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a = [1,2,3,4,5]
numpy.std(a) # will give the standard deviation of a
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import numpy as np
data = [68,86,36,57,24,46,32,53] #define some data
data_std = np.std(data) #outputs 19.00493356999703
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import math
xs = [0.5,0.7,0.3,0.2] # values (must be floats!)
mean = sum(xs) / len(xs) # mean
var = sum(pow(x-mean,2) for x in xs) / len(xs) # variance
std = math.sqrt(var) # standard deviation
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a = np.array([[1, 2], [3, 4]])
>>> np.std(a)
1.1180339887498949 # may vary
>>> np.std(a, axis=0)
array([1., 1.])
>>> np.std(a, axis=1)
array([0.5, 0.5])