数据合并 Pandas

Question

我运行在不同的机器上进行了一些 pcmark 测试。最后我想巩固机器结果。我修改了最终结果以显示。我尝试了使用 pandas 的不同形式的合并，但我无法获得预期的结果，但这已经足够接近了。如有任何建议，我们将不胜感激

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 的数据帧：

|------------|---------------------------|--------------|------------|  
|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 的行值与 web 浏览器引导为空白。 Chrome 缺少应用程序列。

|------------|---------------------------|--------------|------------|------------|  
|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)

Answer 1

在您的情况下，合并 Test Case 和 SubTest，然后使用 ffill 或 bfill 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

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