2889 Reshape Data: Pivot

Problem Statement

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.

For the whole problem statement, please refer here.

Plans

• Use pandas to handle the data.

• Pivot the data based on the month column.

• Provide the pivoted DataFrame with each city as a separate column.

• The resulting DataFrame should have the month as the index.

Solution

import pandas as pd

def pivotTable(weather: pd.DataFrame) -> pd.DataFrame:
    # Pivot the table to have the temperature of each city in each month
    return weather.pivot(index='month', columns='city', values='temperature')

Explanation

1. Import Pandas

   • We start by importing the Pandas library, which provides data structures and operations for manipulating numerical tables and time series.

2. Define the Function

   • We define a function pivotTable that takes a single argument weather, which is a DataFrame containing weather data.

3. Pivoting the Data

   • We use the pivot method on the DataFrame weather to pivot the data based on the month column.

   • The index='month' argument specifies that the month column should be used as the index of the resulting DataFrame.

   • The columns='city' argument specifies that the city column should be used to create separate columns for each city.

   • The values='temperature' argument specifies that the temperature column should be used to fill the values in the pivoted DataFrame.

4. Return the Result

   • We return the pivoted DataFrame with each city as a separate column and the month as the index.