python - Logical MultiIndexing in Pandas -

is there way extract values of b index one c greater zero? want extract values -0.22 , -1.21.

import numpy np import pandas pd arrays =[np.array(['one','one','one','two','two','two']),np.array(['a','b','c','a','b','c'])] df = pd.dataframe(np.random.randn(6,5),index=arrays)  df                0         1         2         3         4 1     -0.908680  0.031505 -0.087090 -0.039527  0.221196         b  1.010757  1.272553 -0.220535 -1.216996 -0.122108         c -0.781714 -1.830215  0.584311  0.010987 -0.050355 2     -0.331269  0.410596  0.569802  1.455710  0.377796         b  0.079330 -2.538031 -1.665904  0.477257  0.500805         c -0.388749  2.188289 -1.465292  0.594870 -0.031983 

you can create mask , use loc mask:

import numpy np import pandas pd np.random.seed(1) arrays = [np.array(['one','one','one','two','two','two']),           np.array(['a','b','c','a','b','c'])] df = pd.dataframe(np.random.randn(6,5),index=arrays) print (df)               0         1         2         3         4 1  1.624345 -0.611756 -0.528172 -1.072969  0.865408     b -2.301539  1.744812 -0.761207  0.319039 -0.249370     c  1.462108 -2.060141 -0.322417 -0.384054  1.133769 2 -1.099891 -0.172428 -0.877858  0.042214  0.582815     b -1.100619  1.144724  0.901591  0.502494  0.900856     c -0.683728 -0.122890 -0.935769 -0.267888  0.530355  idx = pd.indexslice mask = (df.loc[idx['one', 'c'],:]) > 0  print (mask) 0     true 1    false 2    false 3    false 4     true name: (one, c), dtype: bool  print (df.loc[idx['one', 'b'], mask]) 0   -2.301539 4   -0.249370 name: (one, b), dtype: float64