run Floyd-Warshall
+Let's use the example: `s = "abab"`
+- Distinct characters: 'a' and 'b' (2 distinct characters)
+- We can split into: "a" and "bab" (starts with 'a' and 'b')
 
-**2.2 Start Processing:**
-We initialize dp[0] = 0, then process each position.
+**2.2 Start Checking:**
+We count distinct characters in the string.
 
 **2.3 Trace Walkthrough:**
-Processing `source = "abcd"` to `target = "acbe"`:
 
-| i | source[0:i] | target[0:i] | Options | dp[i] |
-|---|-------------|-------------|---------|-------|
-| 0 | "" | "" | Base case | 0 |
-| 1 | "a" | "a" | No change (dp[0] + 0) | 0 |
-| 2 | "ab" | "ac" | Try "b"→"c": dp[1] + cost(b→c) = 0 + 5 = 5 | 5 |
-| 3 | "abc" | "acb" | Try "c"→"b": dp[2] + cost(c→b) = 5 + 5 = 10<br>Or "bc"→"cb": need to check if exists | 10 |
-| 4 | "abcd" | "acbe" | Try "d"→"e": dp[3] + cost(d→e) = 10 + 20 = 30 | 30 |
-
-Actually, we need to check all substring conversions. For position 2, we can convert "b" to "c" at cost 5. For position 3, we convert "c" to "b" at cost 5 (or find better path). For position 4, we convert "d" to "e" at cost 20. Total: 5 + 5 + 20 = 30, but the example says 28, so there must be a better path.
+| String | Distinct Characters | Count | Maximum Substrings |
+|--------|-------------------|-------|-------------------|
+| "abab" | {'a', 'b'} | 2 | 2 |
+| "abcd" | {'a', 'b', 'c', 'd'} | 4 | 4 |
+| "aaaa" | {'a'} | 1 | 1 |
 
 **2.4 Increment and Loop:**
-For each position i, we try all possible substring conversions ending at i and take the minimum cost.
+We iterate through the string once to collect all distinct characters in a set.
 
 **2.5 Return Result:**
-After processing, `dp[4] = 28` (using optimal conversions), which is the minimum cost to convert "abcd" to "acbe".
+For "abab", we have 2 distinct characters, so the maximum number of substrings is 2. We can split as "a" + "bab" where "a" starts with 'a' and "bab" starts with 'b'.