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数据重塑：透视
DataFrame weather +-------------+--------+ | Column Name | Type | +-------------+--------+ | city | object | | month | object | | temperature | int | …
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简单 · Reshape Data: Pivot core interview pattern
答案摘要
import pandas as pd def pivotTable(weather: pd.DataFrame) -> pd.DataFrame:
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题目描述
DataFrame weather
+-------------+--------+
| Column Name | Type |
+-------------+--------+
| city | object |
| month | object |
| temperature | int |
+-------------+--------+
编写一个解决方案，以便将数据 旋转，使得每一行代表特定月份的温度，而每个城市都是一个单独的列。
输出结果格式如下示例所示。
示例 1:
输入：
+--------------+----------+-------------+
| 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 |
+--------------+----------+-------------+
输出：
+----------+--------+--------------+
| month | ElPaso | Jacksonville |
+----------+--------+--------------+
| April | 2 | 5 |
| February | 6 | 23 |
| January | 20 | 13 |
| March | 26 | 38 |
| May | 43 | 34 |
+----------+--------+--------------+
解释：
表格被旋转，每一列代表一个城市，每一行代表特定的月份。解题思路
方法一
import pandas as pd
def pivotTable(weather: pd.DataFrame) -> pd.DataFrame:
return weather.pivot(index='month', columns='city', values='temperature')
复杂度分析
| 指标 | 值 |
|---|---|
| 时间 | and space complexity depend on the number of rows and columns in the table. Pivoting is typically O(n) in time for scanning all rows and O(c*m) in space for storing the new table, where c is the number of cities and m is the number of months. |
| 空间 | Depends on the final approach |
面试官常问的追问
外企场景- question_mark
Do you recognize this as a data reshaping or pivot problem?
- question_mark
Can you suggest a pandas function that avoids manual aggregation?
- question_mark
How would you handle missing city-month temperature entries?
常见陷阱
外企场景- error
Forgetting to set the correct index, leading to a misaligned table.
- error
Not sorting months after pivoting, which may cause tests to fail.
- error
Overwriting original data instead of creating a clean pivoted table.
进阶变体
外企场景- arrow_right_alt
Pivot by multiple indices such as year and month to handle multi-year data.
- arrow_right_alt
Aggregate temperatures by mean or max if multiple entries exist per city-month.
- arrow_right_alt
Pivot with additional columns like humidity or rainfall instead of temperature.