x : array_like
A 1D or 2D array containing multiple variables and observations.
Each row of x represents a variable, and each column a single
observation of all those variables. Also see rowvar below.
y : array_like, optional
An additional set of variables and observations. y has the same
shape as x.
rowvar : bool, optional
If rowvar is True (default), then each row represents a
variable, with observations in the columns. Otherwise, the relationship
is transposed: each column represents a variable, while the rows
contain observations.
bias : bool, optional
Default normalization (False) is by (N1), where N is the
number of observations given (unbiased estimate). If bias is 1,
then normalization is by N. This keyword can be overridden by
the keyword ddof in numpy versions >= 1.5.
allow_masked : bool, optional
If True, masked values are propagated pairwise: if a value is masked
in x, the corresponding value is masked in y.
If False, raises an exception.
ddof : {None, int}, optional
New in version 1.5.
If not None normalization is by (N  ddof), where N is
the number of observations; this overrides the value implied by
bias. The default value is None.
