Active Businesses — LeetCode 1126 Python Solution

Table: Events +---------------+---------+ | Column Name | Type | +---------------+---------+ | business_id | int | | event_type | varchar | | occurrences | int | +---------------+---------+ (business_id, event_type) is the primary key (combination of columns with unique values) of this table. Each row in the table logs the info that an event of some type occurred at some business for a number of times.

+---------------+---------+
| Column Name   | Type    |
+---------------+---------+
| business_id   | int     |
| event_type    | varchar |
| occurrences   | int     | 
+---------------+---------+
(business_id, event_type) is the primary key (combination of columns with unique values) of this table.
Each row in the table logs the info that an event of some type occurred at some business for a number of times.

import duckdb
import pandas as pd

def solution(events: pd.DataFrame) -> pd.DataFrame:
    con = duckdb.connect()
    con.register("Events", events)
    return con.execute("""SELECT business_id
FROM
    EVENTS AS t1
    JOIN (
        SELECT
            event_type,
            AVG(occurences) AS occurences
        FROM EVENTS
        GROUP BY event_type
    ) AS t2
        ON t1.event_type = t2.event_type
WHERE t1.occurences > t2.occurences
GROUP BY business_id
HAVING COUNT(1) > 1;""").df()