Python 堆栈相关列

我有以下数据集，是从pandas dataframe中提取的

{'Batch': {0: 'Nos705', 1: 'Nos706', 2: 'Nos707', 3: 'Nos708', 4: 'Nos709', 5: 'Nos710', 6: 'Nos711', 7: 'Nos713', 8: 'Nos714', 9: 'Nos715'}, 
'Message': {0: 'ACBB', 1: 'ACBL', 2: 'ACBL', 3: 'ACBC', 4: 'ACBC', 5: 'ACBC', 6: 'ACBL', 7: 'ACBL', 8: 'ACBL', 9: 'ACBL'}, 
'DCC': {0: 284, 1: 21, 2: 43, 3: 19, 4: 0, 5: 0, 6: 19, 7: 27, 8: 27, 9: 19}, 
'DCB': {0: 299, 1: 22, 2: 24, 3: 28, 4: 167, 5: 167, 6: 20, 7: 27, 8: 27, 9: 28}, 
'ISC': {0: 'Car010030', 1: 'Car010054', 2: 'Car010047', 3: 'Car010182', 4: 'Car010004', 5: 'Car010004', 6: 'Car010182', 7: 'Car010182', 8: 'Car010182', 9: 'Car010182'},
'ISB': {0: 'Car010010', 1: None, 2: None, 3: None, 4: None, 5: None, 6: None, 7: None, 8: None, 9: None}, 
'VSC': {0: 25, 1: 25, 2: 25, 3: 25, 4: 25, 5: 25, 6: 25, 7: 25, 8: 25, 9: 25},
'VSB': {0: 27.0, 1: nan, 2: nan, 3: nan, 4: nan, 5: nan, 6: nan, 7: nan, 8: nan, 9: nan},
'PGC': {0: 2.78, 1: 2.79, 2: 2.08, 3: 2.08, 4: 2.08, 5: 2.08, 6: 2.71, 7: 1.73, 8: 1.73, 9: 1.73}, 
'PGB': {0: 2.95, 1: nan, 2: nan, 3: nan, 4: nan, 5: nan, 6: nan, 7: nan, 8: nan, 9: nan}, 
'PHB': {0: 2.96, 1: nan, 2: nan, 3: nan, 4: nan, 5: nan, 6: nan, 7: nan, 8: nan, 9: nan}, 
'PHC': {0: 2.94, 1: 2.94, 2: 1.63, 3: 1.63, 4: 1.63, 5: 1.63, 6: 2.06, 7: 1.75, 8: 1.75, 9: 1.75}, 
'BPC': {0: 3.17, 1: 3.17, 2: 3.17, 3: 3.17, 4: 3.17, 5: 3.17, 6: 3.17, 7: 3.17, 8: 3.17, 9: 3.17}, 
'BPB': {0: None, 1: None, 2: None, 3: None, 4: None, 5: None, 6: None, 7: None, 8: None, 9: None}}

我想创建一个为相关列堆叠的数据帧 例：DCC和DCB的所有值应显示在一列中，一列在另一列的下方。同样适用于ISC和ISB、VSC和VSB、PGC和PCB、PHC和PHB、BPC和BPB

批处理仍然是这里的主键。它是如何用Python实现的

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首先将重复的列转换为多索引：

df1 = df.set_index(['Batch','Message'])

然后在列中创建

多索引

，按列名称中没有最后和最后值的所有值创建，并按重塑，按正确顺序添加：

如有必要，最后删除

类型

列：

df1 = df1.drop('types', axis=1) 

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请张贴您的预期输出图像快照的预期输出添加

df1 = df1.drop('types', axis=1)