statsmodels Error Message: "ValueError: v must be > 1 when p >= .9"

Question

I am trying to perform multiple sample comparison and Tukey HSD using the statsmodels module, but I keep getting this error message, "ValueError: v must be > 1 when p >= .9". I have tried looking this up on the internet for a possible solution, but no avail. Any chance anyone familiar with this module could help me out decipher what I am doing wrong to prompt this error. I use Python version 2.7x and spyder. Below is a sample of my data and the print statement. Thanks!

import numpy as np
from statsmodels.stats.multicomp import (pairwise_tukeyhsd,MultiComparison)

###--- Here are the data I am using:
data1 = np.array([ 1,     1,     1,     1,   976,    24,     1,     1,    15, 15780])
data2 = np.array(['lau15', 'gr17', 'fri26', 'bays29', 'dantzig4', 'KAT38','HARV50', 'HARV10', 'HARV20', 'HARV41'], dtype='|S8')

####--- Here's my print statement code: 
print pairwise_tukeyhsd(data1, data2, alpha=0.05)

Answer 1

Seems you have to provide more data than a single observation per group, in order for the test to work.

Minimal example:

from statsmodels.stats.multicomp import pairwise_tukeyhsd,MultiComparison

data=[1,2,3]
groups=['a','b','c']

print("1st try:")
try:
        print(pairwise_tukeyhsd(data,groups, alpha=0.05))
except ValueError as ve:
        print("whoops!", ve)


data.append(2)
groups.append('a')
print("2nd try:")
try:
        print( pairwise_tukeyhsd(data, groups, alpha=0.05))
except ValueError as ve:
        print("whoops!", ve)

Output:

1st try:
/home/user/.local/lib/python3.7/site-packages/numpy/core/fromnumeric.py:3367: RuntimeWarning: Degrees of freedom <= 0 for slice
  **kwargs)
/home/user/.local/lib/python3.7/site-packages/numpy/core/_methods.py:132: RuntimeWarning: invalid value encountered in double_scalars
  ret = ret.dtype.type(ret / rcount)
whoops! v must be > 1 when p >= .9
2nd try:
Multiple Comparison of Means - Tukey HSD, FWER=0.05 
====================================================
group1 group2 meandiff p-adj  lower    upper  reject
----------------------------------------------------
     a      b      0.5   0.1  -16.045  17.045  False
     a      c      1.5   0.1  -15.045  18.045  False
     b      c      1.0   0.1 -18.1046 20.1046  False
----------------------------------------------------