Day2. Data Filtering - Recyclable and Low Fat Products

Problem

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.

Solution

# my solution
import pandas as pd

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

# check result

data = [['0', 'Y', 'N'], ['1', 'Y', 'Y'], ['2', 'N', 'Y'], ['3', 'Y', 'Y'], ['4', 'N', 'N']]
Products = pd.DataFrame(data, columns=['product_id', 'low_fats', 'recyclable']).astype({'product_id':'int64', 'low_fats':'category', 'recyclable':'category'})

find_products(Products)

# the others

# 1.
def find_products(products: pd.DataFrame) -> pd.DataFrame:
    result_df = products[(products['low_fats'] == 'Y') & (products['recyclable'] == 'Y')]
    return result_df[['product_id']]
    
# 2.
def find_products(products: pd.DataFrame) -> pd.DataFrame:
    return products.query('low_fats == "Y" & recyclable == "Y"')[["product_id"]]

# 3.
def find_products(products: pd.DataFrame) -> pd.DataFrame:
    return products[
        (products['low_fats'] == 'Y') & \
        (products['recyclable'] == 'Y')
    ][['product_id']]

reference

leetcode - 30 Days of Pandas / Recyclable and Fat Products