numpy.random.wald() in Python Last Updated : 18 Aug, 2020 Comments Improve Suggest changes Like Article Like Report With the help of numpy.random.wald() method, we can get the random samples from Wald or Inverse Gaussian distribution and return the random samples as numpy array by using this method. Inverse Gaussian distribution Syntax : numpy.random.wald(mean, scale, size=None) Return : Return the random samples as numpy array. Example #1 : In this example we can see that by using numpy.random.wald() method, we are able to get the random samples from wald or inverse gaussian distribution and return the random samples. Python3 # import numpy import numpy as np import matplotlib.pyplot as plt # Using wald() method gfg = np.random.wald(5, 3.7, 5000) plt.hist(gfg, bins = 50, density = True) plt.show() Output : Example #2 : Python3 # import numpy import numpy as np import matplotlib.pyplot as plt # Using wald() method gfg = np.random.wald(10, 5.5, 10000) plt.hist(gfg, bins = 100, density = True) plt.show() Output : Comment More infoAdvertise with us Next Article numpy.random.wald() in Python J Jitender_1998 Follow Improve Article Tags : Python Python-numpy Python numpy-Random Practice Tags : python Similar Reads numpy.random.weibull() in Python With the help of numpy.random.weibull() method, we can get the random samples from weibull distribution and return the random samples as numpy array by using this method. Weibull Distribution Syntax : numpy.random.weibull(a, size=None) Return : Return the random samples as numpy array. Example #1 : 1 min read numpy.random.f() in Python With the help of numpy.random.f() method, we can get the random samples of F distribution and return the random samples of numpy array by using this method. Syntax : numpy.random.f(dfnum, dfden, size=None) Return : Return the random samples as numpy array. Example #1 : In this example we can see tha 1 min read numpy.random.rayleigh() in python With the help of numpy.random.rayleigh() method, we can get the random samples from Rayleigh distribution and return the random samples. Rayleigh distribution function Syntax : numpy.random.rayleigh(scale=1.0, size=None) Return : Return the random samples as numpy array. Example #1 : In this example 1 min read numpy.random.rand() in Python This article provides an in-depth exploration of the `numpy.random.rand()` function in Python. It covers the function's syntax, and definition, and includes illustrative examples with detailed explanations for better understanding. numpy.random.rand() Function Syntax The numpy.random.rand() function 3 min read numpy.random.zipf() in Python With the help of numpy.random.zipf() method, we can get the random samples from zipf distribution and return the random samples as numpy array by using this method. Zipf distribution Syntax : numpy.random.zipf(a, size=None) Return : Return the random samples as numpy array. Example #1 : In this exam 1 min read numpy.random.randn() in Python The numpy.random.randn() function creates an array of specified shape and fills it with random values as per standard normal distribution. If positive arguments are provided, randn generates an array of shape (d0, d1, ..., dn), filled with random floats sampled from a univariate ânormalâ (Gaussian) 3 min read numpy.random.shuffle() in python With the help of numpy.random.shuffle() method, we can get the random positioning of different integer values in the numpy array or we can say that all the values in an array will be shuffled randomly. Syntax : numpy.random.shuffle(x) Return : Return the reshuffled numpy array. Example #1 : In this 1 min read numpy.random.standard_t() in Python With the help of numpy.random.standard_t() method, we can get the random samples from standard T distribution having degree of freedom and return the random samples by using this method. Standard T distribution Syntax : numpy.random.standard_t(df, size=None) # Here df is degree of freedom. Return : 1 min read numpy.random.get_state() in Python With the help of numpy.random.get_state() method, we can get the internal state of a generator and return the tuple by using this method. Syntax : numpy.random.get_state() Return : Return the tuple having {tuple(str, ndarray of 624 units, int, int, float), dict} Example #1 : In this example we can s 1 min read numpy.random.power() in Python With the help of numpy.random.power() method, we can get the random samples from power distribution and return the random samples by using this method. power distribution Syntax : numpy.random.power(a, size=None) Return : Return the random samples as numpy array. Example #1 : In this example we can 1 min read Like