Maximum transaction each day

# Table: Transactions
# 
# +----------------+----------+
# | Column Name    | Type     |
# +----------------+----------+
# | transaction_id | int      |
# | day            | datetime |
# | amount         | int      |
# +----------------+----------+
# transaction_id is the column with unique values for this table.
# Each row contains information about one transaction.
# 
#  
# 
# Write a solution to report the IDs of the transactions with the maximum amount on their respective day. If in one day there are multiple such transactions, return all of them.
# 
# Return the result table ordered by transaction_id  in ascending order.
# 
# The result format is in the following example.
#
# Example 1:
# Input:
# Transactions table:
# +----------------+--------------------+--------+
# | transaction_id | day                | amount |
# +----------------+--------------------+--------+
# | 8              | 2021-4-3 15:57:28  | 57     |
# | 9              | 2021-4-28 08:47:25 | 21     |
# | 1              | 2021-4-29 13:28:30 | 58     |
# | 5              | 2021-4-28 16:39:59 | 40     |
# | 6              | 2021-4-29 23:39:28 | 58     |
# +----------------+--------------------+--------+
# Output:
# +----------------+
# | transaction_id |
# +----------------+
# | 1              |
# | 5              |
# | 6              |
# | 8              |
# +----------------+
# Explanation:
# "2021-4-3"  --> We have one transaction with ID 8, so we add 8 to the result table.
# "2021-4-28" --> We have two transactions with IDs 5 and 9. The transaction with ID 5 has an amount of 40, while the transaction with ID 9 has an amount of 21. We only include the transaction with ID 5 as it has the maximum amount this day.
# "2021-4-29" --> We have two transactions with IDs 1 and 6. Both transactions have the same amount of 58, so we include both in the result table.
# We order the result table by transaction_id after collecting these IDs.

import pandas as pd

def find_maximum_transaction(transactions: pd.DataFrame) -> pd.DataFrame:
  transactions['date'] = transactions['day'].dt.date
  max_per_day = transactions.groupby('date')['amount'].transform('max')
  result = transactions[transactions['amount'] == max_per_day][['transaction_id']]
  return result.sort_values('transaction_id')