Concatenate the name and the profession

# Table: Person
# 
# +-------------+---------+
# | Column Name | Type    |
# +-------------+---------+
# | person_id   | int     |
# | name        | varchar |
# | profession  | ENUM    |
# +-------------+---------+
# person_id is the primary key (column with a unique value) for this table.
# Each row in this table contains a person's ID, name, and profession.
# The profession column in an enum of the type ('Doctor', 'Singer', 'Actor', 'Player', 'Engineer', or 'Lawyer')
# 
#  
# 
# Write a solution to report each person's name followed by the first letter of their profession enclosed in parentheses.
# 
# Return the result table ordered by person_id in descending order.
# 
# The result format is shown in the following example.
#
# Example 1:
# Input:
# Person table:
# +-----------+-------+------------+
# | person_id | name  | profession |
# +-----------+-------+------------+
# | 1         | Alex  | Singer     |
# | 3         | Alice | Actor      |
# | 2         | Bob   | Player     |
# | 4         | Messi | Doctor     |
# | 6         | Tyson | Engineer   |
# | 5         | Meir  | Lawyer     |
# +-----------+-------+------------+
# Output:
# +-----------+----------+
# | person_id | name     |
# +-----------+----------+
# | 6         | Tyson(E) |
# | 5         | Meir(L)  |
# | 4         | Messi(D) |
# | 3         | Alice(A) |
# | 2         | Bob(P)   |
# | 1         | Alex(S)  |
# +-----------+----------+
# Explanation: Note that there should not be any white space between the name and the first letter of the profession.

import pandas as pd

def concatenate_info(person: pd.DataFrame) -> pd.DataFrame:
  person['name'] = person['name'] + '(' + person['profession'].str[0] + ')'
  return person[['person_id', 'name']].sort_values('person_id', ascending=False)