numpy.random.standard_exponential() in Python Last Updated : 18 Aug, 2020 Summarize Comments Improve Suggest changes Share Like Article Like Report With the help of numpy.random.standard_exponential() method, we can get the random samples of standard exponential distribution and return the random samples. Syntax : numpy.random.standard_exponential(size=None) Return : Return the random samples as numpy array. Example #1 : In this example we can see that by using numpy.random.standard_exponential() method, we are able to get the random samples from standard exponential distribution and return the random samples. Python3 # import numpy import numpy as np import matplotlib.pyplot as plt # Using standard_exponential() method gfg = np.random.standard_exponential(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 standard_exponential() method gfg = np.random.standard_exponential(10000) plt.hist(gfg, bins = 100, density = True) plt.show() Output : Comment More infoAdvertise with us Next Article numpy.random.standard_exponential() in Python J jitender_1998 Follow Improve Article Tags : Python Python-numpy Python numpy-Random Practice Tags : python Similar Reads numpy.random.standard_gamma() in Python With the help of numpy.random.standard_gamma() method, we can get the random samples from standard gamma distribution and return the random samples by using this method. Standard gamma distribution Syntax : numpy.random.standard_gamma(shape, size=None) Return : Return the random samples as numpy arr 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.standard_normal() in Python With the help of numpy.random.standard_normal() method, we can get the random samples from standard normal distribution and return the random samples as numpy array by using this method. Syntax : numpy.random.standard_normal(size=None) Return : Return the random samples as numpy array. Example #1 : 1 min read numpy.random.geometric() in Python With the help of numpy.random.geometric() method, we can get the random samples of geometric distribution and return the random samples of numpy array by using this method. geometric distribution Syntax : numpy.random.geometric(p, size=None) Return : Return the random samples of numpy array. Example 1 min read numpy.random.standard_cauchy() in 1Python With the help of numpy.random.standard_cauchy() method, we can see get the random samples from a standard cauchy distribution and return the random samples. Standard cauchy distribution Syntax : numpy.random.standard_cauchy(size=None) Return : Return the random samples as numpy array. Example #1 : I 1 min read Like