Hopper Company Queries III — LeetCode 1651 Python Solution

Table: Drivers +-------------+---------+ | Column Name | Type | +-------------+---------+ | driver_id | int | | join_date | date | +-------------+---------+ driver_id is the column with unique values for this table. Each row of this table contains the driver's ID and the date they joined the Hopper company.

+-------------+---------+
| Column Name | Type    |
+-------------+---------+
| driver_id   | int     |
| join_date   | date    |
+-------------+---------+
driver_id is the column with unique values for this table.
Each row of this table contains the driver's ID and the date they joined the Hopper company.

import duckdb
import pandas as pd

def solution(drivers: pd.DataFrame, rides: pd.DataFrame, accepted_rides: pd.DataFrame) -> pd.DataFrame:
    con = duckdb.connect()
    con.register("Drivers", drivers)
    con.register("Rides", rides)
    con.register("AcceptedRides", accepted_rides)
    return con.execute("""WITH RECURSIVE
    Months AS (
        SELECT 1 AS month
        UNION ALL
        SELECT month + 1
        FROM Months
        WHERE month < 12
    ),
    Ride AS (
        SELECT
            month,
            SUM(IFNULL(ride_distance, 0)) AS ride_distance,
            SUM(IFNULL(ride_duration, 0)) AS ride_duration
        FROM
            Months AS m
            LEFT JOIN Rides AS r ON month = MONTH(requested_at) AND YEAR(requested_at) = 2020
            LEFT JOIN AcceptedRides AS a ON r.ride_id = a.ride_id
        GROUP BY month
    )
SELECT
    month,
    ROUND(
        AVG(ride_distance) OVER (ROWS BETWEEN CURRENT ROW AND 2 FOLLOWING),
        2
    ) AS average_ride_distance,
    ROUND(
        AVG(ride_duration) OVER (ROWS BETWEEN CURRENT ROW AND 2 FOLLOWING),
        2
    ) AS average_ride_duration
FROM Ride
ORDER BY month
LIMIT 10;""").df()