scipy.stats.mstats.pearsonr¶

scipy.stats.mstats.
pearsonr
(x, y)[source]¶ Calculates a Pearson correlation coefficient and the pvalue for testing noncorrelation.
The Pearson correlation coefficient measures the linear relationship between two datasets. Strictly speaking, Pearson’s correlation requires that each dataset be normally distributed. Like other correlation coefficients, this one varies between 1 and +1 with 0 implying no correlation. Correlations of 1 or +1 imply an exact linear relationship. Positive correlations imply that as x increases, so does y. Negative correlations imply that as x increases, y decreases.
The pvalue roughly indicates the probability of an uncorrelated system producing datasets that have a Pearson 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
 x1D array_like
Input
 y1D array_like
Input
 Returns
 pearsonrfloat
Pearson’s correlation coefficient, 2tailed pvalue.
References
http://www.statsoft.com/textbook/glosp.html#Pearson%20Correlation