[Python/Pandas] 리트코드 1084. Sales Analysis III

문제

Table: Product
+--------------+---------+
| Column Name  | Type    |
+--------------+---------+
| product_id   | int     |
| product_name | varchar |
| unit_price   | int     |
+--------------+---------+

product_id is the primary key (column with unique values) of this table.
Each row of this table indicates the name and the price of each product.

Table: Sales
+-------------+---------+
| Column Name | Type    |
+-------------+---------+
| seller_id   | int     |
| product_id  | int     |
| buyer_id    | int     |
| sale_date   | date    |
| quantity    | int     |
| price       | int     |
+-------------+---------+

This table can have duplicate rows.
product_id is a foreign key (reference column) to the Product table.
Each row of this table contains some information about one sale.
 
Write a solution to report the products that were only sold in the first quarter of 2019. That is, between 2019-01-01 and 2019-03-31 inclusive.
Return the result table in any order.

 

https://leetcode.com/problems/sales-analysis-iii/description/?lang=pythondata

예시

Input: 
Product table:
+------------+--------------+------------+
| product_id | product_name | unit_price |
+------------+--------------+------------+
| 1          | S8           | 1000       |
| 2          | G4           | 800        |
| 3          | iPhone       | 1400       |
+------------+--------------+------------+
Sales table:
+-----------+------------+----------+------------+----------+-------+
| seller_id | product_id | buyer_id | sale_date  | quantity | price |
+-----------+------------+----------+------------+----------+-------+
| 1         | 1          | 1        | 2019-01-21 | 2        | 2000  |
| 1         | 2          | 2        | 2019-02-17 | 1        | 800   |
| 2         | 2          | 3        | 2019-06-02 | 1        | 800   |
| 3         | 3          | 4        | 2019-05-13 | 2        | 2800  |
+-----------+------------+----------+------------+----------+-------+
Output: 
+-------------+--------------+
| product_id  | product_name |
+-------------+--------------+
| 1           | S8           |
+-------------+--------------+

Explanation: 
The product with id 1 was only sold in the spring of 2019.
The product with id 2 was sold in the spring of 2019 but was also sold after the spring of 2019.
The product with id 3 was sold after spring 2019.
We return only product 1 as it is the product that was only sold in the spring of 2019.

문제 풀이

import pandas as pd

def sales_analysis(product: pd.DataFrame, sales: pd.DataFrame) -> pd.DataFrame:
	# 최소 판매일과 최대 판매일 계산하여 필터링
    filtered_sales = sales.groupby('product_id')['sale_date'].agg(['min', 'max']).reset_index()
    filtered_sales = filtered_sales[(filtered_sales['min'] >= '2019-01-01') & (filtered_sales['max'] <= '2019-03-31')]
    
    # 필터링 된 결과와 product df를 merge하여 필요한 열만 반환
    result = pd.merge(filtered_sales, product, on='product_id')[['product_id', 'product_name']]
    return result

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