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feat(content): add new problem pages, reorganize docs into (problems) subfolders, and update meta display to page
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---
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title: '347. Top K Frequent Elements'
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description: Given an integer array nums and an integer k, return the k most frequent elements. You may return the answer in any order
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icon: dot
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topics:
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- { name: "Array", slug: "array" }
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- { name: "Hash Table", slug: "hash-table" }
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- { name: "Divide and Conquer", slug: "divide-and-conquer" }
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- { name: "Sorting", slug: "sorting" }
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- { name: "Heap (Priority Queue)", slug: "heap-priority-queue" }
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- { name: "Bucket Sort", slug: "bucket-sort" }
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- { name: "Counting", slug: "counting" }
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- { name: "Quickselect", slug: "quickselect" }
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video: "YPTqKIgVk-k"
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issue: "https://github.com/prdlk/leetcode/issues/31"
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sidebar:
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label: 'Top K Frequent Elements'
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badge: 'Medium'
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---
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::::warning
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Your algorithm's time complexity must be better than O(n log n), where n is the array's size.
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::::
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### Example 1:
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- Input: `nums = [1,1,1,2,2,3], k = 2`
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- Output: `[1,2]`
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### Example 2:
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- Input: `nums = [1], k = 1`
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- Output: `[1]`
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### Example 3:
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- Input: `nums = [1,2,1,2,1,2,3,1,3,2], k = 2`
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- Output: `[1,2]`
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### Constraints:
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- `1 <= nums.length <= 10^5`
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- `-10^4 <= nums[i] <= 10^4`
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- `k` is in the range `[1, the number of unique elements in the array]`.
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- It is guaranteed that the answer is unique.
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## Approach
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```mermaid
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flowchart TD
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S(["topKFrequent(nums, k)"]) --> F["freq: count every value in nums"]
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F --> K["keys of freq, cast to Number"]
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K --> O["sort by freq[b] - freq[a] — most frequent first"]
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O --> R(["return slice(0, k)"])
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```
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## Solution
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```js
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/**
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* @param {number[]} nums
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* @param {number} k
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* @return {number[]}
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*/
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var topKFrequent = function (nums, k) {
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const freq = {};
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for (let n of nums) freq[n] = (freq[n] || 0) + 1;
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return Object.keys(freq)
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.map(Number)
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.sort((a, b) => freq[b] - freq[a])
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.slice(0, k);
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};
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```
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