NumPy | Create Random Valued Array Last Updated : 12 Jul, 2025 Comments Improve Suggest changes Like Article Like Report To create an array filled with random numbers, given the shape and type of array, we can use numpy.empty() method. Example: Python3 import numpy as np b = np.empty(3, dtype = float) print("Matrix b : \n", b) Output: [6.79249278e-310 6.79249278e-310 1.69375695e+190]SyntaxSyntax: np.empty(shape, dtype=None, order='C', *, like=None) Parameter: shape : Number of rowsorder : C_contiguous or F_contiguousdtype : [optional, float(by Default)] Data type of returned array. like: [optional] allows you to create an array with the same shape and data type as another array-like object More ExamplesLet's see some examples of how to create an array with random values in NumPy. Example 1We create 2 NumPy arrays with random values in this example. Array 'b' with size 2 and array 'a' which is a 2D array. Python3 # Python Program to create numpy array # filled with random values import numpy as geek b = geek.empty(2, dtype = int) print("Matrix b : \n", b) a = geek.empty([2, 2], dtype = int) print("\nMatrix a : \n", a) Output: Matrix b : [140489599921032 21301024] Matrix a : [[140489599921048 18650592] [ 10738656 140489568798064]] Example 2In this example, we create 2 random value arrays in NumPy. Array 'c' which is a 3x3 array and array 'd' which is a 5x3 array. Python3 # Python Program to create numpy array # filled with random values import numpy as geek # Python Program to create numpy array # filled with random values import numpy as geek c = geek.empty([3, 3]) print("\nMatrix c : \n", c) d = geek.empty([5, 3], dtype = int) print("\nMatrix d : \n", d) Output: Matrix c : [[ 1.37596097e-316 5.39314154e-317 5.39307830e-317] [ 5.39345774e-317 5.39345774e-317 6.93325440e-310] [ 5.39481741e-317 6.93325440e-310 8.69555537e-322]] Matrix d : [[140330665569272 23735792 0] [ 10739936 140330589556496 0] [ 0 0 10739904] [140330587337872 0 10915968] [ 0 10739904 0]] Comment More infoAdvertise with us Next Article Numpy - Array Creation S Shivam_k Follow Improve Article Tags : Python Python-numpy Python numpy-program Practice Tags : python Similar Reads Numpy - Array Creation Numpy Arrays are grid-like structures similar to lists in Python but optimized for numerical operations. The most straightforward way to create a NumPy array is by converting a regular Python list into an array using the np.array() function.Let's understand this with the help of an example:Pythonimp 5 min read Creating a one-dimensional NumPy array One-dimensional array contains elements only in one dimension. In other words, the shape of the NumPy array should contain only one value in the tuple. We can create a 1-D array in NumPy using the array() function, which converts a Python list or iterable object. Pythonimport numpy as np # Create a 2 min read Select random value from a list-Python The goal here is to randomly select a value from a list in Python. For example, given a list [1, 4, 5, 2, 7], we want to retrieve a single randomly chosen element, such as 5. There are several ways to achieve this, each varying in terms of simplicity, efficiency and use case. Let's explore different 2 min read Select random value from a list-Python The goal here is to randomly select a value from a list in Python. For example, given a list [1, 4, 5, 2, 7], we want to retrieve a single randomly chosen element, such as 5. There are several ways to achieve this, each varying in terms of simplicity, efficiency and use case. Let's explore different 2 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 Generate Random Float Number in Python Generating a random float number in Python means producing a decimal number that falls within a certain range, often between 0.0 and 1.0. Python provides multiple methods to generate random floats efficiently. Letâs explore some of the most effective ones.Using random.random()random.random() method 2 min read Like