README_EN.md

comments	difficulty	edit_url	tags
true	Easy	https://github.com/doocs/leetcode/edit/main/solution/1700-1799/1757.Recyclable%20and%20Low%20Fat%20Products/README_EN.md	Database

1757. Recyclable and Low Fat Products

中文文档

Description

Table: Products

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

 

Write a solution to 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.

Solutions

Solution 1: Conditional Filtering

We can directly filter the product IDs where low_fats is Y and recyclable is Y.

Python3

import pandas as pd


def find_products(products: pd.DataFrame) -> pd.DataFrame:
    rs = products[(products["low_fats"] == "Y") & (products["recyclable"] == "Y")]
    rs = rs[["product_id"]]
    return rs

MySQL

SELECT
    product_id
FROM Products
WHERE low_fats = 'Y' AND recyclable = 'Y';