如何合并两个具有不同索引级别的数据框？

Question

我的第一个DataFrame代码：

 data = {'Sr.No.': Sr_no,
    'CompanyNames': Company_Names,
    'YourChoice1': ['1','2','3','4','5','6','7','8','9'],
    'YourChoice2': ['1','2','3','4','5','6','7','8','9']}


 df = pd.DataFrame(data, columns = ['Sr.No.', 'CompanyNames','YourChoice1','YourChoice2'])

.csv文件中此数据帧的输出为：

第二个DataFrame代码：

 data = {'BB': {'Field1': {'Previous Data': ['1','2','3','4','5','6','7','8','9'],
                      'Current Data': ['1','2','3','4','5','6','7','8','9']},

           'Field2': {'Previous Data': ['1','2','3','4','5','6','7','8','9'],
                      'Current Data': ['1','2','3','4','5','6','7','8','9']},

           'Field3': {'Previous Data': ['1','2','3','4','5','6','7','8','9'],
                      'Current Data': ['1','2','3','4','5','6','7','8','9']}
           },


    'MD': {'Field1': {'Previous Data': ['1','2','3','4','5','6','7','8','9'],
                      'Current Data': ['1','2','3','4','5','6','7','8','9']},

           'Field2': {'Previous Data': ['1','2','3','4','5','6','7','8','9'],
                      'Current Data': ['1','2','3','4','5','6','7','8','9']}
           }
    }

 form = {(outerKey,midKey,innerKey): values   for outerKey, midDict in data.items()   for midKey, innerDict in midDict.items()  for innerKey, values in innerDict.items()}

 df.to_csv('CSV_File_Name.csv', index=False)

此数据帧的输出为：

我想组合这些数据帧，以便获得以下期望的输出：