{ "data": { "question": { "questionId": "3072", "questionFrontendId": "2889", "boundTopicId": null, "title": "Reshape Data: Pivot", "titleSlug": "reshape-data-pivot", "content": "
\nDataFrame weather\n+-------------+--------+\n| Column Name | Type   |\n+-------------+--------+\n| city        | object |\n| month       | object |\n| temperature | int    |\n+-------------+--------+\n
\n\n

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

\n\n

The result format is in the following example.

\n\n

 

\n
\nExample 1:\nInput:\n+--------------+----------+-------------+\n| city         | month    | temperature |\n+--------------+----------+-------------+\n| Jacksonville | January  | 13          |\n| Jacksonville | February | 23          |\n| Jacksonville | March    | 38          |\n| Jacksonville | April    | 5           |\n| Jacksonville | May      | 34          |\n| ElPaso       | January  | 20          |\n| ElPaso       | February | 6           |\n| ElPaso       | March    | 26          |\n| ElPaso       | April    | 2           |\n| ElPaso       | May      | 43          |\n+--------------+----------+-------------+\nOutput:\n+----------+--------+--------------+\n| month    | ElPaso | Jacksonville |\n+----------+--------+--------------+\n| April    | 2      | 5            |\n| February | 6      | 23           |\n| January  | 20     | 13           |\n| March    | 26     | 38           |\n| May      | 43     | 34           |\n+----------+--------+--------------+\nExplanation:\nThe table is pivoted, each column represents a city, and each row represents a specific month.
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Python 3.10 with Pandas 2.0.2 and NumPy 1.25.0

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