Rename columns

# DataFrame students
# +-------------+--------+
# | Column Name | Type   |
# +-------------+--------+
# | id          | int    |
# | first       | object |
# | last        | object |
# | age         | int    |
# +-------------+--------+
# Write a solution to rename the columns as follows:

# id to student_id
# first to first_name
# last to last_name
# age to age_in_years
# The result format is in the following example.


# Example 1:
# Input:
# +----+---------+----------+-----+
# | id | first   | last     | age |
# +----+---------+----------+-----+
# | 1  | Mason   | King     | 6   |
# | 2  | Ava     | Wright   | 7   |
# | 3  | Taylor  | Hall     | 16  |
# | 4  | Georgia | Thompson | 18  |
# | 5  | Thomas  | Moore    | 10  |
# +----+---------+----------+-----+
# Output:
# +------------+------------+-----------+--------------+
# | student_id | first_name | last_name | age_in_years |
# +------------+------------+-----------+--------------+
# | 1          | Mason      | King      | 6            |
# | 2          | Ava        | Wright    | 7            |
# | 3          | Taylor     | Hall      | 16           |
# | 4          | Georgia    | Thompson  | 18           |
# | 5          | Thomas     | Moore     | 10           |
# +------------+------------+-----------+--------------+
# Explanation:
# The column names are changed accordingly.

import pandas as pd


def renameColumns(students: pd.DataFrame) -> pd.DataFrame:
  return students.rename(
    columns={
      "id": "student_id",
      "first": "first_name",
      "last": "last_name",
      "age": "age_in_years",
    }
  )