#importing the random module from numpy import random #applying the Pareto function res_arr= random.pareto(size=10,a=2.0) #printing the results print('1D array of size 10 having Pareto distribution with slope parameter 2 :\n') print(res_arr)
#importing the random module from numpy import random #here we are using Pareto function to generate Pareto distribution of size 3 x 4 with shape parameter 0.5 res_arr = random.pareto(size=(3,4),a=0.5) print('2D Pareto Distribution as output from Pareto() function:\n') #printing the result print(res_arr)
#importing the random module from numpy import random #here we are using Pareto function to generate Pareto distribution of size 7 x 8 x 9 res = random.pareto(size=(7,8,9), a=1) print('3D Pareto Distribution as output from pareto() function:\n') #printing the result print(res)
#importing all the required modules and packages from numpy import random import matplotlib.pyplot as mpl import seaborn as sb #here we are using Pareto function to generate distributions of size (1000,2) with slope parameter 1.5 sb.distplot(random.pareto(size=(1000,2),a=1.5), hist=False, label='Pareto Distribution') #plotting the graph mpl.show()