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np.random.normal

import numpy as np
np.random.normal(loc=0.0, scale=1.0, size=None)  #Example below

mean, standard_deviation, samples = 23 ,0.8 ,1000

normal_samples = np.random.normal(loc=mean,scale=standard_deviation, size=samples)
'''Parameters
loc :float or array_like of floats
Mean (“centre”) of the distribution.

scale: float or array_like of floats
Standard deviation (spread or “width”) of the distribution. 
Must be non-negative.

size :int or tuple of ints, optional Output shape. 
If the given shape is, e.g., (m, n, k), 
then m * n * k samples are drawn. 
If size is None (default),
a single value is returned if loc and scale are both scalars.
Otherwise, np.broadcast(loc, scale).size samples are drawn.'''

'''Returns
outndarray or scalar
Drawn samples from the parameterized normal distribution.'''

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np.random.normal

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