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我在不同的机器上运行了一些 pcmark 测试。最后我想巩固机器结果。我已经修改了最终结果以显示。我尝试过使用 pandas 进行不同形式的合并，但我无法得到预期的结果，但这已经足够接近了。任何建议，将不胜感激

来自机器 1 的数据帧： 

|------------|---------------------------|--------------|------------|  
|Test Case   | SubTest                   | App          | Count      |  
|------------|---------------------------|--------------|------------|   
|pcmark10    | AppStartUp                | NaN          | NaN        |  
|pcmark10    | PhotoEditing              | NaN          | NaN        |  
|pcmark10    | RenderingAndVisualization | NaN          | NaN        |  
|pcmark10    | Spreadsheet               | soffice.bin  | 1.0        |  
|pcmark10    | VideoConferencing         | NaN          | NaN        |  
|pcmark10    | VideoEditing              | NaN          | NaN        |  
|pcmark10    | WebBrowsing               | NaN          | NaN        |  
|pcmark10    | Writing                   | NaN          | NaN        |  
|------------|---------------------------|--------------|------------|

来自机器 2 的数据框： 

|------------|---------------------------|--------------|------------|  
|Test Case   | SubTest                   | App          | Count      |  
|------------|---------------------------|--------------|------------|   
|pcmark10    | AppStartUp                | NaN          | NaN        |  
|pcmark10    | PhotoEditing              | NaN          | NaN        |  
|pcmark10    | RenderingAndVisualization | NaN          | NaN        |  
|pcmark10    | Spreadsheet               | NaN          | NaN        |  
|pcmark10    | VideoConferencing         | NaN          | NaN        |  
|pcmark10    | VideoEditing              | NaN          | NaN        |  
|pcmark10    | WebBrowsing               | chrome.exe   | 2          |  
|pcmark10    | Writing                   | NaN          | NaN        |  
|------------|---------------------------|--------------|------------|

我希望结果如下所示：

|------------|---------------------------|--------------|------------|------------|  
|Test Case   | SubTest                   | App          | Count_x    | Count_y    |
|------------|---------------------------|--------------|------------|------------|
|pcmark10    | AppStartUp                | NaN          | NaN        | NaN        |  
|pcmark10    | PhotoEditing              | NaN          | NaN        | NaN        |  
|pcmark10    | RenderingAndVisualization | NaN          | NaN        | NaN        |  
|pcmark10    | Spreadsheet               | soffice.bin  | 1.0        | NaN        |  
|pcmark10    | VideoConferencing         | NaN          | NaN        | NaN        |  
|pcmark10    | VideoEditing              | NaN          | NaN        | NaN        |    
|pcmark10    | WebBrowsing               | chrome.exe   | NaN        | 2          |  
|pcmark10    | Writing                   | NaN          | NaN        | NaN        |  
|------------|---------------------------|--------------|------------|------------|

我尝试了结合所有键的外部合并，这就是我得到的。使用外部函数将 pcmark10 的行值引导为空白。应用列中缺少 Chrome。

|------------|---------------------------|--------------|------------|------------|  
|Test Case   | SubTest                   | App          | Count_x    | Count_y    |
|------------|---------------------------|--------------|------------|------------|
|pcmark10    | AppStartUp                | NaN          | NaN        | NaN        |  
|pcmark10    | PhotoEditing              | NaN          | NaN        | NaN        |  
|pcmark10    | RenderingAndVisualization | NaN          | NaN        | NaN        |  
|pcmark10    | Spreadsheet               | soffice.bin  | 1.0        | NaN        |  
|pcmark10    | VideoConferencing         | NaN          | NaN        | NaN        |  
|pcmark10    | VideoEditing              | NaN          | NaN        | NaN        |    
|pcmark10    | WebBrowsing               | NaN          | NaN        | 2          |  
|pcmark10    | Writing                   | NaN          | NaN        | NaN        |  
|------------|---------------------------|--------------|------------|------------|

合并命令：- pd.merge(df1, df2, on=['Test Case', 'SubTest', 'App'], how="outer", indicator=True)

4

1 回答 1

0

在您的情况下，合并Test Caseand SubTest，然后使用ffillorbfill创建App：

(df1.merge(df2, on=['Test Case', 'SubTest'])
    .assign(App=lambda x: x.filter(like='App').bfill(1).iloc[:,0])
    .drop(['App_x','App_y'], axis=1)
)

输出：

  Test Case                    SubTest  Count_x  Count_y          App
0  pcmark10                 AppStartUp      NaN      NaN          NaN
1  pcmark10               PhotoEditing      NaN      NaN          NaN
2  pcmark10  RenderingAndVisualization      NaN      NaN          NaN
3  pcmark10                Spreadsheet      1.0      NaN  soffice.bin
4  pcmark10          VideoConferencing      NaN      NaN          NaN
5  pcmark10               VideoEditing      NaN      NaN          NaN
6  pcmark10                WebBrowsing      NaN      2.0   chrome.exe
7  pcmark10                    Writing      NaN      NaN          NaN
于 2020-03-17T11:38:19.523 回答