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            "questionId": "3072",
            "questionFrontendId": "100013",
            "categoryTitle": "Algorithms",
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            "title": "Reshape Data: Pivot",
            "titleSlug": "reshape-data-pivot",
            "content": "<pre>\nDataFrame <code>weather</code>\n+-------------+--------+\n| Column Name | Type   |\n+-------------+--------+\n| city        | object |\n| month       | object |\n| temperature | int    |\n+-------------+--------+\n</pre>\n\n<p>Write a solution to <strong>pivot</strong> the data so that each row represents temperatures for a specific month, and each city is a separate column.</p>\n\n<p>The result format is in the following example.</p>\n\n<p>&nbsp;</p>\n<pre>\n<strong class=\"example\">Example 1:</strong>\n<strong>Input:</strong>\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+--------------+----------+-------------+\n<strong>Output:</strong><code>\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+----------+--------+--------------+</code>\n<strong>Explanation:\n</strong>The table is pivoted, each column represents a city, and each row represents a specific month.</pre>\n",
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                    "lang": "Pandas",
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                    "code": "import pandas as pd\n\ndef pivotTable(weather: pd.DataFrame) -> pd.DataFrame:\n    ",
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                "Consider using a built-in function in pandas library to transform the data"
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            "sampleTestCase": "{\"headers\":{\"weather\":[\"city\",\"month\",\"temperature\"]},\"rows\":{\"weather\":[[\"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]]}}",
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            "exampleTestcases": "{\"headers\":{\"weather\":[\"city\",\"month\",\"temperature\"]},\"rows\":{\"weather\":[[\"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]]}}",
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