Tabla: Employee

+-------------+------+
| Column Name | Type |
+-------------+------+
| id          | int  |
| salary      | int  |
+-------------+------+

- `id` es la llave primaria (columna con valores únicos) para esta tabla.
- Cada fila de esta tabla contiene información del salario de un empleado.

El formato del resultado se muestra en el siguiente ejemplo.

Ejemplo 1:

Entrada:

Tabla Employee:
+----+--------+
| id | salary |
+----+--------+
| 1  | 100    |
| 2  | 200    |
| 3  | 300    |
+----+--------+

Salida:

+---------------------+
| SecondHighestSalary |
+---------------------+
| 200                 |
+---------------------+

Ejemplo 2:

Entrada:

Tabla Employee:
+----+--------+
| id | salary |
+----+--------+
| 1  | 100    |
+----+--------+

Salida:

+---------------------+
| SecondHighestSalary |
+---------------------+
| null                |
+---------------------+

Solución:

import numpy as np
import pandas as pd

def second_highest_salary(employee: pd.DataFrame) -> pd.DataFrame:
    col_name = 'SecondHighestSalary'

    salaries = employee['salary'].drop_duplicates()
    two_highest = salaries.nlargest(2).reset_index()

    try:
        second = two_highest.loc[1]  # Second highest salary

        return pd.DataFrame(
            [[second['salary']]], columns=[col_name]
        ).astype({col_name: 'int64'})
    except KeyError:
        return pd.DataFrame({col_name: [np.nan]})