Stairs.
corr
(other, lower=inf, upper=inf, lag=0, clip='pre')¶Calculates either correlation, autocorrelation or crosscorrelation.
All calculations are based off the Pearson correlation coefficient.
The calculation is between two step functions described by self and other. If lag is None or 0 then correlation is calculated, otherwise crosscorrelation is calculated. Autocorrelation is a special case of crosscorrelation when other is equal to self.
Parameters: 


Returns:  The correlation (or crosscorrelation) between self and other 
Return type:  float 
See also
Examples
>>> fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(12,5), sharey=True, sharex=True)
>>> for ax, title, stair_instance in zip(axes, ("s1", "s2"), (s1, s2)):
... stair_instance.plot(ax, label=title)
... ax.set_title(title)
>>> s1.corr(s2)
0.24687803791136045
>>> s2.corr(s1)
0.24687803791136045
>>> s1.corr(s2, lower=0, upper=6)
0.27500954910846337
>>> # autocorrelation with lag 1
>>> s1.corr(s1, lower=1, upper=5, lag=1)
0.8660254037844386
>>> # crosscorrelation with lag 1
>>> s1.corr(s2, lower=1, upper=5.5, lag=1)
0.4961389383568339
>>> # crosscorrelation with lag 1
>>> s1.corr(s2, lower=1, upper=4.5, lag=1, clip='post')
0.4961389383568339