1294. Weather Type in Each Country 🔒

Description

Table: Countries

+---------------+---------+
| Column Name   | Type    |
+---------------+---------+
| country_id    | int     |
| country_name  | varchar |
+---------------+---------+
country_id is the primary key (column with unique values) for this table.
Each row of this table contains the ID and the name of one country.

 

Table: Weather

+---------------+------+
| Column Name   | Type |
+---------------+------+
| country_id    | int  |
| weather_state | int  |
| day           | date |
+---------------+------+
(country_id, day) is the primary key (combination of columns with unique values) for this table.
Each row of this table indicates the weather state in a country for one day.

 

Write a solution to find the type of weather in each country for November 2019.

The type of weather is:

• Cold if the average weather_state is less than or equal 15,
• Hot if the average weather_state is greater than or equal to 25, and
• Warm otherwise.

Return the result table in any order.

The result format is in the following example.

 

Example 1:

Input: 
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 |
+------------+---------------+------------+
Output: 
+--------------+--------------+
| country_name | weather_type |
+--------------+--------------+
| USA          | Cold         |
| Australia    | Cold         |
| Peru         | Hot          |
| Morocco      | Hot          |
| China        | Warm         |
+--------------+--------------+
Explanation: 
Average weather_state in USA in November is (15) / 1 = 15 so weather type is Cold.
Average weather_state in Austraila in November is (-2 + 0 + 3) / 3 = 0.333 so weather type is Cold.
Average weather_state in Peru in November is (25) / 1 = 25 so the weather type is Hot.
Average weather_state in China in November is (16 + 18 + 21) / 3 = 18.333 so weather type is Warm.
Average weather_state in Morocco in November is (25 + 27 + 31) / 3 = 27.667 so weather type is Hot.
We know nothing about the average weather_state in Spain in November so we do not include it in the result table. 

Solutions

Solution 1

MySQL

# Write your MySQL query statement below
SELECT
    country_name,
    CASE
        WHEN AVG(weather_state) <= 15 THEN 'Cold'
        WHEN AVG(weather_state) >= 25 THEN 'Hot'
        ELSE 'Warm'
    END AS weather_type
FROM
    Weather AS w
    JOIN Countries USING (country_id)
WHERE DATE_FORMAT(day, '%Y-%m') = '2019-11'
GROUP BY 1;

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