Compute the standard deviation along the specified axis.
Returns the standard deviation, a measure of the spread of a distribution, of the array elements. The standard deviation is computed for the flattened array by default, otherwise over the specified axis.
Parameters:  a : array_like
axis : int, optional
dtype : dtype, optional
out : ndarray, optional
ddof : int, optional


Returns:  standard_deviation : {ndarray, scalar}; see dtype parameter above.

See also
Notes
The standard deviation is the square root of the average of the squared deviations from the mean, i.e., var = sqrt(mean(abs(x  x.mean())**2)).
The mean is normally calculated as x.sum() / N, where N = len(x). If, however, ddof is specified, the divisor N  ddof is used instead.
Note that, for complex numbers, std takes the absolute value before squaring, so that the result is always real and nonnegative.
Examples
>>> a = np.array([[1, 2], [3, 4]])
>>> np.std(a)
1.1180339887498949
>>> np.std(a, 0)
array([ 1., 1.])
>>> np.std(a, 1)
array([ 0.5, 0.5])