3601. Find Drivers with Improved Fuel Efficiency
Description
Table: drivers
+-------------+---------+ | Column Name | Type | +-------------+---------+ | driver_id | int | | driver_name | varchar | +-------------+---------+ driver_id is the unique identifier for this table. Each row contains information about a driver.
Table: trips
+---------------+---------+ | Column Name | Type | +---------------+---------+ | trip_id | int | | driver_id | int | | trip_date | date | | distance_km | decimal | | fuel_consumed | decimal | +---------------+---------+ trip_id is the unique identifier for this table. Each row represents a trip made by a driver, including the distance traveled and fuel consumed for that trip.
Write a solution to find drivers whose fuel efficiency has improved by comparing their average fuel efficiency in the first half of the year with the second half of the year.
- Calculate fuel efficiency as
distance_km / fuel_consumed
for each trip - First half: January to June, Second half: July to December
- Only include drivers who have trips in both halves of the year
- Calculate the efficiency improvement as (
second_half_avg - first_half_avg
) - Round all results to
2
decimal places
Return the result table ordered by efficiency improvement in descending order, then by driver name in ascending order.
The result format is in the following example.
Example:
Input:
drivers table:
+-----------+---------------+ | driver_id | driver_name | +-----------+---------------+ | 1 | Alice Johnson | | 2 | Bob Smith | | 3 | Carol Davis | | 4 | David Wilson | | 5 | Emma Brown | +-----------+---------------+
trips table:
+---------+-----------+------------+-------------+---------------+ | trip_id | driver_id | trip_date | distance_km | fuel_consumed | +---------+-----------+------------+-------------+---------------+ | 1 | 1 | 2023-02-15 | 120.5 | 10.2 | | 2 | 1 | 2023-03-20 | 200.0 | 16.5 | | 3 | 1 | 2023-08-10 | 150.0 | 11.0 | | 4 | 1 | 2023-09-25 | 180.0 | 12.5 | | 5 | 2 | 2023-01-10 | 100.0 | 9.0 | | 6 | 2 | 2023-04-15 | 250.0 | 22.0 | | 7 | 2 | 2023-10-05 | 200.0 | 15.0 | | 8 | 3 | 2023-03-12 | 80.0 | 8.5 | | 9 | 3 | 2023-05-18 | 90.0 | 9.2 | | 10 | 4 | 2023-07-22 | 160.0 | 12.8 | | 11 | 4 | 2023-11-30 | 140.0 | 11.0 | | 12 | 5 | 2023-02-28 | 110.0 | 11.5 | +---------+-----------+------------+-------------+---------------+
Output:
+-----------+---------------+------------------+-------------------+------------------------+ | driver_id | driver_name | first_half_avg | second_half_avg | efficiency_improvement | +-----------+---------------+------------------+-------------------+------------------------+ | 2 | Bob Smith | 11.24 | 13.33 | 2.10 | | 1 | Alice Johnson | 11.97 | 14.02 | 2.05 | +-----------+---------------+------------------+-------------------+------------------------+
Explanation:
- Alice Johnson (driver_id = 1):
- First half trips (Jan-Jun): Feb 15 (120.5/10.2 = 11.81), Mar 20 (200.0/16.5 = 12.12)
- First half average efficiency: (11.81 + 12.12) / 2 = 11.97
- Second half trips (Jul-Dec): Aug 10 (150.0/11.0 = 13.64), Sep 25 (180.0/12.5 = 14.40)
- Second half average efficiency: (13.64 + 14.40) / 2 = 14.02
- Efficiency improvement: 14.02 - 11.97 = 2.05
- Bob Smith (driver_id = 2):
- First half trips: Jan 10 (100.0/9.0 = 11.11), Apr 15 (250.0/22.0 = 11.36)
- First half average efficiency: (11.11 + 11.36) / 2 = 11.24
- Second half trips: Oct 5 (200.0/15.0 = 13.33)
- Second half average efficiency: 13.33
- Efficiency improvement: 13.33 - 11.24 = 2.09
- Drivers not included:
- Carol Davis (driver_id = 3): Only has trips in first half (Mar, May)
- David Wilson (driver_id = 4): Only has trips in second half (Jul, Nov)
- Emma Brown (driver_id = 5): Only has trips in first half (Feb)
The output table is ordered by efficiency improvement in descending order then by name in ascending order.
Solutions
Solution 1
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