Specify Multi-Level columns using pd.read_clipboard?

问题

Here's some data from another question:

main    Meas1     Meas2 Meas3   Meas4  Meas5
sublvl  Value     Value Value   Value   Value       
count   7.000000  1.0   1.0     582.00  97.000000       
mean    30        37.0  26.0    33.03   16.635350

I would like to read in this data in such a way that the first column is actually the index, and the first two rows are treated as multi-level columns where MeasX is the first level, and Value is the second level.

How can I do this using pd.read_clipboard?

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My pd.read_clipboard series:

• How do you handle column names having spaces in them when using pd.read_clipboard?

• How to handle custom named index when copying a dataframe using pd.read_clipboard?

• Copying MultiIndex dataframes with pd.read_clipboard?

回答1:

In [17]: pd.read_clipboard(sep='\s+', index_col=[0], header=[0,1])
Out[17]: 
main   Meas1 Meas2 Meas3   Meas4     Meas5
sublvl Value Value Value   Value     Value
count    7.0   1.0   1.0  582.00  97.00000
mean    30.0  37.0  26.0   33.03  16.63535

来源：https://stackoverflow.com/questions/45800520/specify-multi-level-columns-using-pd-read-clipboard