In [1]:

    

import scikit_posthocs as sp
import numpy as np
import pandas as pd


    

In [2]:

    

x = [[1,2,3,5,1], [12,31,54], [10,12,6,74,11]]
sp.posthoc_conover(x)


    

    
Out[2]:





array([[ -1.00000000e+00,   3.98391078e-04,   1.39164426e-03],
       [  3.98391078e-04,  -1.00000000e+00,   1.86722274e-01],
       [  1.39164426e-03,   1.86722274e-01,  -1.00000000e+00]])

In [3]:

    

sp.posthoc_conover(x, p_adjust = 'holm')


    

    
Out[3]:





array([[-1.        ,  0.00119517,  0.00278329],
       [ 0.00119517, -1.        ,  0.18672227],
       [ 0.00278329,  0.18672227, -1.        ]])

In [4]:

    

groups = [['a']*5, ['b']*3, ['c']*5]
df = pd.DataFrame({'vals': np.concatenate(x), 'groups': np.concatenate(groups)})
df


    

    
Out[4]:







  

    

      

      
groups
      
vals
    
  
  

    

      
0
      
a
      
1
    
    

      
1
      
a
      
2
    
    

      
2
      
a
      
3
    
    

      
3
      
a
      
5
    
    

      
4
      
a
      
1
    
    

      
5
      
b
      
12
    
    

      
6
      
b
      
31
    
    

      
7
      
b
      
54
    
    

      
8
      
c
      
10
    
    

      
9
      
c
      
12
    
    

      
10
      
c
      
6
    
    

      
11
      
c
      
74
    
    

      
12
      
c
      
11
    
  

In [5]:

    

result = sp.posthoc_conover(df, val_col='vals', group_col='groups')
result


    

    
Out[5]:







  

    

      

      
a
      
b
      
c
    
  
  

    

      
a
      
-1.000000
      
0.000398
      
0.001392
    
    

      
b
      
0.000398
      
-1.000000
      
0.186722
    
    

      
c
      
0.001392
      
0.186722
      
-1.000000