How do you solve Top K Frequent Elements on LeetCode?

Top K Frequent Elements (LeetCode #347) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(n) time complexity and O(n) space complexity. Key insight: Using a frequency map helps in counting occurrences efficiently.

What is the brute force solution for Top K Frequent Elements?

The brute force approach for Top K Frequent Elements is Brute Force, with O(n log n) time complexity and O(n) space complexity. The brute force approach involves counting the frequency of each element and then sorting these frequencies to find the top k elements. This is straightforward but inefficient for larger inputs. The optimal Optimal Solution approach improves this to O(n).

What are the interview tips for Top K Frequent Elements?

Always clarify the constraints and edge cases with the interviewer. Discuss your thought process and the trade-offs of different approaches. Practice explaining your code as you write it, as this helps in interviews.

What are common mistakes when solving Top K Frequent Elements?

Not considering edge cases like all elements being the same. Confusing frequency counts with the values themselves.

#347

Top K Frequent Elements

Medium

ArrayHash TableDivide and ConquerSortingHeap (Priority Queue)Bucket SortCountingQuickselectHash MapArray

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Approaches

Brute ForceOptimal

Complexity Comparison

	Brute Force	Optimal Solution★
Time	O(n log n)	O(n)
Space	O(n)	O(n)

💡

Intuition

Time O(n)Space O(n)

Using a bucket sort approach allows us to efficiently group elements by their frequency, enabling us to directly access the top k frequent elements without sorting all elements.

⚙️

Algorithm

3 steps

1Step 1: Create a frequency map to count occurrences of each element in nums.
2Step 2: Create an array of buckets where the index represents frequency and each bucket contains the elements with that frequency.
3Step 3: Iterate through the buckets in reverse order to collect the top k elements.

solution.py14 lines

1# Full working Python code
2from collections import Counter
3
4def topKFrequent(nums, k):
5    count = Counter(nums)
6    buckets = [[] for _ in range(len(nums) + 1)]
7    for num, freq in count.items():
8        buckets[freq].append(num)
9    result = []
10    for i in range(len(buckets) - 1, 0, -1):
11        for num in buckets[i]:
12            result.append(num)
13            if len(result) == k:
14                return result

ℹ

Complexity note: The time complexity is O(n) since we traverse the list a constant number of times, while the space complexity is O(n) for storing the frequency map and buckets.

1Using a frequency map helps in counting occurrences efficiently.
2Bucket sort allows direct access to the most frequent elements without full sorting.

Solutions and explanations are original Tejav content. Problem titles © LeetCode — use the LeetCode button above for the full problem statement.