DataFrame report
+-------------+--------+
| Column Name | Type   |
+-------------+--------+
| product     | object |
| quarter_1   | int    |
| quarter_2   | int    |
| quarter_3   | int    |
| quarter_4   | int    |
+-------------+--------+

El formato del resultado se muestra en el siguiente ejemplo.

Ejemplo 1:

Entrada:

+-------------+-----------+-----------+-----------+-----------+
| product     | quarter_1 | quarter_2 | quarter_3 | quarter_4 |
+-------------+-----------+-----------+-----------+-----------+
| Umbrella    | 417       | 224       | 379       | 611       |
| SleepingBag | 800       | 936       | 93        | 875       |
+-------------+-----------+-----------+-----------+-----------+

Salida:

+-------------+-----------+-------+
| product     | quarter   | sales |
+-------------+-----------+-------+
| Umbrella    | quarter_1 | 417   |
| SleepingBag | quarter_1 | 800   |
| Umbrella    | quarter_2 | 224   |
| SleepingBag | quarter_2 | 936   |
| Umbrella    | quarter_3 | 379   |
| SleepingBag | quarter_3 | 93    |
| Umbrella    | quarter_4 | 611   |
| SleepingBag | quarter_4 | 875   |
+-------------+-----------+-------+

Explicación:
El DataFrame pasa de formato ancho a largo. Cada fila representa las ventas de un producto en un trimestre.

Solución

import pandas as pd


def meltTable(report: pd.DataFrame) -> pd.DataFrame:
    return report.melt(id_vars='product',
                       var_name='quarter',
                       value_name='sales')