How do you solve Rank Teams by Votes on LeetCode?

Rank Teams by Votes (LeetCode #1366) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(n log n) time complexity and O(n) space complexity. Key insight: Understanding how to handle ties is crucial for this problem.

What is the brute force solution for Rank Teams by Votes?

The brute force approach for Rank Teams by Votes is Brute Force, with O(n²) time complexity and O(1) space complexity. The brute force approach involves counting the votes for each team in each position and then sorting the teams based on these counts. This method is straightforward but inefficient for larger inputs. The optimal Optimal Solution approach improves this to O(n log n).

What algorithm or data structure is used to solve Rank Teams by Votes?

Rank Teams by Votes uses the following concepts: Array, Hash Table, String, Sorting, Counting. The recommended patterns to study are: Hash Map, Array.

What are the interview tips for Rank Teams by Votes?

Clarify the ranking rules with the interviewer before diving into coding. Think about edge cases, such as all teams receiving the same votes. Write clean, modular code and explain your thought process as you go.

What are common mistakes when solving Rank Teams by Votes?

Not considering all positions when resolving ties. Overcomplicating the sorting logic instead of using a clear comparator.

#1366

Rank Teams by Votes

Medium

ArrayHash TableStringSortingCountingHash MapArray

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

	Brute Force	Optimal Solution★
Time	O(n²)	O(n log n)
Space	O(1)	O(n)

💡

Intuition

Time O(n log n)Space O(n)

The optimal solution efficiently counts votes and sorts teams using a custom comparator. This method handles ties effectively and is more scalable for larger inputs.

⚙️

Algorithm

3 steps

1Step 1: Use a dictionary to count votes for each team at each position.
2Step 2: Create a list of teams and sort it using a custom comparator based on the vote counts and team names.
3Step 3: Return the sorted list as a string.

solution.py8 lines

1def rankTeams(votes):
2    from collections import defaultdict
3    rank = defaultdict(lambda: [0] * len(votes[0]))
4    for vote in votes:
5        for i, team in enumerate(vote):
6            rank[team][i] += 1
7    sorted_teams = sorted(rank.keys(), key=lambda x: (rank[x], x), reverse=True)
8    return ''.join(sorted_teams)

ℹ

Complexity note: The time complexity is O(n log n) due to the sorting step of the teams based on their ranks. The space complexity is O(n) because we store the vote counts for each team.

1Understanding how to handle ties is crucial for this problem.
2Using a dictionary to count votes allows for efficient access and updates.

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