Flight Occupancy and Waitlist Analysis — LeetCode 2783 Python Solution
MediumLeetCode PremiumDatabase
- Problem
- #2783
- Reading time
- 3 min
- Source
- leetcode.com
Table schema
SQL
Table: Flights +-------------+------+ | Column Name | Type | +-------------+------+ | flight_id | int | | capacity | int | +-------------+------+ flight_id is the column with unique values for this table. Each row of this table contains flight id and its capacity.Example
SQL
+-------------+------+
| Column Name | Type |
+-------------+------+
| flight_id | int |
| capacity | int |
+-------------+------+
flight_id is the column with unique values for this table.
Each row of this table contains flight id and its capacity.Python solution
Python
import duckdb
import pandas as pd
def solution(passengers: pd.DataFrame) -> pd.DataFrame:
con = duckdb.connect()
con.register("Passengers", passengers)
return con.execute("""SELECT
flight_id,
LEAST(COUNT(passenger_id), capacity) AS booked_cnt,
GREATEST(COUNT(passenger_id) - capacity, 0) AS waitlist_cnt
FROM
Flights
LEFT JOIN Passengers USING (flight_id)
GROUP BY 1
ORDER BY 1;""").df()Complexity
| Measure | Complexity |
|---|---|
| Time | O(n log n) (typical) |
| Space | O(n) auxiliary |
Related problems
Frequently asked questions
- How hard is LeetCode 2783. Flight Occupancy and Waitlist Analysis?
- LeetCode 2783. Flight Occupancy and Waitlist Analysis is rated Medium on LeetCode.
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- LeetCode 2783. Flight Occupancy and Waitlist Analysis is tagged Database on LeetCode.
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- Yes. LeetCode 2783. Flight Occupancy and Waitlist Analysis is a LeetCode Premium problem, so the full statement and test cases require a paid LeetCode subscription.