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1294. 不同国家的天气类型

表：Countries

+---------------+---------+
| Column Name   | Type    |
+---------------+---------+
| country_id    | int     |
| country_name  | varchar |
+---------------+---------+
country_id 是这张表的主键(具有唯一值的列)。
该表的每行有 country_id 和 country_name 两列。

 

表：Weather

+---------------+---------+
| Column Name   | Type    |
+---------------+---------+
| country_id    | int     |
| weather_state | varchar |
| day           | date    |
+---------------+---------+
(country_id, day) 是该表的复合主键(具有唯一值的列)。
该表的每一行记录了某个国家某一天的天气情况。

 

编写解决方案找到表中每个国家在 2019 年 11 月的天气类型。

天气类型的定义如下：

以 任意顺序 返回你的查询结果。

返回结果格式如下所示：

 

示例 1：

输入：
Countries table:
+------------+--------------+
| country_id | country_name |
+------------+--------------+
| 2          | USA          |
| 3          | Australia    |
| 7          | Peru         |
| 5          | China        |
| 8          | Morocco      |
| 9          | Spain        |
+------------+--------------+
Weather table:
+------------+---------------+------------+
| country_id | weather_state | day        |
+------------+---------------+------------+
| 2          | 15            | 2019-11-01 |
| 2          | 12            | 2019-10-28 |
| 2          | 12            | 2019-10-27 |
| 3          | -2            | 2019-11-10 |
| 3          | 0             | 2019-11-11 |
| 3          | 3             | 2019-11-12 |
| 5          | 16            | 2019-11-07 |
| 5          | 18            | 2019-11-09 |
| 5          | 21            | 2019-11-23 |
| 7          | 25            | 2019-11-28 |
| 7          | 22            | 2019-12-01 |
| 7          | 20            | 2019-12-02 |
| 8          | 25            | 2019-11-05 |
| 8          | 27            | 2019-11-15 |
| 8          | 31            | 2019-11-25 |
| 9          | 7             | 2019-10-23 |
| 9          | 3             | 2019-12-23 |
+------------+---------------+------------+
输出：
+--------------+--------------+
| country_name | weather_type |
+--------------+--------------+
| USA          | Cold         |
| Austraila    | Cold         |
| Peru         | Hot          |
| China        | Warm         |
| Morocco      | Hot          |
+--------------+--------------+
解释：
USA 11 月的平均 weather_state 为 (15) / 1 = 15 所以天气类型为 Cold。
Australia 11 月的平均 weather_state 为 (-2 + 0 + 3) / 3 = 0.333 所以天气类型为 Cold。
Peru 11 月的平均 weather_state 为 (25) / 1 = 25 所以天气类型为 Hot。
China 11 月的平均 weather_state 为 (16 + 18 + 21) / 3 = 18.333 所以天气类型为 Warm。
Morocco 11 月的平均 weather_state 为 (25 + 27 + 31) / 3 = 27.667 所以天气类型为 Hot。
我们并不知道 Spain 在 11 月的 weather_state 情况所以无需将他包含在结果中。

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上次编辑到这里，代码来自缓存 点击恢复默认模板
# Write your MySQL query statement below

mysql 解法, 执行用时: 485 ms, 内存消耗: 0 B, 提交时间: 2023-10-15 16:36:06 

# Write your MySQL query statement below
SELECT country_name AS 'country_name',
    CASE 
        WHEN AVG(w1.weather_state) <= 15 THEN 'Cold' 
        WHEN AVG(w1.weather_state) >= 25 THEN 'Hot'
        ELSE 'Warm'
    END
        AS 'weather_type'
FROM 
    Countries AS c1
    INNER JOIN Weather AS w1
    ON c1.country_id = w1.country_id
WHERE DATE_FORMAT(w1.day, '%Y-%m') = '2019-11'
GROUP BY c1.country_id
;

mysql 解法, 执行用时: 380 ms, 内存消耗: 0 B, 提交时间: 2023-10-15 16:35:55 

# Write your MySQL query statement below
SELECT country_name AS 'country_name',
    CASE 
        WHEN AVG(w1.weather_state) <= 15 THEN 'Cold' 
        WHEN AVG(w1.weather_state) >= 25 THEN 'Hot'
        ELSE 'Warm'
    END
        AS 'weather_type'
FROM 
    Countries AS c1
    INNER JOIN Weather AS w1
    ON c1.country_id = w1.country_id
WHERE YEAR(w1.day) = 2019 AND MONTH(w1.day) = 11
GROUP BY c1.country_id
;

mysql 解法, 执行用时: 490 ms, 内存消耗: 0 B, 提交时间: 2023-10-15 16:35:41 

# Write your MySQL query statement below
SELECT country_name AS 'country_name',
    CASE 
        WHEN AVG(w1.weather_state) <= 15 THEN 'Cold' 
        WHEN AVG(w1.weather_state) >= 25 THEN 'Hot'
        ELSE 'Warm'
    END
        AS 'weather_type'
FROM 
    Countries AS c1
    INNER JOIN Weather AS w1
    ON c1.country_id = w1.country_id
WHERE w1.day BETWEEN '2019-11-01' AND '2019-11-30'
GROUP BY c1.country_id
;

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