scipy.stats.mstats.spearmanr¶

scipy.stats.mstats.
spearmanr
(x, y=None, use_ties=True, axis=None, nan_policy='propagate')[source]¶ Calculates a Spearman rankorder correlation coefficient and the pvalue to test for noncorrelation.
The Spearman correlation is a nonparametric measure of the linear relationship between two datasets. Unlike the Pearson correlation, the Spearman correlation does not assume that both datasets are normally distributed. Like other correlation coefficients, this one varies between 1 and +1 with 0 implying no correlation. Correlations of 1 or +1 imply a monotonic relationship. Positive correlations imply that as x increases, so does y. Negative correlations imply that as x increases, y decreases.
Missing values are discarded pairwise: if a value is missing in x, the corresponding value in y is masked.
The pvalue roughly indicates the probability of an uncorrelated system producing datasets that have a Spearman correlation at least as extreme as the one computed from these datasets. The pvalues are not entirely reliable but are probably reasonable for datasets larger than 500 or so.
 Parameters
 x, y1D or 2D array_like, y is optional
One or two 1D or 2D arrays containing multiple variables and observations. When these are 1D, each represents a vector of observations of a single variable. For the behavior in the 2D case, see under
axis
, below. use_tiesbool, optional
DO NOT USE. Does not do anything, keyword is only left in place for backwards compatibility reasons.
 axisint or None, optional
If axis=0 (default), then each column represents a variable, with observations in the rows. If axis=1, the relationship is transposed: each row represents a variable, while the columns contain observations. If axis=None, then both arrays will be raveled.
 nan_policy{‘propagate’, ‘raise’, ‘omit’}, optional
Defines how to handle when input contains nan. ‘propagate’ returns nan, ‘raise’ throws an error, ‘omit’ performs the calculations ignoring nan values. Default is ‘propagate’.
 Returns
 correlationfloat
Spearman correlation coefficient
 pvaluefloat
2tailed pvalue.
References
[CRCProbStat2000] section 14.7