Active businesses

# 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.
# 
# The average activity for a particular event_type is the average occurrences across all companies that have this event.
# 
# An active business is a business that has more than one event_type such that their occurrences is strictly greater than the average activity for that event.
# 
# Write a solution to find all active businesses.
# 
# Return the result table in any order.
# 
# The result format is in the following example.
#
# Example 1:
# Input:
# Events table:
# +-------------+------------+-------------+
# | business_id | event_type | occurrences |
# +-------------+------------+-------------+
# | 1           | reviews    | 7           |
# | 3           | reviews    | 3           |
# | 1           | ads        | 11          |
# | 2           | ads        | 7           |
# | 3           | ads        | 6           |
# | 1           | page views | 3           |
# | 2           | page views | 12          |
# +-------------+------------+-------------+
# Output:
# +-------------+
# | business_id |
# +-------------+
# | 1           |
# +-------------+
# Explanation:
# The average activity for each event can be calculated as follows:
# - 'reviews': (7+3)/2 = 5
# - 'ads': (11+7+6)/3 = 8
# - 'page views': (3+12)/2 = 7.5
# The business with id=1 has 7 'reviews' events (more than 5) and 11 'ads' events (more than 8), so it is an active business.

import pandas as pd

def active_businesses(events: pd.DataFrame) -> pd.DataFrame:
  avg_activity = events.groupby('event_type')['occurrences'].mean().reset_index()
  avg_activity.columns = ['event_type', 'avg_occurrences']
  merged = events.merge(avg_activity, on='event_type')
  above_avg = merged[merged['occurrences'] > merged['avg_occurrences']]
  result = above_avg.groupby('business_id')['event_type'].count().reset_index()
  result = result[result['event_type'] > 1][['business_id']]
  return result