Reshape Data: Pivot

DataFrame weather

+-------------+--------+
| Column Name | Type   |
+-------------+--------+
| city        | object |
| month       | object |
| temperature | int    |
+-------------+--------+

Write a solution to pivot the data so that each row represents temperatures for a specific month, and each city is a separate column.

The result format is in the following example.

Example 1:

Input:
+--------------+----------+-------------+
| city         | month    | temperature |
+--------------+----------+-------------+
| Jacksonville | January  | 13          |
| Jacksonville | February | 23          |
| Jacksonville | March    | 38          |
| Jacksonville | April    | 5           |
| Jacksonville | May      | 34          |
| ElPaso       | January  | 20          |
| ElPaso       | February | 6           |
| ElPaso       | March    | 26          |
| ElPaso       | April    | 2           |
| ElPaso       | May      | 43          |
+--------------+----------+-------------+
Output:
+----------+--------+--------------+
| month    | ElPaso | Jacksonville |
+----------+--------+--------------+
| April    | 2      | 5            |
| February | 6      | 23           |
| January  | 20     | 13           |
| March    | 26     | 38           |
| May      | 43     | 34           |
+----------+--------+--------------+
Explanation:
The table is pivoted, each column represents a city, and each row represents a specific month.

Solution

import pandas as pd


def pivotTable(weather: pd.DataFrame) -> pd.DataFrame:
    return weather.pivot(index='month', columns='city', values='temperature')


if __name__ == '__main__':
    data = [['Jacksonville', 'January', 13],
            ['Jacksonville', 'February', 23],
            ['Jacksonville', 'March', 38],
            ['Jacksonville', 'April', 5],
            ['Jacksonville', 'May', 34],
            ['ElPaso', 'January', 20],
            ['ElPaso', 'February', 6],
            ['ElPaso', 'March', 26],
            ['ElPaso', 'April', 2],
            ['ElPaso', 'May', 43]
            ]
    weather = pd.DataFrame(data, columns=['city', 'month', 'temperature'])
    print(pivotTable(weather))