这个系列难度比较低，一题写一篇其实没必要，就全部放到一篇吧

---

595. Big Countries

原题链接：595. Big Countries

Table: World

+-------------+---------+
| Column Name | Type    |
+-------------+---------+
| name        | varchar |
| continent   | varchar |
| area        | int     |
| population  | int     |
| gdp         | bigint  |
+-------------+---------+In SQL, name is the primary key column for this table.
Each row of this table gives information about the name of a country, the continent to which it belongs, its area, the population, and its GDP value.

A country is big if:

• it has an area of at least three million (i.e., 3000000 km2), or
• it has a population of at least twenty-five million (i.e., 25000000).
  Find the name, population, and area of the big countries.

Return the result table in any order.

The result format is in the following example.

Example 1:

Input:

World table:
+-------------+-----------+---------+------------+--------------+
| name        | continent | area    | population | gdp          |
+-------------+-----------+---------+------------+--------------+
| Afghanistan | Asia      | 652230  | 25500100   | 20343000000  |
| Albania     | Europe    | 28748   | 2831741    | 12960000000  |
| Algeria     | Africa    | 2381741 | 37100000   | 188681000000 |
| Andorra     | Europe    | 468     | 78115      | 3712000000   |
| Angola      | Africa    | 1246700 | 20609294   | 100990000000 |
+-------------+-----------+---------+------------+--------------+

Output:

+-------------+------------+---------+
| name        | population | area    |
+-------------+------------+---------+
| Afghanistan | 25500100   | 652230  |
| Algeria     | 37100000   | 2381741 |
+-------------+------------+---------+

思路：

两个条件进行筛选，没啥好说的

pandas写法：

import pandas as pddef big_countries(world: pd.DataFrame) -> pd.DataFrame:res = world[(world['area'] >= 3000000) | (world['population'] >= 25000000)]return res[['name', 'population', 'area']]

mysql写法：

select name, population, area 
from World
where population>=25000000 or area>=3000000

---

1757. Recyclable and Low Fat Products

Table: Products

+-------------+---------+
| Column Name | Type    |
+-------------+---------+
| product_id  | int     |
| low_fats    | enum    |
| recyclable  | enum    |
+-------------+---------+
In SQL, product_id is the primary key for this table.
low_fats is an ENUM of type ('Y', 'N') where 'Y' means this product is low fat and 'N' means it is not.
recyclable is an ENUM of types ('Y', 'N') where 'Y' means this product is recyclable and 'N' means it is not.

Find the ids of products that are both low fat and recyclable.

Return the result table in any order.

The result format is in the following example.

Example 1:

Input:

Products table:
+-------------+----------+------------+
| product_id  | low_fats | recyclable |
+-------------+----------+------------+
| 0           | Y        | N          |
| 1           | Y        | Y          |
| 2           | N        | Y          |
| 3           | Y        | Y          |
| 4           | N        | N          |
+-------------+----------+------------+

Output:

+-------------+
| product_id  |
+-------------+
| 1           |
| 3           |
+-------------+

Explanation: Only products 1 and 3 are both low fat and recyclable.

思路：

两个条件进行筛选，和上面那个就是and和or的区别，没啥好说的

pandas写法：

import pandas as pddef find_products(products: pd.DataFrame) -> pd.DataFrame:res = products[(products['low_fats'] == 'Y') & (products['recyclable'] == 'Y')]return res[['product_id']]

mysql写法：

select product_id 
from Products
where low_fats = 'Y' and recyclable = 'Y'

---