Sorting Multi-Index to full depth (Pandas)

Question

I have a dataframe which Im loading from a csv file and then setting the index to few of its columns (usually two or three) by the set_index method. The idea is to

Answer 1

Its not really clear what you are asking. Multi-index docs are here

The OP needs to set the index, then sort in place

df.set_index(['fileName','phrase'],inplace=True)
df.sortlevel(inplace=True)

Then access these levels via a tuple to get a specific result

df.ix[('somePath','somePhrase')]

Maybe just give a toy example like this and show I want to get a specific result.

In [1]: arrays = [np.array(['bar', 'bar', 'baz', 'baz', 'foo', 'foo', 'qux', 'qux'])
   ...:    .....: ,
   ...:    .....:           np.array(['one', 'two', 'one', 'two', 'one', 'two', 'one', 'two'])
   ...:    .....:           ]

In [2]: df = DataFrame(randn(8, 4), index=arrays)

In [3]: df
Out[3]: 
                0         1         2         3
bar one  1.654436  0.184326 -2.337694  0.625120
    two  0.308995  1.219156 -0.906315  1.555925
baz one -0.180826 -1.951569  1.617950 -1.401658
    two  0.399151 -1.305852  1.530370 -0.132802
foo one  1.097562  0.097126  0.387418  0.106769
    two  0.465681  0.270120 -0.387639 -0.142705
qux one -0.656487 -0.154881  0.495044 -1.380583
    two  0.274045 -0.070566  1.274355  1.172247

In [4]: df.index.lexsort_depth
Out[4]: 2

In [5]: df.ix[('foo','one')]
Out[5]: 
0    1.097562
1    0.097126
2    0.387418
3    0.106769
Name: (foo, one), dtype: float64

In [6]: df.ix['foo']
Out[6]: 
            0         1         2         3
one  1.097562  0.097126  0.387418  0.106769
two  0.465681  0.270120 -0.387639 -0.142705

In [7]: df.ix[['foo']]
Out[7]: 
                0         1         2         3
foo one  1.097562  0.097126  0.387418  0.106769
    two  0.465681  0.270120 -0.387639 -0.142705

In [8]: df.sortlevel(level=1)
Out[8]: 
                0         1         2         3
bar one  1.654436  0.184326 -2.337694  0.625120
baz one -0.180826 -1.951569  1.617950 -1.401658
foo one  1.097562  0.097126  0.387418  0.106769
qux one -0.656487 -0.154881  0.495044 -1.380583
bar two  0.308995  1.219156 -0.906315  1.555925
baz two  0.399151 -1.305852  1.530370 -0.132802
foo two  0.465681  0.270120 -0.387639 -0.142705
qux two  0.274045 -0.070566  1.274355  1.172247

In [10]: df.sortlevel(level=1).index.lexsort_depth
Out[10]: 0