Professional Name Tag Formatter

Easy

A workforce directory service stores a person's primary profession and needs a compact display label for profile cards. Table: Person person_id: unique person identifier name: person display name profession: one of the following values: Doctor, Singer, Actor, Player, Engineer, Lawyer Task: For every row, create a formatted label in this exact pattern: <name> (<first_letter_of_profession>) Examples of the required formatting: "Mira" with profession "Engineer" -> "Mira(E)" "Arun" with profession "Doctor" -> "Arun(D)" Output requirements: Return exactly two columns: person_id name The output "name" column must contain the formatted label. Do not include whitespace between the base name and parentheses. Sort the final result by person_id in descending order. Supported submission environments: SQL (SQLite 3.27.2) Pandas (Python)

Example 1

Input

Person:
| 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":6,"name":"Tyson(E)"},
  {"person_id":5,"name":"Meir(L)"},
  {"person_id":4,"name":"Messi(D)"},
  {"person_id":3,"name":"Alice(A)"},
  {"person_id":2,"name":"Bob(P)"},
  {"person_id":1,"name":"Alex(S)"}
]

Explanation

Each output name is original name plus profession initial in parentheses. Rows are ordered by person_id descending.

Example 2

Input

Person:
| person_id | name   | profession |
|-----------|--------|------------|
| 101       | A      | Actor      |
| 98        | Brenda | Doctor     |
| 205       | Carl   | Lawyer     |
| 77        | Diana  | Singer     |

Output

[
  {"person_id":205,"name":"Carl(L)"},
  {"person_id":101,"name":"A(A)"},
  {"person_id":98,"name":"Brenda(D)"},
  {"person_id":77,"name":"Diana(S)"}
]

Explanation

Even when input rows are unsorted, output must be sorted by descending person_id.

Example 3

Input

Person:
| person_id | name      | profession |
|-----------|-----------|------------|
| 900       | alEX      | Engineer   |
| 450       | maria     | Player     |
| 901       | Zed       | Doctor     |

Output

[
  {"person_id":901,"name":"Zed(D)"},
  {"person_id":900,"name":"alEX(E)"},
  {"person_id":450,"name":"maria(P)"}
]

Explanation

Name text itself is preserved; only profession initial is appended inside parentheses.

Constraints

1 <= number of rows in Person <= 50000
1 <= person_id <= 1000000000
person_id is unique
1 <= length(name) <= 100
name contains only uppercase/lowercase English letters
profession is one of: Doctor, Singer, Actor, Player, Engineer, Lawyer
Output must contain exactly columns [person_id, name]
Output name format is <name>(<first_letter_of_profession>) with no spaces
Result must be ordered by person_id descending
For SQL submissions, use SQLite 3.27.2 semantics
For Pandas submissions, return a DataFrame with columns: person_id, name

Person: | person_id | name | profession | |-----------|-------|------------| | 1 | Alex | Singer | | 3 | Alice | Actor | | 2 | Bob | Player | | 4 | Messi | Doctor | | 6 | Tyson | Engineer | | 5 | Meir | Lawyer |

[ {"person_id":6,"name":"Tyson(E)"}, {"person_id":5,"name":"Meir(L)"}, {"person_id":4,"name":"Messi(D)"}, {"person_id":3,"name":"Alice(A)"}, {"person_id":2,"name":"Bob(P)"}, {"person_id":1,"name":"Alex(S)"} ]

Person: | person_id | name | profession | |-----------|--------|------------| | 101 | A | Actor | | 98 | Brenda | Doctor | | 205 | Carl | Lawyer | | 77 | Diana | Singer |

Person: | person_id | name | profession | |-----------|-----------|------------| | 900 | alEX | Engineer | | 450 | maria | Player | | 901 | Zed | Doctor |