It would be nice if we had access to pydoc from the research environment.... Here is an example of it's usage
from pydoc import help
from scipy.stats.stats import pearsonr
help(pearsonr)
Help on function pearsonr in module scipy.stats.stats:
pearsonr(x, y)
Calculates a Pearson correlation coefficient and the p-value for testing
non-correlation.
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 p-value 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 p-values are not entirely
reliable but are probably reasonable for datasets larger than 500 or so.
Parameters
x : 1D array
y : 1D array the same length as x
Returns
(Pearson's correlation coefficient,
2-tailed p-value)
References
http://www.statsoft.com/textbook/glosp.html#Pearson%20Correlation
