>>> from sklearn import preprocessing
>>> import numpy as np

>>> a=np.array([[1.0,2.0,3.0], [4.0,5.0,9.0], [20,40.0, 80.0]])
>>> scale(a, axis=0)
array([[-0.87929684, -0.79227978, -0.79115821],
       [-0.5195845 , -0.6183647 , -0.61958173],
       [ 1.39888134,  1.41064448,  1.41073994]])
>>> a.std(axis=0)
array([  8.33999734,  17.24979871,  34.96982827])
>>> a.mean(axis=0)
array([  8.33333333,  15.66666667,  30.66666667])
>>> scale(a)
array([[-0.87929684, -0.79227978, -0.79115821],
       [-0.5195845 , -0.6183647 , -0.61958173],
       [ 1.39888134,  1.41064448,  1.41073994]])
>>> scale(a)*a.std(axis=0)+a.mean(axis=0)
array([[  1.,   2.,   3.],
       [  4.,   5.,   9.],
       [ 20.,  40.,  80.]])