How do you solve Sort the Students by Their Kth Score on LeetCode?

Sort the Students by Their Kth Score (LeetCode #2545) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(m log m) time complexity and O(1) space complexity. Key insight: Sorting is a common operation in many problems; understanding how to leverage built-in functions can save time.

What is the time complexity of Sort the Students by Their Kth Score?

The optimal solution for Sort the Students by Their Kth Score runs in O(m log m) time and uses O(1) space. The complexity remains O(m log m) due to sorting, but we do not create an additional copy of the matrix, making the space complexity O(1).

What is the brute force solution for Sort the Students by Their Kth Score?

The brute force approach for Sort the Students by Their Kth Score is Brute Force, with O(m log m) time complexity and O(m) space complexity. The brute-force approach involves sorting the students based on their scores in the k-th exam using a simple sorting algorithm. This is straightforward but inefficient for larger datasets. The optimal Optimal Solution approach improves this to O(m log m).

What algorithm or data structure is used to solve Sort the Students by Their Kth Score?

Sort the Students by Their Kth Score uses the following concepts: Array, Sorting, Matrix. The recommended patterns to study are: Sorting, Array.

What are the interview tips for Sort the Students by Their Kth Score?

Always clarify the problem requirements and constraints before jumping into coding. Think aloud while coding to demonstrate your thought process to the interviewer. Test your solution with edge cases, such as the smallest or largest possible input sizes.

What are common mistakes when solving Sort the Students by Their Kth Score?

Not understanding how to sort based on a specific column. Confusing the indices when accessing elements in a 2D array.

#2545

Sort the Students by Their Kth Score

Medium

ArraySortingMatrixSortingArray

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

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

💡

Intuition

Time O(m log m)Space O(1)

The optimal approach leverages Python's built-in sorting capabilities to sort the students directly based on the k-th score, which is efficient and concise.

⚙️

Algorithm

3 steps

1Step 1: Use the built-in sort function to sort the matrix based on the k-th column.
2Step 2: Specify the sorting order as descending.
3Step 3: Return the sorted matrix.

solution.py4 lines

1score = [[10,6,9,1],[7,5,11,2],[4,8,3,15]]
2k = 2
3sorted_score = sorted(score, key=lambda x: x[k], reverse=True)
4print(sorted_score)

ℹ

Complexity note: The complexity remains O(m log m) due to sorting, but we do not create an additional copy of the matrix, making the space complexity O(1).

1Sorting is a common operation in many problems; understanding how to leverage built-in functions can save time.
2Distinct integers in the matrix simplify the sorting process as there are no ties.

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