2889. Reshape Data: Pivot

DataFrame weather

Column Name	Type
city	object
month	object
temperature	int

Instructions

• 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

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.

Submissions

import pandas as pd

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

Explanation

Python (Pandas)

Submitted by @noeyislearning

• import pandas as pd: This line imports the pandas library and aliases it as pd. Pandas is a popular Python library for data manipulation and analysis.
• def pivotTable(weather: pd.DataFrame) -> pd.DataFrame:
  • pivotTable is the name of the function.
  • It takes one parameter, weather, which is expected to be a pandas DataFrame (pd.DataFrame). The type hint pd.DataFrame helps developers understand that the function expects a DataFrame object as input.
  • The function is also annotated to return a DataFrame (-> pd.DataFrame).
• return weather.pivot(index='month', columns='city', values='temperature'):
  • This line uses the pivot method of the DataFrame to transform the weather DataFrame.
  • index='month': This sets the month column of the original DataFrame as the new index (rows) of the resulting pivoted table.
  • columns='city': This argument specifies that the unique values in the city column will become the columns of the resulting DataFrame.
  • values='temperature': This indicates that the values in the temperature column of the original DataFrame will fill the cells of the pivoted table.
  • The result of this operation is a pivoted table where each row represents a month, each column represents a city, and the cell values are the temperatures.