LeetCode #178 — MEDIUM

Rank Scores

Move from brute-force thinking to an efficient approach using core interview patterns strategy.

Solve on LeetCode
The Problem

Problem Statement

Table: Scores

+-------------+---------+
| Column Name | Type    |
+-------------+---------+
| id          | int     |
| score       | decimal |
+-------------+---------+
id is the primary key (column with unique values) for this table.
Each row of this table contains the score of a game. Score is a floating point value with two decimal places.

Write a solution to find the rank of the scores. The ranking should be calculated according to the following rules:

  • The scores should be ranked from the highest to the lowest.
  • If there is a tie between two scores, both should have the same ranking.
  • After a tie, the next ranking number should be the next consecutive integer value. In other words, there should be no holes between ranks.

Return the result table ordered by score in descending order.

The result format is in the following example.

Example 1:

Input: 
Scores table:
+----+-------+
| id | score |
+----+-------+
| 1  | 3.50  |
| 2  | 3.65  |
| 3  | 4.00  |
| 4  | 3.85  |
| 5  | 4.00  |
| 6  | 3.65  |
+----+-------+
Output: 
+-------+------+
| score | rank |
+-------+------+
| 4.00  | 1    |
| 4.00  | 1    |
| 3.85  | 2    |
| 3.65  | 3    |
| 3.65  | 3    |
| 3.50  | 4    |
+-------+------+

Roadmap

  1. Brute Force Baseline
  2. Core Insight
  3. Algorithm Walkthrough
  4. Edge Cases
  5. Full Annotated Code
  6. Interactive Study Demo
  7. Complexity Analysis
Step 01

Brute Force Baseline

Problem summary: Table: Scores +-------------+---------+ | Column Name | Type | +-------------+---------+ | id | int | | score | decimal | +-------------+---------+ id is the primary key (column with unique values) for this table. Each row of this table contains the score of a game. Score is a floating point value with two decimal places. Write a solution to find the rank of the scores. The ranking should be calculated according to the following rules: The scores should be ranked from the highest to the lowest. If there is a tie between two scores, both should have the same ranking. After a tie, the next ranking number should be the next consecutive integer value. In other words, there should be no holes between ranks. Return the result table ordered by score in descending order. The result format is in the following example.

Baseline thinking

Start with the most direct exhaustive search. That gives a correctness anchor before optimizing.

Pattern signal: General problem-solving

Example 1

{"headers": {"Scores": ["id", "score"]}, "rows": {"Scores": [[1, 3.50], [2, 3.65], [3, 4.00], [4, 3.85], [5, 4.00], [6, 3.65]]}}
Step 02

Core Insight

What unlocks the optimal approach

  • No official hints in dataset. Start from constraints and look for a monotonic or reusable state.
Interview move: turn each hint into an invariant you can check after every iteration/recursion step.
Step 03

Algorithm Walkthrough

Iteration Checklist

  1. Define state (indices, window, stack, map, DP cell, or recursion frame).
  2. Apply one transition step and update the invariant.
  3. Record answer candidate when condition is met.
  4. Continue until all input is consumed.
Use the first example testcase as your mental trace to verify each transition.
Step 04

Edge Cases

Minimum Input
Single element / shortest valid input
Validate boundary behavior before entering the main loop or recursion.
Duplicates & Repeats
Repeated values / repeated states
Decide whether duplicates should be merged, skipped, or counted explicitly.
Extreme Constraints
Upper-end input sizes
Re-check complexity target against constraints to avoid time-limit issues.
Invalid / Corner Shape
Empty collections, zeros, or disconnected structures
Handle special-case structure before the core algorithm path.
Step 05

Full Annotated Code

Source-backed implementations are provided below for direct study and interview prep.

// Accepted solution for LeetCode #178: Rank Scores
// Auto-generated Java example from py.
class Solution {
    public void exampleSolution() {
    }
}
// Reference (py):
// # Accepted solution for LeetCode #178: Rank Scores
// import pandas as pd
// 
// 
// def order_scores(scores: pd.DataFrame) -> pd.DataFrame:
//     # Use the rank method to assign ranks to the scores in descending order with no gaps
//     scores["rank"] = scores["score"].rank(method="dense", ascending=False)
// 
//     # Drop id column & Sort the DataFrame by score in descending order
//     result_df = scores.drop("id", axis=1).sort_values(by="score", ascending=False)
// 
//     return result_df
Step 06

Interactive Study Demo

Use this to step through a reusable interview workflow for this problem.

Press Step or Run All to begin.
Step 07

Complexity Analysis

Time
O(n)
Space
O(1)

Approach Breakdown

BRUTE FORCE
O(n²) time
O(1) space

Two nested loops check every pair or subarray. The outer loop fixes a starting point, the inner loop extends or searches. For n elements this gives up to n²/2 operations. No extra space, but the quadratic time is prohibitive for large inputs.

OPTIMIZED
O(n) time
O(1) space

Most array problems have an O(n²) brute force (nested loops) and an O(n) optimal (single pass with clever state tracking). The key is identifying what information to maintain as you scan: a running max, a prefix sum, a hash map of seen values, or two pointers.

Shortcut: If you are using nested loops on an array, there is almost always an O(n) solution. Look for the right auxiliary state.
Coach Notes

Common Mistakes

Review these before coding to avoid predictable interview regressions.

Off-by-one on range boundaries

Wrong move: Loop endpoints miss first/last candidate.

Usually fails on: Fails on minimal arrays and exact-boundary answers.

Fix: Re-derive loops from inclusive/exclusive ranges before coding.