scipy.stats.zipf() is a zipf discrete random variable. It is inherited from the of generic methods as an instance of the rv_discrete class. It completes the methods with details specific for this particular distribution.
Parameters :
x : quantiles
loc : [optional]location parameter. Default = 0
scale : [optional]scale parameter. Default = 1
moments : [optional] composed of letters [‘mvsk’]; ‘m’ = mean, ‘v’ = variance, ‘s’ = Fisher’s skew and ‘k’ = Fisher’s kurtosis. (default = ‘mv’).Results : zipf discrete random variable
Code #1 : Creating zipf discrete random variable
# importing library from scipy.stats import zipf
numargs = zipf .numargs
a, b = 0.2, 0.8
rv = zipf (a, b)
print ("RV : \n", rv)
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Output :
RV : scipy.stats._distn_infrastructure.rv_frozen object at 0x0000016A4D865848
Code #2 : zipf discrete variates and probability distribution
import numpy as np
quantile = np.arange (0.01, 1, 0.1)
# Random Variates R = zipf .pmf(a, b)
print ("Random Variates : \n", R)
# PDF x = np.linspace(zipf.ppf(0.01, a, b),
zipf.ppf(0.99, a, b), 10)
R = zipf.ppf(x, 1, 3)
print ("\nProbability Distribution : \n", R)
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Output :
Random Variates : nan Probability Distribution : [nan nan nan nan nan nan nan nan nan nan]
Code #3 : Graphical Representation.
import numpy as np
import matplotlib.pyplot as plt
distribution = np.linspace(0, np.minimum(rv.dist.b, 2))
print("Distribution : \n", distribution)
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Output :
Distribution : [0. 0.04081633 0.08163265 0.12244898 0.16326531 0.20408163 0.24489796 0.28571429 0.32653061 0.36734694 0.40816327 0.44897959 0.48979592 0.53061224 0.57142857 0.6122449 0.65306122 0.69387755 0.73469388 0.7755102 0.81632653 0.85714286 0.89795918 0.93877551 0.97959184 1.02040816 1.06122449 1.10204082 1.14285714 1.18367347 1.2244898 1.26530612 1.30612245 1.34693878 1.3877551 1.42857143 1.46938776 1.51020408 1.55102041 1.59183673 1.63265306 1.67346939 1.71428571 1.75510204 1.79591837 1.83673469 1.87755102 1.91836735 1.95918367 2. ]