import pandas as pd
def pivotTable(weather: pd.DataFrame) -> pd.DataFrame:
100013. 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.
原站题解
pythondata 解法, 执行用时: 316 ms, 内存消耗: 60.3 MB, 提交时间: 2023-10-07 10:35:01
''' pivot ''' import pandas as pd def pivotTable(weather: pd.DataFrame) -> pd.DataFrame: return weather.pivot(index='month', columns='city', values='temperature')