numpy.ma.corrcoef¶
-
numpy.ma.
corrcoef
(x, y=None, rowvar=True, bias=False, allow_masked=True, ddof=None)[source]¶ Return correlation coefficients of the input array.
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 1-D or 2-D 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
(N-1)
, whereN
is the number of observations given (unbiased estimate). If bias is 1, then normalization is byN
. This keyword can be overridden by the keywordddof
in numpy versions >= 1.5.allow_masked : bool, optional
If True, masked values are propagated pair-wise: 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)
, whereN
is the number of observations; this overrides the value implied bybias
. The default value isNone
.See also
numpy.corrcoef
- Equivalent function in top-level NumPy module.
cov
- Estimate the covariance matrix.