620. Not Boring Movies

Description

Pandas Schema

data = [[1, 'War', 'great 3D', 8.9], [2, 'Science', 'fiction', 8.5], [3, 'irish', 'boring', 6.2], [4, 'Ice song', 'Fantacy', 8.6], [5, 'House card', 'Interesting', 9.1]]
cinema = pd.DataFrame(data, columns=['id', 'movie', 'description', 'rating']).astype({'id':'Int64', 'movie':'object', 'description':'object', 'rating':'Float64'})

Table: Cinema

+----------------+----------+
| Column Name    | Type     |
+----------------+----------+
| id             | int      |
| movie          | varchar  |
| description    | varchar  |
| rating         | float    |
+----------------+----------+
id is the primary key (column with unique values) for this table.
Each row contains information about the name of a movie, its genre, and its rating.
rating is a 2 decimal places float in the range [0, 10]

Write a solution to report the movies with an odd-numbered ID and a description that is not "boring".

Return the result table ordered by rating in descending order.

The result format is in the following example.

Example 1:

• Input:

    Cinema table:
    +----+------------+-------------+--------+
    | id | movie      | description | rating |
    +----+------------+-------------+--------+
    | 1  | War        | great 3D    | 8.9    |
    | 2  | Science    | fiction     | 8.5    |
    | 3  | irish      | boring      | 6.2    |
    | 4  | Ice song   | Fantacy     | 8.6    |
    | 5  | House card | Interesting | 9.1    |
    +----+------------+-------------+--------+
    

• Output:

    +----+------------+-------------+--------+
    | id | movie      | description | rating |
    +----+------------+-------------+--------+
    | 5  | House card | Interesting | 9.1    |
    | 1  | War        | great 3D    | 8.9    |
    +----+------------+-------------+--------+
    

• Explanation:
  We have three movies with odd-numbered IDs: 1, 3, and 5.
  The movie with ID = 3 is boring so we do not include it in the answer.

Submitted Code

import pandas as pd

def not_boring_movies(cinema: pd.DataFrame) -> pd.DataFrame:
    filtered_movies = cinema.loc[(cinema.id % 2 == 1) & (cinema.description != 'boring')]
    return filtered_movies.sort_values(by='rating', ascending=False)

Runtime: 238 ms | Beats 97.74%
Memory: 67.16 MB | Beats 64.28%

sort_values()에서 ascending을 False로 설정하면 내림차순 정렬을 할 수 있다.

Other Solutions

1st

def not_boring_movies(cinema: pd.DataFrame) -> pd.DataFrame:
    return cinema[::2][cinema.description != 'boring'].sort_values('rating', ascending=False)

id가 1부터 시작해서 중간에 빠진 숫자없이 정렬되어있다고 보장할 수 있다면 이 방법도 사용할 수 있다.

2nd

SELECT *                        -- 3. 필터링된 행에서 모든 열 선택
FROM Cinema                     -- 1. 테이블 불러오기
WHERE MOD(id, 2) = 1            -- 2. 조건에 맞는 행만 필터링
  AND description <> 'boring'   -- (<> 는 표준 SQL에서 '같지 않다'는 뜻)
ORDER BY rating DESC;           -- 4. rating 열 기준으로 내림차순