numpy.random.standard_t() in Python Last Updated : 18 Aug, 2020 Comments Improve Suggest changes Like Article Like Report 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 : Return the random samples as numpy array. Example #1 : In this example we can see that by using numpy.random.standard_t() method, we are able to get the random samples of standard T distribution with degree of freedom and return the numpy array. Python3 # import numpy import numpy as np import matplotlib.pyplot as plt # Using standard_t() method gfg = np.random.standard_t(5, 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_t() method gfg = np.random.standard_t(7, 10000) plt.hist(gfg, bins = 50, density = True) plt.show() Output : Comment More infoAdvertise with us Next Article numpy.random.get_state() 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_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.wald() in Python 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 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.standard_exponential() in Python 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 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 Like