while in the function numpy.cov it has a meaning to specify ddof, since numpy.corrcoef return the correlation coefficient that are the normalized covariance coefficient, ddof is irrelevant.
If I did not misunderstood the meaning of numpy.cov and numpy.corrcoef, I would suggest to remove the optional argument ddof in the function numpy.corrcoef.
I agree that it should be removed, since it's only a source of confusion. This also applies to bias.
It can make a minuscule numerical difference to change ddof, since it's still passed into cov and then normalized through its diagonal. However, I see no utility for this. In order to avoid having to pick ddof arbitrarily when calling cov, I suggest omitting it and thus letting it use its default value.
@charris ddofwas added by you in a5b4a59, maybe you can comment?
Just removing the keyword will break some code, so shouldn't be done anyway. A clarification is preferable.