In [2]:

    

import numpy as np
import pandas as pd


    

In [5]:

    

from sklearn.utils.extmath import cartesian
a = cartesian([np.arange(3),np.arange(3)])
joint_table = pd.DataFrame(a, columns=["X", "Y"])


    

In [6]:

    

probs = np.array([1/8, 1/8, 0, 1/8, 2/8, 1/8, 0, 1/8, 1/8])
joint_table["probability"] = probs
joint_table


    

    
Out[6]:







  

    

      

      
X
      
Y
      
probability
    
  
  

    

      
0
      
0
      
0
      
0.125
    
    

      
1
      
0
      
1
      
0.125
    
    

      
2
      
0
      
2
      
0.000
    
    

      
3
      
1
      
0
      
0.125
    
    

      
4
      
1
      
1
      
0.250
    
    

      
5
      
1
      
2
      
0.125
    
    

      
6
      
2
      
0
      
0.000
    
    

      
7
      
2
      
1
      
0.125
    
    

      
8
      
2
      
2
      
0.125
    
  

In [ ]:

    

rearrange = joint_table_new.pivot_table(index="Y", columns="X")
rearrange.index = ["Y=0", "Y=1", "Y=2"]
rearrange.columns = ["X=0", "X=1", "X=2"]
rearrange