Immediate Food Delivery III — LeetCode 2686 Python Solution

Table: Delivery +-----------------------------+---------+ | Column Name | Type | +-----------------------------+---------+ | delivery_id | int | | customer_id | int | | order_date | date | | customer_pref_delivery_date | date | +-----------------------------+---------+ delivery_id is the column with unique values of this table. Each row contains information about food delivery to a customer that makes an order at some date and specifies a preferred delivery date (on the order date or after it).

+-----------------------------+---------+
| Column Name                 | Type    |
+-----------------------------+---------+
| delivery_id                 | int     |
| customer_id                 | int     |
| order_date                  | date    |
| customer_pref_delivery_date | date    |
+-----------------------------+---------+
delivery_id is the column with unique values of this table.
Each row contains information about food delivery to a customer that makes an order at some date and specifies a preferred delivery date (on the order date or after it).

import duckdb
import pandas as pd

def solution(delivery: pd.DataFrame) -> pd.DataFrame:
    con = duckdb.connect()
    con.register("Delivery", delivery)
    return con.execute("""SELECT  order_date
       ,ROUND(100*SUM(IF(customer_pref_delivery_date = order_date,1,0))/COUNT(*),2) AS immediate_percentage
FROM Delivery
GROUP BY  order_date
ORDER BY order_date""").df()