Python: Numpy standard deviation error

Question

This is a simple test

import numpy as np
data = np.array([-1,0,1])
print data.std()

>> 0.816496580928

I don\'t understand how this r

Answer 1

It is worth reading the help page for the function/method before suggesting it is incorrect. The method does exactly what the doc-string says it should be doing, divides by 3, because By default ddofis zero.:

In [3]: numpy.std?

String form: 
File:        /System/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/core/fromnumeric.py
Definition:  numpy.std(a, axis=None, dtype=None, out=None, ddof=0, keepdims=False)
Docstring:
Compute the standard deviation along the specified axis.

...

ddof : int, optional
    Means Delta Degrees of Freedom.  The divisor used in calculations
    is ``N - ddof``, where ``N`` represents the number of elements.
    By default `ddof` is zero.