[Python/Pandas] 리트코드 1068. Product Sales Analysis I

문제

Table: Sales
+-------------+-------+
| Column Name | Type  |
+-------------+-------+
| sale_id     | int   |
| product_id  | int   |
| year        | int   |
| quantity    | int   |
| price       | int   |
+-------------+-------+

(sale_id, year) is the primary key (combination of columns with unique values) of this table.
product_id is a foreign key (reference column) to Product table.
Each row of this table shows a sale on the product product_id in a certain year.
Note that the price is per unit.

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

product_id is the primary key (column with unique values) of this table.
Each row of this table indicates the product name of each product.
 
Write a solution to report the product_name, year, and price for each sale_id in the Sales table.
Return the resulting table in any order.

 

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

예시

Input: 
Sales table:
+---------+------------+------+----------+-------+
| sale_id | product_id | year | quantity | price |
+---------+------------+------+----------+-------+ 
| 1       | 100        | 2008 | 10       | 5000  |
| 2       | 100        | 2009 | 12       | 5000  |
| 7       | 200        | 2011 | 15       | 9000  |
+---------+------------+------+----------+-------+
Product table:
+------------+--------------+
| product_id | product_name |
+------------+--------------+
| 100        | Nokia        |
| 200        | Apple        |
| 300        | Samsung      |
+------------+--------------+
Output: 
+--------------+-------+-------+
| product_name | year  | price |
+--------------+-------+-------+
| Nokia        | 2008  | 5000  |
| Nokia        | 2009  | 5000  |
| Apple        | 2011  | 9000  |
+--------------+-------+-------+

Explanation: 
From sale_id = 1, we can conclude that Nokia was sold for 5000 in the year 2008.
From sale_id = 2, we can conclude that Nokia was sold for 5000 in the year 2009.
From sale_id = 7, we can conclude that Apple was sold for 9000 in the year 2011.

문제 풀이

import pandas as pd

def sales_analysis(sales: pd.DataFrame, product: pd.DataFrame) -> pd.DataFrame:
    merged = pd.merge(sales, product, on = 'product_id', how= 'left')
    result = merged.loc[:,['product_name', 'year', 'price']]
    return result

import pandas as pd

def sales_analysis(sales: pd.DataFrame, product: pd.DataFrame) -> pd.DataFrame:
    return pd.merge(sales, product, on = 'product_id', how= 'left')[['product_name', 'year', 'price']]

---

파이썬을 독학하시는 분들에게 도움이 되길 바라며,

혹 더 좋은 방법이 있거나 오류가 있다면 편하게 말씀 부탁드립니다.