Python uses NumPy Random number generation, including uniform distribution, Normal distribution, Poisson distribution, etc

Environmental construction: 1. Install Python: Visit the official Python website（ https://www.python.org/ ）Download the latest version of Python and follow the installation wizard to install it. 2. Install NumPy: Open the command line or terminal and execute the following command to install: pip install numpy Preparation work: 1. Import NumPy library: python import numpy as np Dependent class library: NumPy Example Dataset: This example does not rely on a specific dataset. Complete code example: python import numpy as np #Generate uniformly distributed random numbers uniform_random = np.random.uniform(low=0.0, high=1.0, size=(3, 3)) print("Uniform Random:") print(uniform_random) #Generate Normal distribution random number normal_random = np.random.normal(loc=0.0, scale=1.0, size=(3, 3)) print(" Normal Random:") print(normal_random) #Generate Poisson distribution random numbers poisson_random = np.random.poisson(lam=1.0, size=(3, 3)) print(" Poisson Random:") print(poisson_random) Output results: Uniform Random: [[0.94025622 0.04079137 0.92320586] [0.40899482 0.08222986 0.82379108] [0.04199387 0.34842895 0.73900607]] Normal Random: [[-0.77378323 -0.2774617 0.67839816] [ 0.07330237 -0.13561491 -0.81868307] [-0.32172272 -0.79865214 -1.39482353]] Poisson Random: [[0 0 3] [0 0 0] [3 2 1]] Note: The above code is only an example code, and the generated random number results may vary each time it is run.