I'm using scipy version 1.0.0.
import scipy as sp
x = [[5829225, 5692693], [5760959, 5760959]]
sp.stats.fisher_exact(x)
For the values above scipy does not return anything but waits. What can be the reason for that? How can I fix it?
However in R it returns a p-value almost immediately.
a = matrix(c(5829225,5692693,5760959,5760959), nrow=2)
fisher.test(a)
From the notes in the documentation:
The calculated odds ratio is different from the one R uses. This scipy implementation returns the (more common) “unconditional Maximum Likelihood Estimate”, while R uses the “conditional Maximum Likelihood Estimate”.
For tables with large numbers, the (inexact) chi-square test implemented in the function chi2_contingency can also be used.
(Emphasis mine)
Like DSM's comment mentioned, it's probably just very slow for your large values. And since the notes call out large values, you might try the alternative they suggest:
>>> chi2, p, dof, expected = sp.stats.chi2_contingency(x)
>>> p
6.140729432506709e-178