熊貓中的邏輯多元索引

Question

有沒有辦法爲索引One提取B的所有值，其中C大於零？所以我想提取值-0.22和-1.21。

import numpy as np 
import pandas as 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 
One  A -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 
Two  A -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 

Answer 1

您可以創建mask然後用loc通過mask：

import numpy as np 
import pandas as 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 
One A 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 
Two A -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