在python中将单个熊猫索引转换为三级MultiIndex

Question

I have some data in a pandas dataframe which looks like this:

gene                                  VIM  
time:2|treatment:TGFb|dose:0.1  -0.158406  
time:2|treatment:TGFb|dose:1     0.039158  
time:2|treatment:TGFb|dose:10   -0.052608  
time:24|treatment:TGFb|dose:0.1  0.157153  
time:24|treatment:TGFb|dose:1    0.206030  
time:24|treatment:TGFb|dose:10   0.132580  
time:48|treatment:TGFb|dose:0.1 -0.144209  
time:48|treatment:TGFb|dose:1   -0.093910  
time:48|treatment:TGFb|dose:10  -0.166819  
time:6|treatment:TGFb|dose:0.1   0.097548  
time:6|treatment:TGFb|dose:1     0.026664  
time:6|treatment:TGFb|dose:10   -0.008032  

where the left is an index. This is just a subsection of the data which is actually much larger. The index is composed of three components, time, treatment and dose. I want to reorganize this data such that I can access it easily by slicing. The way to do this is to use pandas MultiIndexing but I don't know how to convert my DataFrame with one index into another with three. Does anybody know how to do this?

To clarify, the desired output here is the same data with a three level index, the outer being treatment, middle is dose and the inner being time. This would be useful so then I could access the data with something like df['time']['dose'] or 'df[0]` (or something to that effect at least).

Answer 1

You can first replace unnecessary strings (index has to be converted to Series by to_series , because replace doesnt work with index yet) and then use split . Last set index names by rename_axis (new in pandas 0.18.0 )

df.index = df.index.to_series().replace({'time:':'','treatment:': '','dose:':''}, regex=True)
df.index = df.index.str.split('|', expand=True)
df = df.rename_axis(('time','treatment','dose'))

print (df)
                          VIM
time treatment dose          
2    TGFb      0.1  -0.158406
               1     0.039158
               10   -0.052608
24   TGFb      0.1   0.157153
               1     0.206030
               10    0.132580
48   TGFb      0.1  -0.144209
               1    -0.093910
               10   -0.166819
6    TGFb      0.1   0.097548
               1     0.026664
               10   -0.008032