Welcome to Subscribe On Youtube
178. Rank Scores
Description
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 | +-------+------+
Solutions
Solution 1: Direct Implementation
Use the DENSE_RANK() function, the syntax is as follows:
DENSE_RANK() OVER (
PARTITION BY <expression>[{,<expression>...}]
ORDER BY <expression> [ASC|DESC], [{,<expression>...}]
)
In this syntax:
- First, the
PARTITION BYclause divides the result set generated by theFROMclause into partitions. TheDENSE_RANK()function is applied to each partition. - Second, the
ORDER BYclause specifies the order of rows in each partition that theDENSE_RANK()function operates on.
Unlike the RANK() function, the DENSE_RANK() function always returns consecutive ranking values.
Solution 2
MySQL 8 has only provided ROW_NUMBER(), RANK(), DENSE_RANK() and other [window functions] (https://dev.mysql.com/doc/refman/8.0/en/window-function-descriptions.html),在之前的版本,可以使用变量实现类似的功能。
-
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 -
# Write your MySQL query statement below SELECT score, DENSE_RANK() OVER (ORDER BY score DESC) AS 'rank' FROM Scores; -- Solution 2 SELECT Score, CONVERT(rk, SIGNED) `Rank` FROM ( SELECT Score, IF(@latest = Score, @rank, @rank := @rank + 1) rk, @latest := Score FROM Scores, ( SELECT @rank := 0, @latest := NULL ) tmp ORDER BY Score DESC ) s;