def _get_corr(X, Y):
X = self._shallow_copy(X)
Y = self._shallow_copy(Y)
def _cov(x, y):
return window_aggregations.ewmcov(
x,
y,
self.com,
int(self.adjust),
int(self.ignore_na),
int(self.min_periods),
1,
)
x_values = X._prep_values()
y_values = Y._prep_values()
with np.errstate(all="ignore"):
cov = _cov(x_values, y_values)
x_var = _cov(x_values, x_values)
y_var = _cov(y_values, y_values)
corr = cov / _zsqrt(x_var * y_var)
return X._wrap_result(corr)
def std(self, bias=False, *args, **kwargs):
"""
Exponential weighted moving stddev.
"""
nv.validate_window_func("std", args, kwargs)
return _zsqrt(self.var(bias=bias, **kwargs))
