如何修复不平衡的列多索引?

我试着读入几个结构不好的csv文件:

[empty], A, A, B, B
time   , X, Y, X, Y
0.0    , 0, 0, 0, 0
1.0    , 2, 5, 7, 0
...    , ., ., ., .

使用 pandas.read_csv 与 header=[0,1] 参数I可以很好地访问值:

>>> df = pd.read_csv('file.csv', header=[0,1]'
>>> df.A.X
0 0
1 2
...

但是时间头上方的空字段会导致 Unnamed: 0_level_0 级别:

>>> df.columns
MultiIndex(levels=[['Unnamed: 0_level_0', 'A', 'B'], ...

有什么方法可以解决这个问题,这样我就可以用 df.Time 再一次?

编辑

这是真实数据集的片段:

,,Bone,Bone,Bone
,,Skeleton1_Hip,Skeleton1_Hip,Skeleton1_Hip
,,"1","1","1"
,,Rotation,Rotation,Rotation
Frame,Time,X,Y,Z
0,0.000000,0.009332,0.999247,0.021044
1,0.008333,0.009572,0.999217,0.020468
3,0.016667,0.009871,0.999183,0.019797

(另见: https://gist.github.com/fhaust/25ba612f99420d366f0597b15dbf43e7 更完整的例子)

阅读途径:

pd.read_csv(file, skiprows=2, header=[0,1,3,4], index_col=[1])

我真的不在乎 Frame 列,因为它是用行索引隐式给定的。