def std(self, values, axis=0, weights=None, dtype=None):
    'standard deviation over each group\n\n        Parameters\n        ----------\n        values : array_like, [keys, ...]\n            values to take standard deviation of per group\n        axis : int, optional\n            alternative reduction axis for values\n\n        Returns\n        -------\n        unique: ndarray, [groups]\n            unique keys\n        reduced : ndarray, [groups, ...]\n            value array, reduced over groups\n        '
    (unique, var) = self.var(values, axis, weights, dtype)
    return (unique, np.sqrt(var))
standard deviation over each group

Parameters
----------
values : array_like, [keys, ...]
    values to take standard deviation of per group
axis : int, optional
    alternative reduction axis for values

Returns
-------
unique: ndarray, [groups]
    unique keys
reduced : ndarray, [groups, ...]
    value array, reduced over groups
def std(self, values, axis=0, weights=None, dtype=None):
    'standard deviation over each group\n\n        Parameters\n        ----------\n        values : array_like, [keys, ...]\n            values to take standard deviation of per group\n        axis : int, optional\n            alternative reduction axis for values\n\n        Returns\n        -------\n        unique: ndarray, [groups]\n            unique keys\n        reduced : ndarray, [groups, ...]\n            value array, reduced over groups\n        '
    (unique, var) = self.var(values, axis, weights, dtype)
    return (unique, np.sqrt(var))