numpy.ma.corrcoef

numpy.ma.corrcoef(x, y=None, rowvar=True, bias=<no value>, allow_masked=True, ddof=<no value>)
[source]

Return Pearson productmoment correlation coefficients.
Except for the handling of missing data this function does the same as numpy.corrcoef
. For more details and examples, see numpy.corrcoef
.
Parameters: 

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 : _NoValue, optional 
Has no effect, do not use. Deprecated since version 1.10.0. 
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. Because bias is deprecated, this argument needs to be treated as keyword only to avoid a warning. 
ddof : _NoValue, optional 
Has no effect, do not use. Deprecated since version 1.10.0. 
See also

numpy.corrcoef
 Equivalent function in toplevel NumPy module.

cov
 Estimate the covariance matrix.
Notes
This function accepts but discards arguments bias
and ddof
. This is for backwards compatibility with previous versions of this function. These arguments had no effect on the return values of the function and can be safely ignored in this and previous versions of numpy.