Converting Index into MultiIndex (hierarchical index) in Pandas

Question

In the data I am working with the index is compound - i.e. it has both item name and a timestamp, e.g. name@domain.com|2013-05-07 05:52:51 +0200.

I want to

Answer 1

My preference would be to initially read this in as a column (i.e. not as an index), then you can use the str split method:

csv = '\n'.join(['name@domain.com|2013-05-07 05:52:51 +0200, 42'] * 3)
df = pd.read_csv(StringIO(csv), header=None)

In [13]: df[0].str.split('|')
Out[13]:
0    [name@domain.com, 2013-05-07 05:52:51 +0200]
1    [name@domain.com, 2013-05-07 05:52:51 +0200]
2    [name@domain.com, 2013-05-07 05:52:51 +0200]
Name: 0, dtype: object

And then feed this into a MultiIndex (perhaps this can be done cleaner?):

m = pd.MultiIndex.from_arrays(zip(*df[0].str.split('|')))

Delete the 0th column and set the index to the new MultiIndex:

del df[0]
df.index = m

In [17]: df
Out[17]:
                                            1
name@domain.com 2013-05-07 05:52:51 +0200  42
                2013-05-07 05:52:51 +0200  42
                2013-05-07 05:52:51 +0200  42