numpy.ma.corrcoef¶

numpy.ma.
corrcoef
(x, y=None, rowvar=True, bias=<class numpy._globals._NoValue>, allow_masked=True, ddof=<class numpy._globals._NoValue>)[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, seenumpy.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.