Numpy standard deviation

Numpy calculate standard deviation

import numpy
numbers = [1,5,6,7,9,11,13]
standard = numpy.std(numbers) #Calculates standard deviation
print(standard)

Numpy stdev

# Calculate standard deviaton based on population/sample
import numpy as np
values = [1,5,4,3,3,4]
# as default, std() calculates basesd on a population
# by specifying ddof=1, it calculates based on the sample
np.std(values)				# ==1.247219128924647
np.std(values ,ddof=1)		# ==1.3662601021279464

Source: honingds.com

Numpy standard deviation

aux = np.array( [[0, 0, 0], [1, 2, 3]] )
np.std( aux, axis=0 )

Std python

import numpy as np
values=[1,10,100]
print(np.std(values))
values=[1,10,100,np.nan]
print(np.nanstd(values))

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