python - Hierarchical indexing with Pandas -

i have pandas dataframewith 3 index levels , 2 columns. can see part of here:

                        av_intensity  std_dev key1 key2  time                         0     0    32000          -0.005203  0.006278            32200           0.005330  0.005221            32400           0.002679  0.005006            32600          -0.000723  0.006145            32800          -0.000317  0.010467            33000          -0.006543  0.007808            33200          -0.004180  0.005070            33400          -0.006275  0.009662            33600          -0.014763  0.006938            33800          -0.029516  0.004710 

the indices numbers, e.g. (0.0, 0, 32000.0) set of indices.

i trying use df.ix[ 0.0, :, 32000.0] or df.ix[ :, 0, 32000] kind of hierarchical indexing doesn't work.

is because indices not integer?

how can kind of hierarchical indexing data frame?

see advanced hierarchical indexing section in docs full explanation: http://pandas.pydata.org/pandas-docs/dev/advanced.html#advanced-indexing-with-hierarchical-index

but basically, cannot use slices (:) within multi-index key. can creating : slice(none):

datagroupd.loc[(0.0, slice(none), 32000.0),:] 

or use indexslice convenience object lets write plain :'s:

idx = pd.indexslice datagroupd.loc[idx[0.0, :, 32000.0],:]